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i
ISBN: 978-9970-9269-1-6
© The Eastern Africa Agricultural Producvity Project (EAAPP)
All rights reserved. The contents of this publicaon may be reproduced for non-
commercial purpose provided the Eastern African Agricultural Producvity Project
(EAAPP) and the Associaon for Strengthening Agricultural Research in Eastern and
Central Africa (ASARECA) are acknowledged.
Correct citaon: Kabirizi, J.; Muyekho, F.; Mulaa, M; Msangi, R.; Pallangyo, B.; Kawube, G.;
Zziwa, E.; Mugerwa, S.; Ajanga,S.; Lukwago, G.; Wamalwa N.I. E; Kariuki, I.; Mwesigwa,
R.; Nannyeenya-Ntege, W.; Atuhairwe, A.; Awalla, J.; Namazzi, C.; Nampijja, Z. 2015.
Napier grass feed resource: producon, constraints and implicaons for smallholder
farmers in Eastern and Central Africa.
ISBN: 978-9970-9269-1-6
NAPIER GRASS FEED RESOURCE:
PRODUCTION, CONSTRAINTS AND
IMPLICATIONS FOR SMALLHOLDER
FARMERS IN EASTERN AND CENTRAL
AFRICA
9 7 8 9 9 7 0 9 2 6 9 1 6
ii
© The Eastern African Agricultural Productivity Project (EAAPP)
All rights reserved. The contents of this publication may be reproduced for non-commercial
purpose provided the Eastern African Agricultural Productivity Project (EAAPP) and the
Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA) are
acknowledged.
Correct citation: Kabirizi, J.; Muyekho, F.; Mulaa, M; Msangi, R.; Pallangyo, B.; Kawube, G.; Zziwa,
E.; Mugerwa, S.; Ajanga,S.; Lukwago, G.; Wamalwa N.I. E; Kariuki, I.; Mwesigwa, R.; Nannyeenya-
Ntege, W.; Atuhairwe, A.; Awalla, J.; Namazzi, C.; Nampijja, Z. 2015. Napier grass feed resource:
production, constraints and implications for smallholder farmers in Eastern and Central Africa.
ISBN: 978-9970-9269-1-6
iii
Preface
Milk is an important part of the diets of people in Eastern and Central Africa (ECA) and makes a
major contribution to national food security, income generation and rural development. Smallholders
produce the vast majority of milk in ECA. Napier grass (Pennisetum purpureum Schumach) constitutes
40-80 percent of forages used by smallholder dairy farmers. The productivity of Napier grass in
the region is currently threatened by stunt and smut diseases causing yield reduction of over 40
percentage.
Responding to Eastern Africa Agricultural Productivity Project (EAAPP) Thematic Area 4: fodder
and pasture research along the dairy value chain, the regional project “Enhancing adoption of Napier
grass and alternative fodder grasses resistant/tolerant to stunt and smut diseases for increased feed
availability in smallholder systems in Eastern and Central Africa region” generated and disseminated
technologies and innovations for managing Napier stunt and smut disease in the ECA. The project
improved capacity of stakeholders to utilize technologies for managing smut and stunt diseases
through awareness creation and encouraged information sharing to enhance the adoption of high
yielding alternative forages and tolerant Napier grass accessions in the region to alleviate feed
shortages, improve milk yield and household income. The grasses tolerant to stunt and smut diseases
produced higher dry matter yields and were integrated into the cropping systems.
Adoption of genetically diverse, high yielding and climatically adapted fodder plants will improve
the performance of the dairy sector, alleviate the current shortages and environmental crises
associated with forage diseases, pests and climate change and create employment opportunities. This
will contribute to food and nutritional security, social and gender protection, poverty alleviation and
environmental sustainability.
The lessons learned are particularly valuable for dairy farmers, students, development parteners,
policy makers developing national and regional dairy strategies and for those planning national food
security and human development programmes.
This book is one of numerous outputs of a collaborative project between the Eastern Africa
Agricultural Productivity Programme (EAAPP), Association for Strengthening Agricultural Research
in Easterns and Central Africa (ASARECA), National Agricultural Research Organization (Uganda);
National Livestock Resources Research Institute (Uganda); National Crops Resources Research
Institute (Uganda); Kenya Agricultural and Livestock Research Organisation (Kenya); International
Livestock Research Institute (Kenya); International Centre of Insect Physiology and Ecology (ICIPE-
Kenya); International Centre for Tropical Agriculture (CIAT-Kenya); Rwebitaba Zonal Agricultural
Research and Development Institute (Uganda); Biosciences Eastern and Central Africa - International
Livestock Research Institute (BecA - ILRI) Hub (Kenya); Alupe Research Station (Kenya); Department
of Biological Sciences, Ministry of Agriculture Food Security and Cooperatives, Dar es Salaam
(Tanzania); Masinde Muliro University of Science and Technology (Kenya); Makerere University
(Uganda) and Tanzania Livestock Research Institute (Tanzania).
I acknowledge nancial and technical support from the World Bank and ASARECA; Special thanks
to the regional project research team for contributing to the project outputs.
Dr. Tobias Onyango
Coordinator, Regional Dairy Centre of Excellence, Naivasha, Kenya
July 2015
iv
Table of Contents
Preface ....................................................................................................................................................... ii
Abbreviations/Acronyms ...................................................................................................................... x
CHAPTER 1: Smallholder dairy industry in Eastern and Central Africa (ECA)
1.1 Smallholder Agriculture in Eastern and Central Africa: Trends,
Constraints and Opportunities ................................................................................................. 1
1.2 Smallholder dairy production in ECA ..................................................................................... 1
1.3 Major constraints to smallholder dairy production in ECA ................................................. 3
CHAPTER 2: Eastern Africa Agricultural Productivity Project (EAAPP)
2.1 Background .................................................................................................................................. 9
2.2 The Regional Dairy Centre of Excellence (RDCoE) overview .............................................. 9
2.3 Thematic areas of the RDCoE ................................................................................................... 14
2.4. RDCoE approved projects ......................................................................................................... 11
CHAPTER 3: Napier grass: challenges, establishment, management and utilization
3.1 Introduction ................................................................................................................................. 12
3.2. The role of Napier grass in smallholder dairy farming systems ......................................... 12
3.3 Establishment, management and utilization of Napier grass .............................................. 13
3.4 Challenges to production of Napier grass .............................................................................. 18
3.5 Napier grass head smut ............................................................................................................. 19
3.6 Napier grass stunt disease ......................................................................................................... 19
3.7 Efforts to improve Napier grass productivity in ECA .......................................................... 20
CHAPTER 4: Status of Napier grass stunt diseases in the East African region
4.1 Status, Napier stunt and smut disease and farmers management
practices in Uganda .................................................................................................................... 22
4.2 Napier Stunt Disease in Uganda: farmer perception and effect
on fodder yield ............................................................................................................................ 28
4.3 Status, Napier stunt and smut disease and farmers management
practices in Western and Central Kenya ................................................................................. 33
4.4 Status of Napier grass stunt diseases in southern highland zones
of Tanzania and management strategy ................................................................................... 42
4.5 Status of Napier stunt disease in Rwanda .............................................................................. 47
v
CHAPTER 5: Napier grass resource evaluation
5.1 Evaluation of Napier grass (Pennisetum Purpureum) accessions
for dry matter yield, nutritive quality and tolerance to Napier
stunt disease in Uganda ............................................................................................................. 54
5.2 Epiphytology of Napier head smut disease and progress in the
search for tolerant cultivars ....................................................................................................... 62
5.3 Evaluation of Napier stunt and smut tolerant napier grass clones
and alternative fodder grasses for forage yield in Kenya ..................................................... 75
5.4 Screening Napier accessions for resistance/tolerance to NSD
using the loop-mediated isothermal amplication of DNA (LAMP) ................................. 78
CHAPTER 6: Epidemiology of Napier stunt disease in Eastern and Central African region
6.1 Genetic Characterization of Alupe Napier Grass Accessions
Based on Simple Sequence Repeat Markers ........................................................................... 94
CHAPTER 7: Evaluation of alternative forages and feed resources to improve feed
availability in smallholder dairy production systems
7.1: Homecoming of Brachiaria: improved hybrids prove useful for
African animal agriculture ........................................................................................................ 102
7.2 Impact of promoting Brachiaria hybrid cv. Mulato 11 as seed crop
in smallholder crop-livestock systems Uganda ..................................................................... 106
7.3 Production characteristics of smallholder dairy farming in the
Lake Victoria agro-ecological zone, Uganda .......................................................................... 111
7.4 Prioritization of agro-industrial by-products for improved productivity
on smallholder dairy farms in the Lake Victoria Crescent, Uganda ................................... 116
7.5 Prioritization of crop residues for improving productivity on smallholder
dairy farming households in the Lake Victoria Crescent, Uganda ..................................... 128
7.6 Effect of supplementing lactating crossbred animals with Bentonite as a
mineral supplement on milk production ................................................................................ 138
7.7 Effect of supplementing lactating crossbred animals with Bentonite
as a mineral supplement on milk production ........................................................................ 148
7.8 Multiplication of improved Brachiaria planting materials:
An innovative approach: Short communication .................................................................... 152
vi
List of Tables
4.1.1: Gender and age classication of respondents ........................................................................ 24
4.1.2: Means of livestock types in the different Agro-ecological Zones ....................................... 24
4.1.3: Land Ownership and Tenure .................................................................................................... 25
4.1.4: Occurance of Napier stunt disease in the three agro-ecological zones ............................... 26
4.1.5: Sources of Napier planting materials ...................................................................................... 27
4.2.1: Incidence and extent of Napier stunt disease in Masaka district ........................................ 29
4.2.2: Major management practices used by farmers to reduce NSD incidence .......................... 30
4.2.3: Results of PCR-tests of leaf samples of stunted Napier grass from
10 districts in Uganda ................................................................................................................. 31
4.3.1: Proportion of male, female adults and youths per household in
western and Central Kenya ....................................................................................................... 34
4.3.2: Number of improved dairy cattle per household in western and
Central Kenya .............................................................................................................................. 34
4.3.3: Percentage (%) range of milk production in litres per day
during good (rain season) months in western and Central Kenya ..................................... 35
4.3.4: Average milk yield in litres per day during the dry season in
western and Central Kenya ....................................................................................................... 35
4.3.5: Dairy cattle production system in western and Central Kenya ........................................... 35
4.3.6: Sources forage available to farmers in western and Central Kenya .................................... 36
4.3.7: Important copping strategies when fodder is short supply in
western and Central Kenya ....................................................................................................... 36
4.3.8: Sources of purchased fodder in western and Central Kenya ............................................... 36
4.3.9: Area planted Napier grass in Western and Central Kenya .................................................. 37
4.3.10: Preferred Napier grass varieties in Western and Central Kenya ........................................ 37
4.3.11: Criteria used by farmers when choosing Napier grass variety
to plant in western and Central Kenya .................................................................................... 37
4.3.12: Period of maintaining Napier grass stand in same farm in western
and Central Kenya ...................................................................................................................... 38
4.3.13: Number of harvest made on Napier grass by farmers in western
and Central Kenya ...................................................................................................................... 39
4.3.14: Napier grass management practices adopted by farmers to
improve yields in western and Central Kenya ....................................................................... 39
4.3.15: Presence of Napier stunt farmers own farm and within the district in
western and Central Kenya ....................................................................................................... 40
4.3.16: Napier stunt disease severity in farmers own farm and within
the district in western and Central Kenya ............................................................................... 40
4.3.17: Napier head smut disease severity within farmers own farm
and within the district in western and Central Kenya ......................................................... 41
4.4.1: NSD infected villages in Muheza, Lushoto and Meru districts ........................................... 43
4.4.2: Households with NSD infected elds in Muheza, Lushoto and
Meru Districts .............................................................................................................................. 44
4.4.4: Composition of stakeholders who received information on
NSD management ....................................................................................................................... 45
vii
4.5.1: Gender disaggregated household composition (%) and average
number of persons (heads per 100 households) by Provinces in Rwanda ......................... 48
4.5.2: Level of participation of different gender relations in Napier
Smut and Stunt ........................................................................................................................... 49
4.5.3: Education levels among dairy households encountered during
Napier Smut and Stunt Disease survey in Rwanda .............................................................. 49
4.5.4: Percentage of farmers using different housing structures ................................................... 50
4.5.5: Percentage (%) of farmers and number of parcels owned ................................................... 50
4.5.6: Napier varieties used ................................................................................................................. 51
4.5.7: Reasons for planting Napier grass ........................................................................................... 51
5.1.1: Effect of Napier stunt disease on herbage biomass yield of
introduced Napier grass accessions ........................................................................................ 56
5.1.2: Nutrient content (%) of different Napier grass accessions .................................................. 58
5.2.1: The eighteen presumed tolerant accessions selected from
glasshouse level screening ........................................................................................................ 66
5.2.2: Smutting proportions of the various screened susceptible accessions ............................... 67
5.3.1: Dry matter yields of Napier stunt disease and smut disease
torelant at KARLO Kakamega in western Kenya ................................................................. 76
5.3.2: Dry matter yield of selected alternative fodder grasses and,
Napier stunt disease and smut Disease tolerant clones at
KARLO Kakamega and KARLO Alupe in western Kenya ................................................. 76
5.4.1: Napier grass accessions, locality of origin and Dry matter yield
recorded in Kenya ...................................................................................................................... 80
5.4.2: Proportions of data on symptom appearance in Napier accessions ................................... 87
5.4.3: Mean proportional changes in plant height, leaf length and width ................................... 89
6.1.1: SSR primers used to assess genetic diversity in 23 Napier clones ...................................... 97
6.1.2: Genetic diversity parameters averaged across all groups and
loci for 23 Napier grass clones .................................................................................................. 98
6.1.3: Mean number of effective loci (ne), shannon index (i),
proportion of private alleles, expected heterozygosity he) and
percentage polymorphism across the 23 Napier grass clones ............................................. 98
6.1.4: Nei’s Unbiased genetic distance of the 23 Napier grass clones
based on SSR analysis ................................................................................................................ 99
7.1.1: Fodder availability and quality, and feeding period for different
forage banks ................................................................................................................................ 104
7.1.2: Socio-economic benets of introduced forages ...................................................................... 105
7.2.1: Commercially available hybrid Brachiaria cultivars ............................................................. 107
7.3.1: Enterprise budgets on Brachiaria Mulato for cattle and
non-cattle households ................................................................................................................ 113
7.3.2: Financial analysis of effects of Napier Stunt Disease on resource
use and cash ow ........................................................................................................................ 114
7.4.1: Household demographic prole of the smallholder dairy farmers
in Lake Victoria agro-ecological zone of Uganda .................................................................. 119
7.4.2: Mean ± SD dairy herd structure among smallholder dairy
farmers in Lake Victoria agro-ecological zone, Uganda ....................................................... 120
7.4.3: Smallholder dairy farmers ranking of challenges in Lake Victoria
viii
Agro-ecological Zone ................................................................................................................. 121
7.4.4: Smallholder dairy farmers ranking of feed resources utilization
in Lake Victoria agro-ecological zone ...................................................................................... 122
7.4.5: Labour activities in smallholder dairy farming system of
Lake Victoria Agro-ecological zone, Uganda ......................................................................... 123
7.4.6: Smallholder dairy farmer’s rankings of challenges on milk
marketing in Lake Victoria agro- ecological zone, Uganda ................................................. 124
7.5.1: Smallholder dairy farmers’ rankings of agro-industrial by-
products utilization in LVZ, Uganda ....................................................................................... 130
7.5.2: Farmers’ rankings of factors that enhance use of agro-industrial
by-products unprocessed .......................................................................................................... 131
7.5.3: Farmers ranking of spatial and temporal variability on
availability of agro-industrial by-products in LVZ ............................................................... 132
7.5.4: Smallholder dairy farmers’ rankings of limitation to utilizing
of Agro-industrial by-products ................................................................................................ 133
7.5.5: Methods used by the farmers to store, process and preserve
agro-industrial by-products in LVZ, Uganda ........................................................................ 133
7.6.1: Farmers ranking of crop residues ........................................................................................... 140
7.6.2: Methods applied by farmers to store, process and preserve crop residues ..................... 142
7.7.1: Amount and cost of ingredients used in formulation of concentrates ............................... 149
ix
List of Figures
4.1.1: Disciminate analysis biplot showing the varieties and propagation
methods of Napier grass in the three agro- ecological zones ............................................... 25
4.1.2: Severity of Napier stunt disease amongst farmers ................................................................ 26
4.2.1: Effect of Napier stunt disease on plant height, root length,
herbage biomass yield and number of shoots ........................................................................ 30
4.4.1: Sampled households in Lushoto, Muheza and Meru districts. ........................................... 43
4.4.2: NSD infected households in Muheza, Lushoto and Meru districts .................................... 44
4.5:1: Percentage of male and female headed households in sample
districts during Napier Smut and Stunted disease survey .................................................. 48
4.5.2: Land use pattern (proportion of farmers) for Napier production
in selected districts of Rwanda ................................................................................................. 52
4.5.3: The proportion of farmers that recognized specic symptoms
of the stunt disease ..................................................................................................................... 52
4.5.4: Napier stunt disease incidences (%) in selected districts of Rwanda ................................. 53
4.5.5: Napier stunt disease severity among selected districts of Rwanda .................................... 53
5.1.1: Monthly rainfall totals for NaCRRI (2012) .............................................................................. 55
5.1.2: Napier stunt disease progress on some of the Napier accessions over time ..................... 57
5.2.1: A smutted Napier crop head .................................................................................................... 64
5.2.2: Potential effects of co-evolution on the selected asymptomatic
(tolerant) Napier grass accessions in a region based selection
scenario during screening for resistant accessions ................................................................ 69
5.2.3: Proportions of asymptomatic accessions out of the total selected
per neighbour joining group showing the selection orientation
towards some groups in having the largest number of accessions
expressing resistance selected against the head smut disease ............................................. 70
5.2.4: Proportions of asymptomatic versus symptomatic accessions
selected within each neighbour joining group ....................................................................... 70
5.2.5: Global chart showing the Z- region (Zambezi valley) where
napier grass is indigenous and the proximity of each neighbour
joining group (NJG) to the region in terms of majority member
accession origin ........................................................................................................................... 70
5.2.5: Trend of Napier grass accessions’ selection against time without
cutting back in experiment one’s screening showing the 21st
and 24th weeks that represent the critical timeline that marks the
onset of resistance and the harvest point respectively .............................................................
5.2.6: Trend of Napier grass accessions’ selection against time
without cutting back in experiment one’s screening showing
the 21st and 24th weeks that represent the critical timeline
that marks the onset of resistance and the harvest point respectively ............................... 72
5.3.3: Napier grass cumulative dry matter yields from six harvests at each ............................... 77
5.4.1: Arrangement of potted Napier plants in experimental cages
during inoculation. The middle plant is the source of inoculum.
The six plants surrounding it get inoculated by 50 insect vectors
(Maiestas banda) ......................................................................................................................... 83
x
5.4.2: A set up for collecting honeydew of Maiestas banda
(adopted from Khan and Saxena 1984) ................................................................................... 84
5.4.3: Comparisons of Napier accessions at LAMP 1 screening .................................................... 85
5.4.4: A chart of comparisons of Napier accessions at LAMP 2 screening ................................... 86
5.4.5: A chart showing comparisons of Napier accessions at LAMP 3 screening ....................... 86
5.4.6: A picture of the third re-growth of Napier accession 16807 four
months after inoculation with the NSD Phytoplasma ......................................................... 88
5.4.7: Amplication of accession 16807 DNA of the third re-growth
(1 -100 Bp ladder (Genscript), - negative, + positive, 6 positive plants .............................. 88
5.4.8: A picture of the third re-growth of Napier accession 16789
four months after inoculation with the NSD phytoplasma ................................................ 88
5.4.9: Amplication of accession 16789 DNA of the third re-growth
(1 -100 Bp ladder (Genscript), - negative, + positive, 11plants
negative by LAMP at the third month of screening).............................................................. 88
5.4.10: A morphological comparison of the accessions 16789
(resistant), 16807 (tolerant) and 16840 (susceptible) after
four months of incubation ......................................................................................................... 88
5.4.11a. Bluish amino acid spots for the honey dew droppings of Maiestas
banda on Bana variety (control) ............................................................................................... 89
5.4.11b.Bluish amino acid spots for the honey dew droppings of Maiestas
banda on accession N16789 (resistant) ................................................................................... 89
6.1.1: PCoA scatter plot showing the clustering of the 23 Napier grass clones .......................... 96
6.1.2: UPGMA neighbour joining dendogram of 23 napier grass clones
computed from 17 SSR markers using darwin hierachial clustering ................................. 97
7.1.1: Maps showing study sites ......................................................................................................... 103
7.1.2: Drought tolerant Brachiaria hybrid cv Mulato 11 ................................................................. 103
7.4.1: Map of Uganda showing the study locations of Buikwe, Jinja
and Mayuge districts ................................................................................................................. 117
7.4.2: The highest level of education of the household heads in the
smallholder dairy farming system in Lake Victoria
Agro-ecological Zone, Uganda ................................................................................................. 119
7.4.3: The major sources of income of household heads of smallholder
dairy farmers in Lake Victoria agro-ecological zone, Uganda .......................................... 120
7.5.1: Map of Uganda showing the location of Buikwe, Jinja and
Mayuge districts ......................................................................................................................... 129
7.6.1: Map of Uganda showing the location of Buikwe, Jinja and
Mayuge districts ......................................................................................................................... 139
7.6.2: Spatial and temporal variability of crop residues in the study areas ................................. 142
7.7.5: Variations in milk yield during the treatment ...................................................................... 150
Publications .............................................................................................................................................. 154
Journal publications ................................................................................................................................ 154
Conference papers .................................................................................................................................. 155
Books ......................................................................................................................................................... 157
Farming information materials, manuals ............................................................................................ 158
xi
Abbreviations/Acronyms
AfDB African Development Bank
AEZ Agro-Ecological Zones
APSK Animal Production Society of Kenya
ASAL Arid and semi-arid lands
ASARECA Association for Strengthening Agricultural Research in Eastern and Central Africa
CAADP Comprehensive Africa Agricultural Development Programme
C.A.N. Calcium ammonium nitrate
CIAT International Center for Tropical Agriculture
DAP Di-ammonium Phosphate
EAAPP: Eastern African Agricultural Productivity Project
ECA Eastern and Central Africa
ESAZ Eastern Semi-Arid Zone
FYM Farm Yard Manure
ft feet
GDP Gross Domestic Product
HIV/AIDS Human immunodeciency virus infection/acquired immune deciency syndrome
IFAD International Fund for Agricultural Development
ICIPE International Centre of Insect Physiology and Ecology
BecA - ILRI Biosciences eastern and central Africa - International Livestock Research Institute Hub
ILRI International Livestock Research Institute
IPM Integrated Pest Management
KALRO Kenya Agricultural and Livestock Research Organisation
KW4 Kawanda variety 4
LVB Lake Victoria Basin
m Meter
MDGs Millennium Development Goals
MoLD Ministry of Livestock Development
N Nitrogen
NaCRRI National Crops Resources Research Institute
NaLIRRI National Livestock Resources Research Institute
NARS National Agricultural Research Systems
NEPD New Partnership for African Development
NGO Non-Government Organization
NSD Napier Stunt Disease
P Phosphorus
P99 Pennisetum 99 hybrid
P2O5 Single super phosphate
PCU Project Coordination Unit
RAB Rwanda Agriculture Board
RCoE Regional Centre of Excellence
RDCoE Regional Dairy Centre of Excellence
xii
SDP Smallholder Dairy Research and Development Project
T Tonne
TBC Tanzania Broadcasting Corporation
TALIRRI Tanzania Livestock Research Institute
TSAP Tanzania Society of Animal Production
UNDP United Nations Development Programme
USD United States Dollars
WR Western Rangelands
1
CHAPTER 1: Smallholder Dairy Industry in Eastern and Central Africa
1 Jolly Kabirizi and 2Francis N. Muyekho
1 National Livestock Resources Research Institute, P.O. Box 96, Tororo, Uganda
2 Department of Biological Sciences, Masinde Muliro University of Science and Technology,
P.O. Box 190-50100, Kakamega, Kenya
1.1 Smallholder Agriculture in Eastern and Central Africa (ECA): Trends, Constraints and
Opportunities.
Ethiopia, Kenya, Tanzania and Uganda can be characterized as “agriculture-based,” that is,
agriculture is the backbone of these economies (Adeleke Salami et al., 2011). In Ethiopia and Tanzania,
agriculture remains the main contributor to the Gross Domestic Product (GDP), contributing 47%
and 43%, respectively. In Uganda and Kenya, however, the rapid development of the service sector
with a growth rate of about 9.5 percent, has outpaced agriculture, contributing 45% and 60% of the
GDP, respectively, far above agriculture’s contribution of 30 and 34%. Nevertheless, agriculture still
accounts for about 75% of the labor force in all the ECA countries, underscoring the importance of the
sector in job creation and poverty reduction across countries.
Agriculture is dominated by smallholder farmers who occupy the majority of land and produce most
of the crop and livestock products. According to Adeleke Salami et al. (2011), African smallholder
farmers can be categorized on the basis of: (i) the agro-ecological zones in which they operate; (ii) the
type and composition of their farm portfolio and landholding; or (iii) on the basis of annual revenue
they generate from farming activities. In areas with high population densities, smallholder farmers
usually cultivate less than one hectare of land, which may increase up to 10 ha or more in sparsely
populated semi-arid areas, sometimes in combination with livestock of up to 10 animals dened
smallholder farmers on the basis of land and livestock holdings, cultivate less than 2 hectares of land
and own only a few heads of livestock.
The key long-standing challenge of the smallholder farmers is low productivity stemming from the
lack of access to markets, credit, and technology, compounded by the volatile food and energy prices
and very recently by the global nancial crisis.
1.2 Smallholder Dairy Production in ECA
Livestock, and especially cattle, have historically played multiple roles both in economic life and in
socio-cultural traditions of African people. Cattle have been valued not simply as a source of food
(milk, blood and meat) and hides but also as a visible form of wealth and a source of social prestige.
In certain parts of the region, cattle still provide a valuable source of draft and traction power both
for the plough and for transportation carts whereas in Arid and semi-arid lands, cattle still provide a
valuable security against famine.
2
The dairy industry plays an important role in food security, employment creation, income generation,
and enhancement of the livelihoods of dairy farmers, traders, processors and all participants engaged
in the entire milk supply chain (Muia et al 2011). Studies by Njarui et al (2011) showed that milk and
milk products are an important dietary component for all social strata. In coastal lowlands of Kenya,
Nicholson et al (2004) reported that for each cow owned, mean household income increased by 53%
compared with households without dairy cows.
Studies conducted in ECA region have shown that women are the caretakers where dairy cattle are
stall-fed (Kabirizi, 2006; Njarui et al., 2012). This provides women with access to the benets of dairy
keeping, such as the opportunity to sell products like milk. The income helps the women to meet their
immediate needs and to enhance their status in the household and at the community level. Given the
current trade and economic imbalances.
Dairy development may play a crucial role in diversifying the income base of farmers who are affected
by low prices for primary commodities on the world market.
The contribution of dairy cattle to the reduction of child mortality is well demonstrated through the
enhanced capacity of poor households to meet health related expenses from the income earned from
sale of milk and other products (Nicholson et al., 2004). Besides, studies have indicated a generally
positive interaction between livestock and human health, as high value nutrients from milk contribute
to the health conditions of vulnerable. For maternal health, milk and milk products, and occasionally
meat contribute massively to the nutritional status of women. Dairy production is very useful as a
mitigation strategy for HIV/AIDS affected families (Vorster et al. 2004).
Dairy plays crucial roles in recycling of waste products and residues from cropping systems through
feeding while dung and urine from the livestock is a good source of manure for enhanced soil fertility
in cropping systems. In the high potential areas, the economic importance of the cow has increasingly
shifted to commercial milk production while at the same time retaining the complementary role of
sustaining soil fertility for sustainable agricultural production. In such area, increasing population
pressure interacting with the need to sustain soil fertility has driven the change in production structure
with dairying becoming an important component of agricultural production
Eastern Africa is Africa’s most promising region for dairy production. The region holds over 40 percent
of Africa’s cattle resource of about 222 million (FAO, 2010). There are differences in development of
dairy sub-sector between countries within the ECA region, with Kenya having a longer history in
dairy farming than the other countries (Omore et al., 1996).
The dairy industry’s contribution to Gross Domestic Product (GDP) is 3 percent in Kenya, 5 percent
in Tanzania, and 8 percent in Uganda (FAO, 2011). Milk production is estimated to be ve million
tonnes per year, 60 percent of which is produced in Kenya (FAO, 2011). More than 80 percent of the
milk is traded informally as raw milk. Within sub-Saharan Africa, Eastern Africa has the highest
concentration of traditional cattle and improved dairy cattle. Kenya, with over 2.7 million improved
cattle, accounts for about 75 percent of improved dairy cattle in Eastern and Southern Africa, and
about 20 percent of the estimated 17.9 million tonnes of milk produced in sub-Saharan Africa in 2003
(Muriuki and Thorpe 2001). Smallholder dairying dominates in the region and Kenya is the major
regional producer, processor and exporter of dairy products.
Exotic dairy cattle were rst introduced in Kenya from Europe by white settlers in 1920s, who
established dairy farms in Central highlands and Rift Valley region. Although few farmers in the
semi-arid region of Eastern Kenya commenced dairy farming in 1960s, it was not until in 1980s and
3
onwards when there was accelerated adoption of dairy farming (Njarui et al 2009). On the other hand,
dairy farming is relatively young in Uganda with the rst introduction of dairy cattle from Germany
in 1980s (Kabirizi et al., 2006). In the recent past, there has been a steady growth of dairy farming in
the region and it has increasingly become an important source of livelihoods.
Smallholder dairy farming is growing in Tanzania at a rate of 6% per year, with an estimated 190,000
registered farmers (Anon, 2002). Despite the fact that smallholder dairy farming is widespread in
different parts of Tanzania where the climate is appropriate, the supply of milk and milk products
in these regions has not kept pace with the rapid increase in the human population. Productivity in
existing smallholder dairy herds is constrained by the small size of farms and their distance from
markets, animal health and reproductive problems and lack of good-quality animal feeds in sufcient
quantities. Other constraints include lack of infrastructure for input and output markets, unfavourable
regulatory and taxation policies, poor ow of information, restricted access to credit and limited
supply of dairy cattle. Nevertheless, the sector is acknowledged for its contribution to household food
security, employment opportunities and as a regular source of income for farmers. Dairy production
integrated into rural, peri-urban and urban smallholder mixed farming systems may increase and
stabilize farm incomes and act as a catalyst for agricultural development and improved standards of
living. The authors conclude that smallholder dairy production is an important undertaking and, if
adequately supported by appropriate policies and adaptive research technologies, it may contribute
signicantly towards the household economy, self-sufciency in milk and national gross domestic
product.
The expanding smallholder dairy industry in the ECA region is fuelled by increased urbanization and
improved income, resulting in high demand for milk and milk products. Consequently, many dairy
farms have been established in peri-urban areas of major commercial urban centres with increased
adoption of improved dairy cattle of European breed (Bos taurus); Holstein-Friesian, Aryshire,
Guernsey, Jersey and their crosses with local zebu (Bos inducus). The production is mainly dominated
by smallholders who own few dairy cattle. As smallholder farmers make major shift towards market-
oriented dairy production, they are faced with several challenges.
1.3 Major Constraints to Smallholder Dairy Production in ECA
Smallholder agriculture in the Uganda, Kenya, Ethiopia and Tanzania has been facing numerous
constraints. While some are unique to each of the countries, most are of a similar nature, implying that
common solutions would address them across countries
(a) Land tenure, access rights and land management
The uncertainties regarding land tenure and the inadequate access to land have been a critical challenge
to smallholder farming in ECA region (Kabirizi et al., 2011). The constraints related to the tenure
system, such as insecurity of land tenure, unequal access to land, lack of a mechanism to transfer
rights and consolidate plots, have resulted in under-developed agriculture, high landlessness, food
insecurity, and degraded natural resource. Furthermore, the available land in East Africa is overly
subdivided into small and uneconomic units, resulting generally in fragmented production systems
and low productivity. In fact, the farm sizes range from as low as about 1ha per household in Ethiopia
and 2.0 ha in Tanzania and 2.5ha in Uganda and Kenya (Njarui et al., 2012).
The land ownership issues go well beyond small sizes of plots. For example, in Ethiopia, all land
4
is state-owned, according to the country’s 1994 constitution. In practice, traditional land tenure
arrangements prevail as an outcome of subsistence agriculture, with peasant associations responsible
for allocating land to residents (Kamara et al 2004).
Equally important, in terms of access to additional land, is proper management of the existing one.
According to Kimaru and Jama (2005), in East Africa sustained gains to agricultural productivity are
threatened by land degradation, especially land erosion and loss of fertility. Adeleke Salami et al.
(2011) recommended that clear land-use and agricultural policies need to be developed to provide a
framework for researchers, extension workers and smallholder farmers on environmentally-sensitive
practices. Nevertheless, the lack of clarity of property rights and un-equitable access to land exacerbate
the land degradation problem.
Studies conducted in Uganda showed that land scarcity and land tenure system have direct
implications on the quantity and quality of feed or level of feed investment smallholder farmers
can make for improved dairy cattle production. (Kabirizi et al,, 2006). In customary land system, the
right over land is regulated by local customs and is acquired through inheritance. Security of land
is therefore minimal and there are sometimes conicts among clan members. Under customary land
tenure system, women are most discriminated against in the administration and dispute settlement of
customary land. Even after planting the forages, there are times when clan leaders sell or give away
the land. This is one of the reasons for not planting large acreages of forages because of fear of loosing
the land after investing a lot of resources. Information from farmer groups showed that 67% of the
women had access to land through their husbands or male relatives but when widowed or divorced,
7% of the women lost this access and had to return to their parents’ land. This was a major problem
especially where the woman had already invested in a dairy cattle enterprise and had planted fodder.
(b) Access to input and output markets
Improved access to input and output markets is a key precondition for the transformation of the
agricultural sector from subsistence to commercial production. Smallholder farmers must be able
to benet more from efcient markets and local-level value-addition, and be more exposed to
competition. The ECA countries are still grappling with marketing of both agricultural inputs and
outputs, with markets not adequately equipped to serve the needs of the poor.
On the input side, the average application rates of fertilizer for arable crops in ECA countries are
estimated to be 30 kg/ha/year in Kenya, 14 kg/ha/year in Ethiopia, 5kg/ha/year in Tanzania and1
kg/ha/year in Uganda – far less than the world average of 100kg/ha/year (Smaling et al , 2006) .
There is also the problem of high cost and waste of key inputs such as seed and fertilizers. For this
reason, it was reported in UNDP (2007) that farmers have substantially reduced use of quality inputs
such as seed, fertilizer, and pesticides and that the respective use of improved seeds, fertilizers, agro-
chemicals and manure were only 6.3 per cent, 1.0 per cent, 3.4 per cent and 6.8 per cent of the parcel
of agricultural land in Uganda.
Limited access to market-related information e.g. on prices, value chains, competitors, consumer
preferences leads to either high or low production of some products and the related marketing
constraints. Among the consequences of lack of market information is the presence of a multiplicity
of intermediaries which increases the charges and shades the transparency of the operation. The
5
presence of so many actors/many informal channels means less prots per actor but expensive prices
and longtime taken by product to reach consumers. The risks of product adulterations also increase
as actors increase along the value chain.
(c) Inadequate feeds
Limited feed resource is a major constraint that hinders the growth of dairy farming in ECA (Njarui
et al. 2012). The limited feed resource is attributed to limited amount of rainfall, punctuated with
frequent drought, leading to poor growth of pastures. The situation is exacerbated by shrinking land
holdings due to increased population and cultivation of food crops. This has negatively affected the
number and type of animals that farmers keep and, manure quantity and quality. Nutrient deciencies
in the soil in the EAC region has greatly affected feed supply for the dairy subsector (Mubiru et
al., 2003). This is caused mainly by excessive removal of vegetation through grazing and harvesting
feeds. Often, these nutrients are not replenished or unevenly deposited back in the soil.
(d) Climate change and related food security challenges
Climate change, resulting mostly from global warming, has been among the major causes of reduced
agricultural production and productivity in many parts of Africa, including ECA region. Most crop
and livestock farming is rainfed, and therefore, susceptible to weather uctuations. Over the last three
decades the frequency of droughts and oods in ECA region has increased, resulting in crop failures
and loss of livestock (Ericksen, 2010). Ethiopia has been hit hardest by persistent drought, making
food security the key issue for poverty reduction. Furthermore, with increasing land degradation,
land resilience has been reduced and the effects of drought and oods exacerbated.
(e) Infrastructure
Poor infrastructure continues to impede agricultural activities in ECA region. The key challenges
are inadequate and poor conditions of the market facilities and transportation systems, including
road and rail. Previous infrastructural investments were often ineffective as a result of poor design
and poor maintenance, sometimes due to stop-go practices of donors funding these investments.
The road system, which is the most important for market development in terms of distribution of
inputs and output to and from farms, is the most serious infrastructural bottleneck facing agricultural
development. As a result of poor road network, smallholder farmers depend on inefcient forms
of transportation including use of animals. In addition, irrigation facilities are poor as less than 4
percent of all agricultural output is produced under irrigation compared with about 33 percent in
Asia (AfDB/IFAD, 2009).
(f) Agricultural extension and innovation
Research and extension services in most of the ECA countries have been disintegrated and ineffective
for any technological transformation to take effect. Despite various attempts to strengthen them, the
linkages between research, extension and training are weak, and collaboration between public and
private partners limited.
6
(g) Processing and marketing
Although crop and livestock production in the ECA region is largely subsistence, the trend is
gravitating towards commercialization. Njarui et al. (2010) observed that about 15% of dairy cattle
farmers in Kenya produce between 11-20 litres of milk/day resulting into surplus milk available for
direct sale and for processing into other milk derivatives. Further the study revealed that 43% of the
milk producers lacked market for their milk during the milk glut period.
(h) Increasing labour productivity
The ECA region will probably be transformed from a mostly rural to urban population due to rural
– urban migration caused mainly by difference between urban and rural wage rates, probabilities
of obtaining urban jobs, and the demand for labour force. Majority of the urban migrants are youth
(especially male), as such continuous migration from rural to urban area will in a long run affect the
labour availability in the rural area as the rural farmers age.
(i) Poor livestock breeds
Many improved breeds of dairy cattle exhibit an inherently low genetic potential for productivity
traits. Even the exotic cattle reared under tropical conditions suffer a lot from heat stress and vector-
borne diseases due to their poor adaptability. According to Petrus et al (2011), use of improved breeds
in developing countries presents farmers with a major challenge as the breeds require intensive
management for them to realize full production potential. Attempts to increase cattle productivity
through crossbreeding between local and exotic breeds have not always been successful because
of inefcient breeding programmes characterized by ambiguous breeding goals, poor records,
inadequate feeding; limited technical personnel among others.
(j) Animal disease and parasites
In most ECA countries, animal health is probably the area which has benetted the most from
government efforts. Since colonial days, the delivery of health services has long been a major concern.
Currently, livestock health services are supported by several sub-regional vaccine laboratories, and a
few regional reference diagnostic laboratories. Training of veterinarians is quite widespread in Africa.
But these research and training efforts are adversely affected by improvisation, lack of concerted action
and coordination and a poor denition of real needs. Consequently, the smallholder dairy farmers
are still plagued by major contagious diseases (rinderpest, contagious bovine pleuropneumonia
(McDermott, 1999).
(k) Processing and value addition constraints
Because of the high perishability of animal products, timely processing and value addition is an
important step in the dairy value chain to ensure sustainable supply of products, preventing loss and
associated healthy risks. There are, however, several constraints to realizing this important value chain
component: (i) lack of processing and preservation facilities for the extended storage life of meat and
milk. Technology is either not available, expensive or no power to operate machinery and, (ii) poor
quality of nished products (e.g. packaging, standards): This is caused due to poor understanding
of each value chain plays’ requirements, thus substandard products delivered along the value chain.
7
(l) Gender issues affecting dairy production
Despite their considerable involvement and contribution, women’s role in smallholder dairy cattle
production has often been underestimated or, worse, ignored. Gender-blindness is partly the result
of a paternalistic bias, but also women’s attitude which may have been conditioned by their culture
and society to undervalue the worth of the work they do. Yet in most systems, women provide labour
for the various tasks related to dairy production but may or may not control the process of decision-
making, particularly over the disposal of animals and animal products and also may not own the
means of production e.g.livestock, land and water. Kabirizi et al. (2006), noted that husbands and
wives both usually have control over the use of resources, although there may be “unequal, often
conicting claims on resources for the satisfaction of basic needs”. Men’s de jure ownership rights
over animals are guaranteed by a near universal set of inheritance rules that are gender biased and
rooted in religion and patriarchal kinship systems.
(m) Lack of business skills
Lack of business management skills (e.g. production planning) and, in particular, inadequate access
to the knowledge and technologies needed to meet rising sanitary standards, making it extremely
difcult for smallholders to gain credible certication of compliance with marketing requirements
(Lundy et al. 2008).
(n) Financing Agriculture and Access to Credit
For investment, smallholder dairy farmers in ECA countries depend on savings from their low
incomes, which limits opportunities for expansion. Because of the lack of collateral and/or credit
history, most farmers are bypassed not only by commercial and national development banks, but
also by formal micro-credit institutions. In addition to own sources, farmers thus rely on incomes of
friends and relatives, remittances, and informal money lenders (Mahieux et al. 2011).
References
Adeleke Salami, Abdul B. Kamara and Zuzana Brixiova. 2011. Smallholder Agriculture in East
Africa: Trends, Constraints and Opportunities. African Development Bank Group. Working paper.
No 105 - April 2010.
AfDB/IFAD (2009), AFDB/IFAD Joint Evaluation of their agricultural operations and policies
in Africa, Draft Report, Rome and Tunis, African Development Bank
Anona 2002. Study on the horticulture development in Tanzania. The United Republic of
Tanzania. Ministry of Agriculture and Food Security. http://www.kilimo.go.tz/publications/
swahili Report.pdf
Ericksen, Polly 2010. Livestock Drought Management Tool. Final report for project OSRO/
RAF/915/RFF PR 44865 Submitted by ILRI (International Livestock Research Institute, Ethiopia) to
the FAO Sub-Regional Emergency and Rehabilitation Ofcer for East and Central Africa 10 December
2010
FAO (Food and Agriculture Organization of the United Nations) 2010 Status of and prospects
for smallholder milk production: A global perspective, edited by Hemme T and Otte T. http://www.
fao.org/docrep/012/i1522e/i1522e0
FAO. 2011. Dairy development in Kenya, by H.G. Muriuki. Rome. http://www.fao.org/
docrep/013/al745e/al745e00.pdf
8
Kabirizi J, Mpairwe D, and Mutetika D, 2006. Effect of intercropping forage legumes with
elephant grass on fodder production in intensive smallholder dairy farms in Uganda. Uganda Journal
of Agricultural Science 2006, 12 (2): 16 -25
Lundy M., Verónica Gottret M., Ostertag C., Best, R. and Ferris S. 2008. Participatory market
chain analysis for smallholder producers.
http://www.crsprogramquality.org/storage/pubs/agenv/marketchain.pdf.
ISBN 0-945356-41-2
Mahieux T., Zafar O., and Kherallah, M. 2011. Financing Smallholder Farmers and Rural
Entrepreneurs in the Near East and North Africa. Paper presented at the IFAD Conference on New
Directions for Smallholder Agriculture 24-25 January, 2011. International Fund for Agricultural
Development Via Paolo Di Dono, 44, Rome 00142, Italy. http://www.ifad.org/events/agriculture/
doc/papers/kherallah.pdf
McDermott J.J., Randolph T.F and Staal S.J. 1999.The economics of optimal health and
productivity in smallholder livestock systems in developing countries. Rev. sci. tech. Off. int. Epiz.,
1999.18 (2), 399-424
Mubiru S, Romney D, Halberg N and Tenywa J S 2003. Nutrient balances and options for
their improvement under different levels of intensication of dairy production in Uganda. In:
Proceedings of the Livestock Systems Research Programme (LSRP) Annual Scientic Workshop 2003.
In collaboration with DANIDA’s Agriculture; sector research Programme (ASPS) and the National
Agricultural Research Organisation (NARO) pp. 206-216
Muia, J. M. K., Kariuki, J. N., Mbugua, P. N., Gachuiri, C. K., Lukibisi, L. B., Ayako, W. O., and
Ngunjiri, W. V., 2011, Smallholder dairy production in high altitude Nyandarua milk-shed in Kenya:
Status, challenges and opportunities., Livestock Research for Rural Development, 23(108).
Muriuki H. G., Mwangi D. M. and Thorpe W. 2001. How Smallholder Dairy Systems in Kenya
Contribute to Food Security and Poverty Alleviation: results of recent collaborative studies. Paper for
Oral Presentation at the 28th Tanzania Society of Animal Production Conference, Morogoro, 7th- 9th
August, 2001.
Http://www.smallholderdairy.org/publications/Conference/Muriuki-2001-Smallholder
TSAP.pdf
Nicholson, C.F., Thornton, P.K., Mohammed, L., Muinga, R. W., Mwamachi, D.M., Elbasha,
E.H., Staal, S.J. and Thorpe, W. 1999. Smallholder Dairy Technology in Coastal Kenya, An adoption
and Impact study. ILRI (International Livestock Research Institute).
Njarui, D. M. G., Gatheru, M., Wambua, J. M., Nguluu, S. N., Mwangi, D. M., and Keya, G.
A., 2011, Feeding management for dairy cattle in smallholder farming systems of semi-arid tropical
Kenya, Livestock Research for Rural Development, 23(111).
Njarui, D. M. G., Kabirizi, J. M., Itabari, J. K., Gatheru, M., Nakiganda, A., and Mugerwa, S.,
2012, Production characteristics and gender roles in dairy farming in peri-urban areas of Eastern and
Central Africa, Livestock Research for Rural Development, 24(7).
Omore, A.O., McDermott, J.J., Gitau, G.K., 1996b. Factors inuencing production on smallholder
dairy farms in central Kenya. In: Proceedings of the 5th Scientic Conference of the Kenya Agricultural
Research Institute (KARI). 14th - 16th October, 1996. KARI Headquarters, Nairobi, Kenya. pp 370-379
Petrus N P, Mpofu I, Schneider M B and Nepembe M 2011 The constraints and potentials of
pig production among communal farmers in Etayi Constituency of Namibia. Livestock Research for
Rural Development. Volume 23, Article #159. Retrieved April1, 2012, from http://www.lrrd.org/
lrrd23/7/petr23159.htm
UNDP (2007), Uganda Human Development Report 2007, Rediscovering Agriculture for
Human Development, Kampala, Uganda, United Nations Development Programme.
Vorster, Hester H., Kruger Annamarie., Margetts, Barrie M., Venter Christina S, H Kruger
Salome, Salome Veldman Salome and MacIntyre Una E. 2004. The nutritional status of asymptomatic
HIV-infected Africans: directions for dietary intervention, Public Health Nutrition: 7(8), 1055–1064
9
CHAPTER 2: Eastern Africa Agricultural Productivity Project (EAAPP)
1Jolly Kabirizi, 2Francis N.Muyekho and 3George Lukwago
1National Livestock Resources Research Institute (NaLIRRI), Tororo, Uganda
2Department of Biological Sciences, Masinde Muliro University of Science and Technology,
P.O. Box 190-50100, Kakamega, Kenya
3National Coordinator, Eastern Africa Agricultural Productivity Programme (EAAPP)-Project Coordinating
Unit (PCU), National Agricultural Research Organization, P.O. Box 295, Entebbe,Uganda
2.1 Background
Agricultural technology is fundamental to productivity growth and requires effective and efcient
innovation systems in order to generate high returns in investments. According to the 2008 World
Development Report, the policy environment for agriculture in much of Africa has much improved
relative to earlier years. This justies increased investment in agricultural technology development
in order to negate losses in foregone returns. Among the foregone returns are gains from economies
of scale that would arise from the assembly of the critical mass of researchers and facilities needed
to address the complex problems of African agricultural innovation systems and commodity value
chains.
The East African Agricultural Productivity Programme (EAAPP) was conceived in 2009 by the
governments of Ethiopia, Kenya, Tanzania and Uganda in partnership with ASARECA and the World
Bank. EAAPP addresses the constraints related to low productivity in cassava, wheat, rice and dairy
in the project countries of Uganda (cassava), Kenya (dairy), Tanzania (rice), and Ethiopia (wheat). The
specic objectives of EAAPP are to: (a) enhance regional specialization in agricultural research; (b)
increase regional collaboration in agricultural training and dissemination; and, (c) facilitate increased
sharing of agricultural information, knowledge and technology across national boundaries.
These objectives are being pursued through: (i) strengthening the existing Uganda national agricultural
research program in cassava so that it becomes a RCoE; (ii) supporting regional research, training
and dissemination of relevant technologies; and, (iii) supporting increased availability of improved
genetic materials (planting materials, seeds and livestock germplasm) in the selected commodities in
participating countries.
2.2 The Regional Dairy Centre of Excellence (RDCoE) overview
Kenya is amongst the biggest per capita milk producing and consuming countries in the region. There
are more than 1 million smallholder dairy farmers, according to surveys done by the Smallholder
Dairy Research and Development Project (SDP), contributing more than 70 percent of gross marketed
production from farms (FAO, 2011)..
The dairy sector in Kenya is dominated, at the producer level, by smallholders farmer and at the
marketing level by informal sector traders and hawkers. At present, a large proportion of marketed
milk (86%) is sold informally (FAO, 2011). The livelihoods of millions of people in the country depend
on these informal milk markets, which are often the sole source of income for small-scale dairy
producers and jobs for thousands of unskilled youth. It is estimated that, from smallholder farmers
(producers) to milk hawkers, nearly 1 million households and businesses are involved. Informal milk
10
sector accounts for more than 70% of 40,000 jobs in dairy marketing alone and further directly supports
over 350,000 others in formal employment. Considering that there are 1 million smallholders’ farmers,
for whom dairy is a family business, it is likely that more than 2 million people derive living from the
dairy sector through their involvement in production, marketing and service provision.
Kenya was selected to host the dairy Regional Dairy Centre of Excellence (RDCoE) because it is a
national priority with;
(1) Proven potential for sub regional spillovers
(2) Proven potential for leadership in dairy
(3) It is aligned with regional priorities as dened by ASARECA
(4) Proven potential to address both immediate and long-term food security needs and
(5) Kenya demonstrated interest to support the development of the RDCoE
The goal of the RDCoE is to improve the livelihoods of smallholder dairy farmers within the Eastern
Africa region. The purpose of the RDCoE is to develop, test and disseminate technologies, knowledge
and information that will assist in building a globally competitive dairy industry in the region.
The RDCoE objectives are:
(a)To provide state-of-the-art analysis of feeds and dairy products in the region
(b)To develop, test and disseminate improved dairy technologies in the region
(c)To build scientic capacity to carry out quality dairy research in the region
(d)To build the capacity of other stakeholders in the region to provide support services to the
dairy sector in the region. Together with other stakeholders generate information that will
assist in the development of enabling dairy policies in the region.
(e)To establish an elaborate communication strategy both nationally and regionally to ensure
real-time information exchange
The regional Priority areas of focus
(a) Animal genetic improvement (Covering genetic resource characterization, breeding, germ-
plasm multiplication, upgrading of local genetic resources, gene-environment interaction/
matching, related policies, etc)
(b) Feed resource utilization (covering fodder/pasture, crop residues, fortied feeds, ration
formulation, pasture/forage breeding, seed multiplication, feed conservation, feed safety,
farming systems) Animal health (Covering all aspects of animal health, policy, regulatory
services)
(c) Processing and value addition (covering all aspects of dairy products value addition to
increase competitiveness in the regional and world markets)
(d) Socio-economics (covering policy analyses, farmer oriented socio-economic studies, trade,
management of information systems, monitoring and evaluation, impact assessment studies,
feasibility studies, input/output markets, gender studies)
Expected outcomes
(a) A state of the art Dairy Centre of Excellence with the necessary support systems that will
underpin a competitive dairy sector in the region is established.
(b) Competitiveness, productivity and sustainability of the regional dairy industry is improved
through development, validation, dissemination and up-scaling of appropriate technologies
to stakeholders.
11
(c) Linkages between the regional scientic and farming community with the various Eastern
Africa governments’
policy-making organs and the general integration of regional economy catalysed.
(d) Capacity of all dairy industry stakeholders (researchers, extension, farmers, private
entrepreneurs, policy-makers, etc) improved through formal training and learning exchange
visits.
(e) Information ow in the region reinvigorated through establishment of region-wide
information exchange network. Dairy data, analytical reports, publications, extension
messages and experiential knowledge can have wide circulation and therefore readership
also improved.
(f) Overall, an improved dairy industry, will impact positively on both national and regional
economy. In particular, it will directly contribute towards poverty reduction and creation of
employment
2.3. Thematic areas of the RDCoE
1. Feeds and feeding systems
2. Crop residues and agro-industrial by-products research
3. Dairy breed development and germplasm multiplication
4. Dairy Feed Safety Research
5. Dairy Health Research and Development
6. Farming Systems Research
2.4. RDCoE approved projects
1. Enhancing adoption of Napier grass accessions tolerant to Napier stunt and smut diseases
for improved feed resources availability in smallholder dairy systems.
2. Enhancing Adoption of Appropriate policies and safety standards of feeds and milk for
improved livelihoods in the ECA countries.
3. Improving value addition and marketing of milk for smallholders In East African Region
4. Improving indigenous cattle for dairy productivity through targeted selection and cross
breeding in ECA countries.
5. Improve East Cost Fever control by contributing towards efcient vaccine development.
References
FAO. 2011. Dairy development in Kenya, by H.G. Muriuki. Rome
12
CHAPTER 3: Napier grass: Challenges, Establishment, Management and
Utilization
1 Jolly Kabirizi, 2Francis N. Muyekho and 3Beatrice Pallangyo
1 National Livestock Resources Research Institute (NaLIRRI), Tororo, Uganda
2 Masinde Muliro University of Science and Technology, Kakamega, Kenya, 3Plant Health Services,
3 Department of Biological Sciences, Ministry of Agriculture Food Security and Cooperatives,
P.O.Box 9071, Dar es Salaam, Tanzania
3.1 Introduction
Napier grass, commonly known as elephant grass (Pennisetum purpureum) was named after colonel
Napier of Bulawayo in Zimbabwe who early in the 19th century urged Rhodesia’s (now Zimbabwe)
Department of Agriculture to explore the possibility of using it for commercial livestock production
(Boonman, 1993). In Uganda, Napier grass used to be promoted in Uganda for soil conservation and
for mulching coffee. According to Acland (1971) it turned out that very few smallholders mulched
their coffee and found it more protable to sell Napier grass to coffee estates or feed the grass to their
livestock. Napier grass has advantages over other grasses because of its high yielding capacity and
ease of propagation, and management within a wide ecological range (0 < 2,000m ASL) (Orodho
2006). It has so far become the most important fodder for cut-and-carry especially in Kenya, where it
is mainly propagated through cuttings (Humphreys 1994).
3.2. The role of Napier grass in smallholder dairy farming systems
(a) Napier grass as major feed resource in intensive and semi-intensive dairy systems
Napier grass is a major forage for dairy cattle in intensive and semi intensive systems, grown by
over 70 percent of smallholder dairy farmers in Kenya (Abate 1992; Staal et al., 1998; Orodho 2006;
Mulaa et al., 2013); Uganda (Kabirizi et al., 2006) and Tanzania (Pallangayo et al., 2008). It constitutes
between 40 to 80% of the forage for the smallholder dairy farms (Staal et al., 1997). Because of high
population pressure farms are small, with an average holding size of 0.9-2.0 ha (Gitau et al., 1994); and
are still decreasing. Animals are, therefore, conned in stalls and fed mainly on Napier grass under
zero grazing.
(b) Soil fertility improvement
Napier grass is widely used for soil and water conservation in hilly slope areas. In Uganda and Kenya,
for example, vigorous campaigns are being undertaken to sensitise and encourage farmers to take on
Napier grass cultivation for fodder and as a measure to control stem borers and soil erosion.
(c) Control of stem borers in maize and sorghum crops
Napier grass has been identied as an important tool in the integrated management of stem borers of
maize and sorghum due to its importance as a trap crop for these pests (Khan, et al., 1997; Midega et
al., 2010).
13
The push–pull effect is established by exploiting semio-chemicals to repel insect pests from the crop
(‘push’) and to attract them into trap crops (‘pull’) e.g. Napier grass. The systems exemplied here
have been developed for subsistence farming in Africa and delivery of the semiochemicals is entirely
by companion cropping, i.e. intercropping for the push and trap cropping for the pull. The main
target is a series of lepidopterous pests attacking maize and other cereals. Although the area given to
the cereal crop itself is reduced under the push–pull system, higher yields are produced per unit area
(Ahmed Khan, et al., 1997).
An important spin-off is that the companion crops are valuable forage for farm animals. Leguminous
intercrops especially Desmodium species also provide advantages with regard to plant nutrition and
some of the trap crops help with water retention and in reducing land erosion. A major benet of
intercropping desmodium in the push-pull technology of controlling stemborers is that it provides
dramatic control of the African witchweed (striga) (Khan et al. 1997). Animal husbandry forms an
essential part of intensive subsistence agriculture in Africa and developments using analogous push–
pull control strategies for insect pests of cattle are exemplied.
(d) Source of income
Many farmers without animals produce Napier grass fodder for sale to dairy farmers in form of fresh
or conserved (silage) fodder.
(e) Other uses
The grass serves as mulch in banana farming regions of Uganda, Kenya and Tanzania. Other uses of
Napier grass are: wind and re break. Matured grass turned into reeds can be used for cheap farm
construction. It serves as a wind break in maize elds and stabilizes soil by holding particles together
thereby preventing soil erosion (Cook et al., 2007; Khan et al., 2014).
3.3 Establishment, management and utilization of Napier grass
Napier grass is a fast growing, deeply rooted, perennial grass growing up to 4 metres tall that can
spread by underground stems to form thick ground cover. Napier grass is easy to establish and
persistent; drought tolerant; suitable for cutting and very good for silage making.
A maize eld infested by stiga weeds Push and Pull technology
14
(a) Climate and soils
Napier grass can be grown at altitudes ranging from sea level to 2,000m above sea level. When grown
at altitudes above 2000 m, growth and regeneration after cutting is slow and it may die due to frost.
It does best in high rainfall areas, over 1500 mm per year. Napier grass can grow in almost any soils;
but does best in deep, fertile, well-draining soils. It is however very drought tolerant and can be used
as dry season reserve in dry areas.
(b) Establishment
Napier grass is established in well-prepared land (ploughed and harrowed) from root splits, canes
with 3 nodes or from whole canes. The material is planted 15-20 cm deep with splits planted upright,
three node canes planted at an angle of 30-45o while whole canes are buried in the furrow 60-90 cm
apart.
Vegetative (stem cutting) propagation
Whether root splits or canes are used, they should be sufciently mature to tiller well and produce
tall and high yielding forage plants. Cane planting materials should be obtained from plants about to
ower where the stems are still green.
15
(c) Spacing
The spacing may vary depending on the annual rainfall of the area; usually the higher the rainfall the
closer the spacing. Root splits and canes are usually spaced at:
• 50 - 60 cm x 50- 60 cm in areas receiving rainfall of above 1800mm per year.
• 50-60cm x 90-100 cm is used in areas receiving 900 – 1800 mm of rainfall per year,
• 90-100 cm x 90-100cm in low rainfall areas receiving 700 - 900 mm of rainfall.
(d) Methods of Establishing Napier grass
Two methods may be used, namely: (i) conventional and (ii) Tumbukiza (micro-catchments)
(i) Conventional method
• Plough and harrow the eld well before planting
• Dig planting holes 15-12 cm deep, or spacing
• In each hole apply: 2 handfuls of farmyard manure (FYM) or a soda bottle full of DAP or
both a handful of FYM and 1/2 soda bottle top of DAP
• Place 3 nodes piece of cane ensuring two nodes are covered or place a root split of Napier
planting material in the hole
• Cover the planted material with soil
• Intercrop with forage legumes
ii) Tumbukiza technology (micro-catchments) method
“Tumbukiza” is a method where the planting is done in round or rectangular pits of 60 cm wide
diameter and 60 cm deep, lled with a mixture of topsoil and manure in the ratio of 1:2. The rows of
pits should be 60 cm apart.
• Plough and harrow the eld well
• Dig pits with spacing of 60x 60 cm or 60 cm x 90 or 90 x 90 cm depending on moisture
regime
• Mix 1 tin (20 liter) of top soil with 1 0r 2 tins of FYM
• Put the soil-farmyard manure into the pit leaving 1 cm space at the brim
• Plant 5-10 cuttings/canes/root splits per hole
“Tumbukiza” pits for improved fodder productivity
This method gives higher herbage yields even during the dry season than the conventional method.
Napier grass can also be established by the
16
(e) Varieties
Kenya
• Conventional varieties promoted are: Bana grass, French Cameroon, Clone 13 and Pakistan
Napier hybrid.
• Napier clones and alternative fodder grasses tolerant to stunt disease currently being
promoted in western Kenya and other areas where stunt disease is a serious problem are:
South Africa, Ouma 2 and 3
• Alternative fodder grasses are: Brachiaria hybrid cv Mulato II, Sorghum var. 6518, Giant
Panicum, Guatemala grass and Giant setaria.
• Napier clones tolerant to stunt disease being promoted in Central and Eastern Kenya where
smut disease is a serious problem are: Kakamega 1 and Kakamega 2
• Newly identied Napier clones tolerant to smut disease that are being multiplied by Kenya
Agricultural and Livestock research Institute are: ILRI accession 16806, ILRI accession 16782,
ILRI accession 16789, ILRI accession 16805, ILRI accession 16811, ILRI accession 16783, ILRI
accession 16800, ILRI accession 16835
• In addition, some of the tolerant Napier clones identied in Kenya as listed above are being
screened for tolerance to Napier stunt and smut diseases in Uganda, Tanzania, Rwanda and
Burundi and tolerant clones have been multiplied and distributed to farmers.
Uganda
• A number of Napier grass leafy varieties e.g. Kawanda variety 4 (KW4) and Pennistum 99 (a
hybrid between KW4 and Bulrush millet) are available.
• In addition, 22 Napier grass accessions obtained from the Alupe Research Institute in Kenya
were screened for tolerance to Napier stunt disease, dry matter yield (DMY) and nutritive
quality. Kakamega 1, Kakamega 2, 112 and 16072 produced the highest yields DMY of 40 to
42.0 kg/ha. The accessions were recommended for multiplication in NSD “hot spot” areas of
Uganda as a way to improve feed availability and NSD in an environmentally friendly and
cheaper means. Napier grass accessions Kakamega 1, Kakmega 3 and 16805 were promoted
in Rwanda and Burundi.
(f) Intercropping with forage legumes
Generally planting Napier grass with herbaceous legumes increases the dry matter yield and crude
protein of the forage (Mwangi, 2002; Kabirizi et al., 2006); those that are compatible and give high
yields include:
• Giant vetch (Vicia dasycarpa) at higher elevations;
• Silverleaf desmodium (Desmodium uncinatum), greenleaf desmodium(D. Intortum), stylo
(Stylosanthes guianensis) and glycine (Neonotonia wightii) in high and medium altitudes;
• Centro (Centrosema pubescens), siratro (Macroptilium atropurpureum), buttery pea (Clitoria
ternatea), lablab (Dolichos lablab) and stylo in the semi-arid coastal regions.
17
This legume should be planted at a spacing of 1 m x 1 m and a seed rate of 1 -4 kg/ha near the
grass rows or in between the rows. The legume helps to control the weeds and contribute to herbage
production without competing with the grass. It also improves the Nitrogen content of the soil and
the grass.
(g) Fertilizer application
Because of its rapid growth and high yields Napier grass requires regular application of nitrogen (N)
and phosphorus (P) in the form of fertilizers or farm yard manure (FYM) (Orodho, 2006). High yields
of Napier are maintained with the following rates of application:
• 20 kg/ha/year of P in the form of either single or triple superphosphates (SSP or TSP)
at a rate of 100 kg/ha applied twice a year as a ring application around the stools at the
beginning of the long and short rainy season on weeded plots.
• 75 kg/ha/ of N usually in the form of Calcium Ammonium Nitrate (CAN) at a rate of 300
kg/ha to be applied in splits after every grass harvest (except the harvest taken during the
dry season, because of low soil moisture) or in three equal doses in a year, during the long
rains and short rains.
• Dairy cattle slurry: this is a mixture of cow dung, urine, and feed left over, available from
the zero-grazing stable. The rate of application is 5.5 tons of DM/ha/year or 55 tons of
liquid slurry. This should be buried between Napier grass rows to avoid loss of nitrogen by
volatilization. The slurry is applied after the onset of long and short rainy seasons.
(h) Weeding and inter-Row Cultivation
Napier should be weeded regularly in order to maintain the grass in a vigorous and productive
condition.
• It should be weeded as early as possible and at least twice after planting and kept weed free
throughout growth especially after cutting.
• Aggressive weeds such as couch grass (Digitaria sp.) are best controlled during the dry
season
• Regular weeding helps to ensure that fertilizer applied after harvest will only be utilized by
the forage crop.
• Regrowth can be harvested when it reaches 2-3 feet (60-90 cm) high which means a period of
6-8 weeks between cuts
Napier grass intercropped with forage legumes
18
(j) Potential Yields
Yields depend on agro-ecological zone and management but on average Napier grass can give 12 to
25 tons/ha of dry matter yield. Under optimal management practices Napier grass can give yields 40
t/ha/year in high rainfall (1200 mm to 2400 mm of rainfall).
(k) Feeding management
• Chop the harvested mixture of Napier grass and Desmodium to reduce wastage while
feeding it to the animals.
• Do not graze animals directly on Napier grass.
• Feed 70 kg or 7 head loads of fresh Napier grass to a dairy cow per day.
• Two acres of Napier grass planted by the conventional method can give enough feed for 1
• dairy cow for a full year.
• One acre of Napier grass planted by the Tumbukiza method can give enough feed for 2 to 3
dairy cows for one year.
3.4 Challenges to production of Napier grass
(a) Poor agronomic conditions
• The agronomic conditions under which the Napier grass is grown affect its yield per unit
area and quality.
• Rainfall, and drought are among the key constraints to Napier grass production,
unfortunately are beyond the producer’s or farmer’s control.
• Phosphorus (P) and Nitrogen (N) have a large inuence on forage yield and quality but the
fertilizers are expensive for farmers to afford and apply in adequate amounts.
• Legumes can substitute N fertilizers when intercropped with grasses but the seed is either
unavailable or too expensive for farmers
(i) Harvesting
Napier grass is ready for harvesting 3-4 months after planting and harvesting can continue at an
interval of 6-8 weeks for 3 5 years depending on its management, soil fertility and soil moisture. Leave
a stem length of about10 cm from the ground at harvesting.
A farmer cutting Napier grass fodder
19
(b) Pests and Diseases
Napier stunt and head smut diseases, caused by phytoplasma and a fungus Ustilago kameruniensis,
respectively, have in the recent years caused forage yield reduction of up to 90% (Mulaa et al., 2013),
and are currently the biggest threats to forage production and hence dairy sector in the region. In
Western Kenya, stunt disease has resulted in an estimated milk yield reduction of 20-40% due to
under feeding and destocking due to inadequate feeds (Mulaa et al., 2013).
Both diseases have been recorded in Kenya, Tanzania, Uganda, Ethiopia and Rwanda, and Burundi with cross
boarder movement of livestock and people carrying Napier grass with them.
3.5 Napier head smut
Napier grass head smut is a fungal disease caused by Ustilago kamerunensisis which is a serious
problem in central and eastern Kenya but has also been reported in Tanzania, Uganda, Rwanda and
Congo (Mulaa et al., 2010). The disease is spread rapidly by wind and infected plant material.
Napier grass head smut disease
Early owering with smutted heads, stunted plant with thin leaves and lots stems, these lead
eventually to tillers dying. Symptoms start on some tillers and eventually affect the whole plant.
Infected stems are smaller, thinner and shorter, with few, small and sometimes distorted leaves. Re-
growth of infected plants is slow after cutting. They ower early and the ower head becomes a mass
of black spores. The total dry matter is reduced, after 2-3 cuttings, the entire stool dries.
3.6 Napier stunt disease
Napier stunt disease leads to reduction in area under Napier by about 40 per cent (Nanyeenya et
al., 2014). In Uganda Napier Stunt Disease (NSD) has been reported in 97 per cent of farmers’ elds
causing stunting, curling/twisting of leaf tips leading to up 50 per cent reduction in biomass yield
(Kabirizi et al., 2014).
20
Symptoms of Napier stunt disease
Many smallholders in Kenya have lost up to 100 percent of their Napier crop and are forced to de-stock
or sell off their entire herd because of lack of sufcient feeds farmers in the study area retained their
herd sizes (4.6 heads of cattle) (Orodho, 2006) and Mulaa, 2010). Farmers have however, struggled
to make up for the lost biomass due to NSD by stepping up feed supplementation resulting into an
increase in cost of supplements per day by 200 per cent. Time taken to fetch feeds is also greater by
43 per cent.
The disease is much more severe and prevalent in poorly managed elds and farmers have noted that
in well-weeded and heavily manured elds, disease severity is reduced (Orodho 2006 and Kabirizi
et al. 2014). From recent surveys, incidences of between 30% and 90% infections by Napier stunt
disease has been recorded in many smallholder elds (Mulaa et al., 2010). In some parts of Eastern
and Central Africa, women and children use plenty of time looking for pastures or stall feeding. This
translates to time and economic loss to these growing economies.
3.7 Efforts to improve Napier grass productivity in ECA
Under EAAPP funded regional project “Enhancing adoption of Napier grass and alternative fodder
grasses resistant/tolerant to stunt and smut diseases for increased feed availability in smallholder
systems in Eastern and Central Africa”, the following research activities were implemented in the
Kenya, Uganda, Tanzania, Rwanda and Burundi during the period of 2011-2015:
(a) Status of Napier grass stunt and head smut disease, current germplasm and implication on
smallholder dairy production in Kenya, Uganda, Tanzania, Ethiopia and Rwanda, Burundi.
(b) Screening for Napier grass (Pennisetum purpureum) accessions for resistance/tolerance to
stunt disease pathogen
(c) Screening for Napier grass (Pennisetum purpureum) accessions resistance/tolerance to head
smut pathogen Ustilago kamerunensis
(d) Evaluation of alternative forage species for yield and resistance/tolerance to stunt disease
(e) Epidemiology of Napier stunt disease and progress in the search for tolerant cultivars
(f) Epidemiology of Napier head smut disease and progress in the search for tolerant
(g) Characterization of Napier germplasm in the region
(h) Agronomic management of the identied tolerant Napier grass clones to stunt and smut
diseases in Kenya
(i) Cultural practices (Integrated pest management – IPM) of Napier Stunt and smut Diseases
(j) Forage/crop/livestock integration
(k) Strategic utilization of crop residues and alternative forages/feed resources
Detailed activities are described in the Chapters that follow.
21
References
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systems in Vertisols of the Ethiopian highlands. Tropical Agriculture, 59, 68-72.
Acland, J.D. 1971. East African Crops. Longman
Boonman, J.G. 1993. East African Grasses and Fodders, Their Ecology and Husbandry. Kluwer
Academic Publishers. pp. 196.
Cook, S.M, Khan, Z.R, Pickett, J.A. 2007. The use of ‘push–pull’ strategies in integrated pest
management. Annual Review of Entomology 52, 375–400.
Gitau. G.K., O’Callaghan, C.J., McDermott, J., Omore, A., Odima, P.A., Mulei, C.M. and
Kilungo, J..K. 1994. Description of smallholder dairy farms in Kiambu district, Kenya. Preventative
Veterinary Medicine21:155–166.
Humphreys, L,.R. 1991. Tropical Pasture Utilization. Cambridge University Press. Cambridge.
UK.
Kabirizi, J., Nielsen, S.L., Nicolasen, M., Byenkya, S and Alacai, T (2007): Napeir stunt Disease
in Uganda: Farmers’ perceptions and impact on fodder production ACSC Proceeding Vol 8 pp 895-89
Kabirizi, J.; Mugerwa, S.; Ziwa, E.; Lukwago, G.; Namazzi, C. 2012. Napier stunt disease
incidence, severity and management in Uganda. Proceeding of the Annual Scientic Symposium of
the Animal Production Society of Kenya, April 11th to 13th 2012.Green Hills Hotel, Nyeri. Kenya. pp
30-35.
Khan Z., Pickett P., Midega, C. Jimmy Pittchar J. 2014. Climate-smart push-pull: A
conservation agriculture technology for food security and environmental sustainability in Africa.
First Africa Congress on Conservation Agriculture Lusaka, Zambia, 18th to 21st March 2014. www.
africacacongress.org/sites/.../1acca2014_zeyaur_k_ppt_pittchar.ppt
Midega CAO, Khan ZR, Amudavi DM, Pittchar J, Pickett JA. 2010. Integrated management of
Striga hermonthica and cereal stemborers in nger millet (Eleusine coracana (L.) Gaertn.), through
intercropping with Desmodium intortum. International Journal of Pest Management 56, 145–151.
Mulaa M, Awalla B, Hanson J, Proud J, Cherunya A, Wanyama J, Lusweti C and Muyekho
F. 2010. Screening Napier grass (Pennisetum purpureum schumach) Accessions for tolerance to
Stunting disease in Western Kenya. South west Kenya.
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Mulaa, M.; Kabirizi, J.; Pallangyo, B.; Hanson, J.; Proud, J.; Mukiibi, E.; Maeda, C.; Wanjala, B.;
Awalla, B.J and Namazzi, C. 2013.Diversity, biomass and resistance to stunt in Napier grass clones
in East and Central Africa region. In: Ndikumana, J.; Mubiru, S.; Zziwa, E. and Tenywa, J.S. (eds)
2013. Enhancing the competitiveness of the livelihoods in Eastern and Central Africa. Association for
Strengthening Agricultural Research in Eastern and Central Africa, Entebbe, Uganda pp 27-34. ISBN:
978-92-95070-96-7
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of Desmodium intortum in Central Kenya. In: Mwangi D.M. and Kairuki J. N. (eds). Proceedings of
APSK (Animal Production Society of Kenya), 2002. Annual Symposium held from 9th to 10th May
2002 at National Animal Husbandry Research Centre, Nairobi, Kenya. pp. 9-20.
Nanyeenya N.W; Kabirizi J.M; Zziwa, E.; Lukwago and Mugerwa, S. 2014. Promoting
Brachiaria hybrid cv. Mulato 1 as a fodder and seed crop in smallholder crop-livestock systems in
Uganda. National Livestock Resources Research Institute, Uganda (Unpublished).
Orodho, A.B, 2006. The role and importance of Napier grass in the smallholder dairy industry
in Kenya. www.fao.org/AG/AGP/AGPC/doc/newpub/napier/napierkenya.htm
Pallangyo B, Maeda C, Mkonyi S. 2008. Napier grass (Pennisetum purpurium (Sachum)
diversity, uses and diseases in Eastern, Northern and lake zones of Tanzania. In document of the 1st
National Plant Protection Advisory Committee Ad hoc meeting held at Sugarcane Research Institute,
Kibaha Tanzania 19th September 2008 pp 38 – 66
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Thorpe W. and Wambugu M. (1998). Characterisation of dairy systems supplying the Nairobi milk
market: A pilot survey in Kiambu district for the identication of target producers. KARI/MoA/ILRI
Collaborative Research Project Report
22
CHAPTER 4: Status of Napier grass stunt diseases in the East African region
4.1 Status, Napier stunt and smut disease and farmers management practices in Uganda
1Mugerwa S. 2Zziwa, E. and 1Kabirizi J.,
1National Livestock Resources Research Institute (NaLIRRI), Tororo, Uganda
Association for Strengthening Agriculture Research in Eastern and Central Africa (ASARECA), Uganda
Introduction
Agriculture is considered the most critical economic pillar throughout the region contributing over
45% of the regional GDP’s and directly employs over 75% of population; its revitalization is likely
to yield wide range of positive impacts. In line with the Millennium Development Goals (MDGs) of
halving global poverty by 2015, the New Partnerships for Africa Development (NEPAD) through
the Comprehensive Africa Agricultural Development Plan (CAADP) and in collaboration with
development partners initiated a regional outt to spearhead revitalization of agricultural productivity
throughout the Eastern Africa sub-region. This new outt was dubbed EAAPP, anchored in CAADP
pillar IV focusing on improving agricultural research, technology generation, dissemination and
adoption.
A baseline survey was carried out in three districts purposely selected to represent three agro-
Ecological Zones (AEZ) of Uganda. The districts included Jinja, Kiruhura and Katakwi which
represented the Lake Victoria Basin (LVB), Western Rangelands (WR) and the Eastern Semi-Arid
Zone (ESAZ), respectively. The survey examined farmers’ perceptions on feeds and feeding. The
key stakeholders included crop-livestock farmers, community extension staff and local government
agricultural production staff among others.
Methodology
The study design was cross sectional and both qualitative and quantitative data were employed
to gain an in-depth understanding of farmers’ socio-economic factors, livestock feeds and feeding
systems, livestock breeds and breeding methods and livestock health in three agro-ecological zones of
Uganda. The study sites were purposively selected based on their relevance to study questions. The
District Livestock Production Department provided a sampling frame which contained all livestock
keeping households from the selected districts. After consultations with the district extension staff,
fty households were then selected from each district using the sampling frame following systematic
random sampling procedures. The total number of livestock keeping households in each district was
divided by 50 to obtain an nth value. The rst household was chosen randomly but the subsequent
households were chosen after every an nth value until all the 50 households had been selected. In
totality, we administered questionnaires on 150 respondents.
Data sources and collection methods
Primary qualitative and quantitative data was obtained using semi-structured pre-tested questionnaires
administered by way of one on- one direct interview while secondary data was got from published
articles and reports among others. Secondary data was mainly used compare survey results with
existing trends as well as to discuss the survey results.
23
Validity of the questionnaire
Lawshe’s content validity ratio was used to measure the validity of study as described below: CVR
= (ne − N / 2) / (N / 2) where CVR = content validity ratio, ne = number of farmers indicating
“essential”, N = total number of farmers. For essential validity content validity ratio was 0.8. The
ratio formula yields values which range from +1 to -1; positive values indicate that at least half the
farmers rated the item as essential. The mean CVR across items may be used as an indicator of overall
test content validity.
Data collection and analysis
Data was collected by trained enumerators using a structured questionnaire. Data was analysed
using Statistical Packages for Social Sciences (SPSS). Graphs and cross tabulation tables were drawn
using Statistical Packages for Social Sciences (SPSS). Farmers’ responses on the constraints faced
in utilization of feeds in the three agro-ecological zones was subjected to nonparametric statistics
(Kruskal–Wallis one-way analysis of variance) to determine if signicant differences existed between
the different constraints. Six constraints were ranked by farmers using a scale of 1 to 6, with 6 being
the least important constraint and 1 the most important factor. The computed sum and mean of ranks
were compared using multiple pair wise comparisons to establish the signicance differences among
different constraints (Dinno, 2015).
Results and Discussion
Gender and age classication of respondents
Majority of the respondents were males with only 36, 17 and 22% of the respondents being females
in the ESAZ, LVB and WR respectively (Table 4.1.1). Most of the respondents were within the age
category of 21 - 40 and the mean household size was highest in ESAZ (14 members) and lowest in the
LVB (10 members).
24
Table 4.1.1: Gender and age classication of respondents
Table 4.1.2: Means of livestock types in the different Agro-ecological Zones
Household Composition Agro Ecological Zone (%)
ESAZ LVB WR
Respondent’s Gender
Male 64 83 78
Female 36 17 22
Mean Household size (numbers) 14.19 10.12 11.17
Age Category
Male 5-10 15.4 10.9 8.3
Female 5-10 9.7 7.9 6.0
Male 11-20 15.7 15.3 15.6
Female 11-20 11.4 14.4 13.9
Male 21-40 14.9 14.4 22.9
Female 21-40 16.2 11.9 12.8
Male 41-50 5.7 8.9 5.3
Female 41-50 4.9 10.4 6.4
Male>60 2.7 4.0 4.5
Female>60 3.5 2.0 4.3
ESAZ= East Semi-Arid Zone, LVB= Lake Victoria Basin and WR = Western rangelands
AE Z Livestock Type
Cows Breeding bulls Oxen Heifers Calves Sheep Goats Chicken
WR 50.54a1.81a1.67b22.92a21.46a3.04a28.75a8.16b
ESAZ 9.78b1.25ab 4.34a4.63b4.72b3.7a10.97b20.22a
LVB 3.24b0.4b0.08b1.44b1.44b0.08b3.52b7.79b
AEZ Agro-ecological zone, ab means with different superscripts across each column are
statistically
different at p= 0.05
Livestock inventory and ownership
The three AEZ differed signicantly (p = 0.001) in possession of livestock types (Table 4.1.2).
The vectors for number of breeding cows (2426), breeding bulls (87), heifers (1100), calves (1030) and
goats (1380) were increasing in the direction of western rangeland ecological zone (WR) indicating
that these livestock types were most abundant in the WR. On the other hand, chicken (647) and oxen
(139) were more abundant in the ESAZ compared to the WR and LVB.
Land ownership and tenure
The mean number of acres per household was highest in WR (279.3 acres) and lowest in the LVB
(4.7 acres) indicating that respondents in the LVB are largely smallholder farmers with limited land
resources for agricultural production (Table 4.1.3).
25
Table 4.1.3: Land Ownership and Tenure
Land Ownership and
Tenure
Category Agro Ecological
Zone
ESAZ LVB WR
Average Land area Size (acres) 30.2 4.7 279.3
Land Ownership and Tenure
(percentage)
Freehold with title 3.1 8 48.0
Freehold without title 93.8 92 52.1
Rented from other
individual
0 0 0
Communal 3.1 0 0
Informal 0 0 0
Mode of Acquisition (%) Purchase 28.1 48 75
Inherited 71.9 48 25
Rented 0 4 0
Main Land Use (%) Crop Production 93.8 56 66.7
Livestock 6.3 36 33.3
Homestead 8
Male 41-50 5.7 8.9 5.3
Female 41-50 4.9 10.4 6.4
Male>60 2.7 4.0 4.5
Female>60 3.5 2.0 4.3
Interventions that enhance agricultural productivity per unit of available land are thus more important
in the LVB than in any other region. The major system of land tenure was reported to be freehold
system but without titled followed by freehold system with titles. Communal land
Cultivation and management of Napier grass
In the ESAZ, only 4% of the farmers grow Napier grass with mean acreage of 0.25 acres. In the LVB,
88% of farmers grow Napier with mean acreage of 1.13 acres while in the WR only 14.6% of farmers
were growing the fodder with a mean acreage of 0.27 acres. Discriminant analysis biplot (Figure
4.1.1) indicated that farmers in the LVB mostly cultivate improved Napier varieties with a few of
them still cultivating the local varieties.
Figure 4.1.1: Disciminate analysis biplot showing the varieties and propagation
methods of Napier grass in the three agro-ecological zones
26
Overall, the percentage of land used in production of improved forages is 0.53%. Farmers mostly
use stem cuttings for propagation of the fodder. The farmers in the WR mostly cultivate local Napier
varieties and commonly use root splits for propagation. Farmers noted that weeding and application
of animal manures were the most common agronomic practices undertaken to improve productivity
of fodder and pasture. Other forage management practices included uprooting of diseased Napier
plants, spraying of pesticides, fencing off fodder elds to deter animals from destroying the elds.
Occurance and severity of Napier stunt disease. Majority of the farmers (76% of the respondents) in
the LVB reported the occurrence of Napier stunt disease on their farms (Table 4.1.4).
Table 4.1.4: Occurance of Napier stunt disease in the three agro-ecological zones
Agro-ecological zone Presence of Napier stunt disease (%)
Yes No WR
Lake Victoria basin 75.9 24.1 Research institutions Extension worker
West rangeland 31.5 68.5 4.5 4.5
Eastern Semi Arid 0 100.0 12.5 0
Overall 37.1 64.2 6.7 3.3
Thirty two (32) percent of the respondents reported the disease in the WR while no respondent
reported the occurrence of the disease in the ESAZ. The high prevalence of the disease in the LVB was
attributed to the increased cultivation of improved Napier varieties that are highly susceptible to the
disease. The reported absence of NSD in the ESAZ may not necessarily mean that the disease had not
affected the region but because farmers devote no efforts on fodder cultivation making it difcult to
notice such diseases. Farmers in the ESAZ mostly depend on natural Napier swards in the wilderness
which are either tolerant to NSD or farmers have not taken time to diagnose the disease. There is
hence a need for eld diagnosis.
Also, because only few farmers had taken the initiative to cultivate Napier in ESAZ, the farmers
were ignorant of the occurrence of the disease but yet in the actual sense, they had the disease. This
was evidenced during the survey when the farmers mistook the disease for inadequate soil nitrogen
implying that many could be ignorant about this disease. Fifty percent of the farmers faced with
disease ranked it as high (>10 diseased plants in 20 plants) while 35% ranked it as moderate (between
5-10 diseased plants in 20 plants). Only 15% of the affected respondents ranked it as low (< 5 diseased
plants in 20 plants) (Figure 4.1.2).
Irrespective of the level of severity, dedicated efforts need to be focused towards the management
of the disease to control its spread to non-diseased plants since it is transmitted by leaf hoppers that
jump from one plant to another. So although the farmers may rank it as low, it can spread quickly as
long as there are diseased plants in the eld. Majority of the farmers (70%) reported that they source
planting materials from other farms implying that this could also be a source of inoculums for the
disease. This also partly explains why the disease is more severe in the LVB where majority of farmers
obtain planting materials from other farms and these may be infected already.
Figure 4.1.2: Severity of Napier
stunt disease amongst farmers
27
Table 4.1.5: Sources of Napier planting materials
Agro-ecological zone Source of Napier planting materials (%)
Yes No WR
Own farm Other farms Research institutions Extension worker
Lake Victoria basin 9.1 81.8 4.5 4.5
West rangeland 50.0 37.5 12.5 0
Overall 20.0 70.0 6.7 3.3
Conclusions and recommendations
Based on ndings of the survey, the following conclusions were made:
a) Napier grass and natural pastures constitute the major sources of forages for feeding
livestock in the three agro-ecological zones.
b) Napier stunt disease is a major constraint to productivity of Napier grass and hence
sustainability of Napier based feeding systems.
c) The level of adoption of forage conservation practices is still very low with only 20% of the
respondents involved in forage conservation and preservation.
d) Maize bran and dairy meal are the main feed stuffs used to supplement animals in the LVB
while farmers in the WR and ESAZ largely use minerals to supplement their animals.
e) Maize stover and banana peels are the major crop residue types utilized by farmers for
feeding livestock.
f) The level of nutritional improvement on crop residues is still very low with only 14% of the
respondents adding molasses to crop residues before feeding them to animals.
g) Forage scarcity and high costs of feeds were noted as the most important constraints limiting
animal feeding systems in the three agro-ecological zones.
Recommendations on feeds and feeding
a) There is need to develop appropriate Napier stunt management interventions/technologies
to control the disease as well as to reduce the susceptibility of the plants to the disease.
b) It is imperative to elucidate the socio-economic determinants of adoption of forage
conservation and preservation technologies with the aim of enhancing their adoption.
c) There is a need to undertake focused eld surveys in the ESAZ to make logical conclusions
on the occurrence of NSD
d) There is an overwhelming need to develop socially acceptable and affordable area-specic
interventions for nutritional improvement of crop residues in addition to molasses.
e) There is a need to enhance forage conservation practices in order to alleviate the problem of
feed scarcity
References
Alexis Dinno, 2015. Dunn’s Test of Multiple Comparisons Using Rank Sums. http://cran.r-
project.org/web/packages/dunn.test/dunn.test.pdf
28
4.2 Napier Stunt Disease in Uganda: farmer perception and effect on fodder yield
Kabirizi Jolly 1, Alicai Titus 2, Steen Nielsen3, Taabu Lawrence1; John Kigongo1
1 National Livestock Resources Research Institute, P
2 National Crops Resources Research Institute,
3 Nielsen, Steen, University of Aarhus, Department of Integrated Pest Management, Research Centre
Introduction
The success of the smallholder dairy sector in Uganda depends on elephant grass (Pennisetum
purpureum), also known as Napier grass. This forage, whose high dry matter yields average about
16 tonnes/ha/year has become the country’s main fodder source grown by over 80% of smallholder
farmers in Uganda. It provides over 70% of the feed, and many farmers earn cash incomes from
selling Napier grass fodder to farmers who have insufcient land to grow their own feed (Kabirizi,
2006). The grass also serves as mulch in banana farming regions in Uganda.
Napier grass production in Uganda is threatened by the emergence of Napier stunt disease (NSD),
which undermine the contribution of the dairy value chain in poverty reduction programs (Kabirizi
et. al., 2004). Napier stunt disease (NSD) was rst observed in central Uganda in 2002. The disease has
been reported in over 40 districts where Napier grass fodder is a major forage for dairy cattle (Kabirizi
et. al., 2010). In view of the importance of Napier grass fodder in the smallholder dairy production
systems, surveys and on-station studies have been conducted to:
a) Identify symptoms of the disease;
b) Assess farmers’ perception of the disease, its management and socio-economic impact on
dairy cattle production.
c) Establish the presence of phytoplasma in affected plants and.
d) Determine the effect of the disease on napier grass fodder production.
Materials and methods
Description of study area
Surveys were conducted in Masaka district located between 00 15’ and 00 43’ South of the equator
and between 310 and 320 East longitude. The average altitude of the district is 1,115 meters above
sea level. The total geographical area is about 6413.3sq km out of which y 1,221 hectares are under
cultivation (Anon, 2009). Annual average rainfall ranges between 1100 mm–1200 mm with 100–110
rainy days. The soil texture varies from red laterite to sandy loam but is productive. The district has
about 944,200 people (about 49% women) with an annual population growth rate of 3.0% (Anon.
2009). The district has a cattle population of about 162,171 with about 8% of the cattle population
being improved breeds (Anon, 2008).
Survey procedure
An intensive survey procedure was adopted in which a structured questionnaire was administered
to 120 smallholder dairy farmers with 1-3 dairy cows. The sample farmers were selected from 12
villages in 4 sub-counties (Kingo, Bukulula, Kalungu and Mukungwe) with the highest population of
improved stall-fed dairy cows. Thirty elds were randomly selected for a detailed study. At each site,
the farmer’s Napier grass eld was assessed to record incidence and severity of the disease and extent
of stunt. Within each eld, 5 plants along two diagonals were recorded in detail. For each plant, the
29
presence or absence of the disease was noted, symptom types recorded and stunt scored on a 1 to 3
scale (1= no stunt, 2= moderate stunt and 3= severe stunt). The incidence of the disease was calculated
from the number of affected plants as a percentage of the total number of plants assessed in a eld.
Herbage biomass yield was estimated using methods described by Kabirizi (2006). Plant height and
root length were measured for randomly selected plants representatives of disease-free and affected
plants in each quadrate. In addition, participatory rural appraisal sessions were held with 2 farmer
groups that comprised of dairy farmers who had beneted from in-calf heifer projects. The objective
was to document farmers’ perception of the disease, its management and socio-economic impact on
dairy cattle production.
Establish the presence of phytoplasma in Napier grass stunted plants
Samples of Napier grass leaves from plants with symptoms of stunt disease were taken from the Lake
Victoria Crescent zone (Wakiso, Jinja, Kampala and Masaka districts); the north-eastern area (Iganga,
Lira, Soroti and Tororo districts) and from the highland areas of south-western Uganda (Kabale and
Kabarole districts). The districts represented the major agro-ecological zones of Uganda. The leaves
were air dried and mailed to University of Aahus, Faculty of Agricultural Sciences in Denmark.
Presence of phytoplasma was tested according to Nielsen et al. (2007). A nested PCR using primer
pairs P1/P7 and either R16R2/R16F2n (Gundersen et al. 1996) or P3/P7 (Smart et al. 1996) was used
to generate template for sequencing. Sequencing primers were R16R2, R16F2n, P3 and P7. Sequences
were aligned using Vector NTI (Invitrogen, Carlsbad, USA).
Results and discussion
Napier Stunt Disease symptoms
The most obvious symptoms of NSD observed on farmers’ elds were stunt, twisting/curling and
cupping of leaf tips and yellow/purple streaking/vein clearing at leaf tips. Affected leaves often had
mosaic rather than a normal evenly and slight curved edge, were yellow in colour and in most cases
showed signs of wilting. Leaves of severely affected plants were reduced to short sword-like stubs that
were often less that one-third of leaves of unaffected plants. Affected plants also had retarded poor
root formation and could easily be uprooted. In extreme cases, affected plants lost leaves entirely and
the stem was unusually short and thick. Shoot proliferation was also observed especially for rationed
stools, but the plants remained stunted with tiny leaves.
Napier grass disease incidence and severity
Napier stunt disease was present in 29 out of 30 elds assessed. The overall incidence of the disease
was 42.3% (Table 4.2.1).
Table 4.2.1: Incidence and extent of Napier stunt disease in Masaka district
Sub-county Number of elds Mean incidence (%)1Mean stunt2
Mukungwe 11 25.1 2.3
Kingo 1 33.3 2.2
Municipality 2 53.3 2.6
Bukulula 16 57.0 2.4
Mean 42.3 2.3
1The number of affected plants as a percentage of the total number of plants assessed in a
eld;
2Scored on a 1-3 scale (1 = no stunt, 2 = moderate stunt and 3 = severe stunt)
30
Farmers’ perception of the disease, its management and socio-economic impact on dairy
cattle production
Information from individual interviews and group discussion showed that farmers were able to
recognize the disease and branded it as the most important disease of Napier grass in the area. Many
farmers recalled that they rst noticed the disease in 2000, but reckon that it is becoming more prevalent
and severe. The farmers asserted that the problem is a disease, but not a pest attack, nutritional disease
or any other environmental stress. They observed that the disease occurs throughout the year but is
more severe during the dry season probably due to moisture stress. Most (65%) farmers were of the
view that the disease occurs under all soil and eld management conditions but poor soils and poor
management (weeds and harvesting) aggravate the disease. They also observed that affected plants
often completely degenerate by the third harvest. Even plants that are apparently healthy during the
primary growth often had symptoms after rationing. Management practices used to control Napier
stunt disease in the study areas are shown in Table 4.4.2.
Table 4.2.2: Major management practices used by farmers to reduce NSD incidence
Strategy Percentage of respondents (%,
n=120)
Weeding 2
Rouging 27
Use clean planting materials 7
None 2
Rouging and manure application 62
Signicant (p<0.05) differences were noted between sub-counties and between individual elds in
a sub-county in the incidence of the disease. The greatest incidence was 57%, recorded in a eld in
Bukulula sub-county. Overall mean stunt was 2.3 and sub-county means were greatest in Municipality
compared to rural areas (Bukulula, Mukungwe and Kingo sub-counties) (Table 4.2.1). Affected plants
appeared to be randomly distributed in the eld. Severely affected plants and normal plants were
observed to be growing side by side.
Effect of Napier stunt disease on plant height, root length and fodder yield
Mean plant height and root length decreased by about 50% in diseased plants when compared to
healthy plants (Figure 4.2.1).
Figure 4.2.1: Effect of Napier stunt disease on plant height, root length, herbage biomass yield and number of shoots
Herbage biomass yield decreased by over 55% in diseased plants when compared to healthy plants
(Figure 4.2.1). The reduction in herbage biomass yield was partly due to rouging. Field observations
showed that the incidence was higher in pure stands of elephant grass than where Napier grass was
planted with a forage legume.
31
About 60% of the farmers reported rouging and manure application as the major strategies they use
to reduce disease incidence. A few (7%) of the respondents selected clean Napier planting materials
from vigorous, disease free plants. However, they noted that using clean planting materials is not a
guarantee that the plants will sprout without disease or will be affected later.
Applying manure and rouging in Napier grass elds, as they did, had the potential to reduce the
effect of the disease as the unaffected tillers ourished although they were not aware of this. Farmers
reported a decline of about 25% in NSD incidence which they attributed to manure application.
Manure enhances growth and establishment of plants through enriching the soil with the required
nutrients. In light of this, plants become less susceptible to disease stress than already stressed plants
(Mpairwe, 1998). It is also possible that manure interferes with multiplication and survival of disease
organisms through modication of the micro-environment or through enhancement of natural
enemies to disease causing organisms (Mugerwa, 2010; personal communication).
During focus group discussions, farmers estimated managing (rouging and manure application and
replanting) the Napier stunt disease in the affected elds, would cost them US $ 200-400 per ha. The
farmers estimated loosing up to 50 percent of the fodder due to the disease which would translate into
a reduction in milk yield of over 30%. Nevertheless, none of the farmers had ever abandoned crops or
particular Napier grass cultivars on their farms because of the problem.
Establish the presence of phytoplasma in Napier grass stunted plants
Out of 31 samples collected from 10 districts, 17 tested positive for the phytoplasma (Table 4.2.3).
Phytoplasma was detected in two of the three main Napier grass growing areas. However, as only 5
samples from the south western area were analysed, it cannot be concluded that the disease is absent
in this region. Whether the inability to detect phytoplasma in a number of samples with symptoms
is caused by inadequacy of the PCR methods, uneven distribution of phytoplasma in the plant,
inadequacy of the method of storing sampled leaves (air drying) or that the stunting symptoms may
be caused by other factors remains to be investigated. To investigate possible molecular variation
between samples, seven samples from different districts were sequenced in the R16R2/R16F2n PCR
fragment of the 16S rRNA gene (app. 1.2 kbp) and the P3/P7 PCR fragment of the 16S/23S intergenic
spacer (app. 0.3 kbp) (Nielsen et. al., 2007).
Table 4.2.3: Results of PCR-tests of leaf samples of stunted Napier grass from 10 districts in
Uganda
Sub-county District No of
localities
No. positive loc/
total loc
No of samples
sequenced
North-Eastern Iganga 5 4/5 1
Lira 3 3/3 1
Soroti 3 3/3 1
Tororo 1 0/1 1
Lake Victoria Shore Jinja 3 2/3 1
Kampala 3 1/1 1
Masaka 8 3/8 2
Wakiso 2 2/2 1
South-Western Kabale 4 0/4 0
Kabalore 1 0/1 0
Loc. = location,
32
The seven sequences derived from the 16S/23S intergenic spacer did not show any variation either,
although this region is generally more variable than the conserved 16S rRNA (Nielsen et. al., 2007).
The sequences were most similar to Bermuda grass white leaf phytoplasma ribosomal sequences
(there are no Napier grass stunt phytoplasma sequences from the 16S/23S intergenic spacer in the
GenBank). The identical sequences of the Kenyan and Ugandan isolates of phytoplasma combined
with the very quick spread of the disease in the East African Region points to that the phytoplasma
originates from a common source. However, the new knowledge that phytoplasma isolated from
Ethiopian Napier grass with stunt disease symptom belongs to another phytoplasma group, namely
16SrIII Group phytoplasma, than the Ugandan and Kenyan isolates indicates that reality is more
complicated. More data of sequences of isolates from the region are necessary to give a more complete
picture of the sources and migration of the stunt disease.
Conclusion
The results presented in this paper represent the rst systematic quantication in Uganda of the
prevalence of the Napier grass stunt disease, the extent of damage it is causing and farmers’ attempts
to control it. Generally, the problem was highly prevalent in Masaka district, although incidence
levels varied with location. It is also clear that the disease is seriously damaging Napier grass, causing
signicant reductions in herbage biomass yield. In view of the importance of livestock to the livelihoods
of the smallholder dairy farmers in Uganda and the dramatic symptoms of this Napier grass stunt
disease there is a need to continue monitoring the occurrence and spread of the disease. Existing
Napier grass varieties should be screened to assess the impact of the disease on their productivity.
Additional work should be initiated aimed at providing farmers with resistant Napier grass planting
materials.
References
Anon, 2009. Masaka district annual report, 2002-2003. Ministry of Agriculture, Animal
Industry and Fisheries
Kabirizi, J., Mpairwe, D and Mutetikka, D. 2004. Testing forage legume technologies with
farmers: A case study of Masaka district, Uganda. Uganda Journal of Agricultural Sciences 9, 906-
913.
Kabirizi, J. 2006. Improving feed availability and animal performance: Incorporating forage
legumes in farming systems”. PhD Thesis. Makerere University. pp. 82
Kabirizi, J.; Alicai, T.; Molo, R. and Kigongo, J. 2010. Napier stunt disease control strategy
project: technical report, November 2009.
Nielsen, S.L., Ebong, C., Kabirizi, J. and Nicolaisen, M. 2007. First report of a 16SrXI Group
phytoplasma (Candidatus Phytoplasma oryzae) associated with Napier grass stunt disease in
Uganda. New Disease Reports 14, January 2007.
33
4.3 Status, Napier stunt and smut disease and farmers management practices in Western
and Central Kenya
Margaret Mulaa1, Francis Muyekho2, Mwendia Solomon4, Sally Rono1, Mutoko Mogan1, Hanson Jean5, Janice
Proud5, Sammy Ajanga3, Lusweti C, Ego W1 and Mukasa B1
1 Kenya Agricultural and Livestock Research Institute, P.O. Box 450 Kitale, Kenya
2 Masinde Muliro University of Science and Technology, P.O. Box 190 Kakamega, Kenya
3 Kenya Agricultural and Livestock Research Institute, P.O. Box 169 Kakamega, Kenya 3&4 Kenya
Agricultural and Livestock Research Institute, Muguga, Kenya 4ILRI, Addis Ababa, Ethiopia
Introduction
Napier grass constitutes between 40 to 80% of forages used by smallholder dairy farmers in Kenya.
The productivity of Napier grass in western and Central Kenya is currently threatened by stunt and
smut diseases causing yield reduction of up to 90% (Mulaa and Ajanga 2005). Stunt disease is more
prevalent in western (Mulaa and Ajanga 2005), while smut disease is more restricted to Central Kenya
Mwendia 2007). Both diseases cause stunted growth in plants with low biomass that are unable to
sustain the feed requirements of dairy cows. Farmers are forced to reduce herd size with related
reduction in farm income in the absence of alternative feeds. Majority of the farmers have land size
due to a high human population and as a result have adopted semi or zero grazing systems. Such
systems demand readily available forage. This translates to time and economic loss if farmers have
spent time looking for grass far away from their farms. Although farmers in western and Central
Kenya have beneted from the management strategy measures that have been packaged by KARI
and other stakeholders through extension ofces at various levels of administration they are still
demanding for a solution to the severe losses that they suffer due to the effects these diseases. The
objective of this study was to determine the current dairy and Napier grass management practices,
the spread and severity of Napier stunt and smut diseases and farmers copping strategies in the
management of these diseases.
Methodology
The study design was cross sectional and both qualitative and quantitative data were employed to gain
an in-depth understanding of farmers’ socio-economic factors, livestock feeds and feeding systems,
livestock breeds and breeding methods and livestock health in six districts in Kenya. The study sites
were purposively selected based on Napier grass production and utilization in the intensive and
semi-intensive dairy production systems. Other factors considered in selecting the survey area were
the level of smut and stunt disease incidence and severity (Agro-ecological Zones having unique
climatic conditions for stunt and smut disease occurrence) and actual and potential suitability for
diary production. The districts surveyed were: Bugoma, Mumias/ Butere(Low Dryland), Busia (Lake
region) in Western Kenya and Kiambu and Muranga (High altitude) in Central Kenya. Total of 551
Households with a minimum of 71 respondents were surveyed. Transects were selected, mainly
following roads and households were selected randomly with every 5th house interviewed. The data
was entered in the spreadsheet analysed using SPSS.
Disease incidence was determined using a scale of 1 – 4 whereby 1 = Nil (no plants with symptoms,
2 = Mild (< 25% of plants with disease symptoms), 3 = Moderate (25 – 50% of plants with disease
symptoms) and 4 = severe (> 50% of plants with disease symptoms). Disease severity was determined
using a scale of 1 - 4 whereby 1 = Nil, 2 = Mild (<25% of tillers with disease symptoms), 3 = Moderate
(25 – 50% of tillers with disease symptoms) and 4 = severe (> 50% of tillers with disease symptoms).
34
Baseline information
Majority of the households had between 1 to 5 people (Table 4.3.1). There males and youths were more
household than females in all the districts. The number of improved dairy cattle was low (ranging
21.2% and 30.8 %) in Western Kenya compared to Muranga and Kiambu (49.4% – 77.6%). Most of
the farmers kept one to two animals and there were more famers in Central Kenya than in western
Kenya (Table 4.3.2). Milk production during the rainy (good) season differed between districts. In
western Kenya, majority of the farmers in Bungoma and Butere produced 3 to 6 litres of milk per day,
while the majority (25%) in Busia produced 1 to 2 with some 20% producing over 20 litres and those
of Mumias produced 9 to 10 litres per day (Table 4.3.3). Milk production per household was higher
in Central Kenya than in western Kenya with over 47.2% farmers in Kiambu producing over 12 litres
of milk per cow per day and 27.8% of Muranga’ producing 9 to 10 Litres. During the dry season
majority of farmers in western produce 1to 4 litres while those in Central produce 4-6 litres of milk
per day (Table 4.3.4). Between70-95% of the milk produced in all the districts was sold. Majority of the
farmers in Central Kenya practice intensive zero grazing while in western the most practiced system
was semi-zero and tethering (Table 4.235).
Table 4.3.1: Proportion of male, female adults and youths per household in western and
Central Kenya
Table 4.3.2: Number of improved dairy cattle per household in western and Central Kenya
Sources of forage Percentage (%) respondents by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Males
1 - 2 49.1 50.0 35.2 48.0 31.8 56.3
3 - 5 26.8 27.1 38.5 32.0 51.8 37.5
6 - 8 13.4 12.5 15.4 12.0 11.8 5.0
9 – 12 7.1 10.4 9.9 8.0 4.7 0
13 - 15 0.9 0 1.1 0 0 1.3
Over 15 2.7 0 0 0 0 0
Females
1 - 2 69.1 67.3 71.6 86.0 72.8 82.9
3 - 5 26.4 30.6 26.1 14.0 23.5 17.1
6 - 8 2.7 0 1.1 0 3.7 0
9 – 12 1.8 2.0 1.1 0 0 0
Number of teenagers per household
1 – 2 59.3 52.6 58.5 62.9 71.8 60
3 – 5 33.7 34.2 34.1 28.6 20.5 28.0
6 – 8 5.8 7.9 5.7 7.7 7.7 8.0
13 - 15 1.2 5.3 0 0 0 4.0
9 – 12 0 0 0 2.9 0 0
Number of improved dairy cattle Percentage (%) response by districts
Bungoma Mumias Butere Busia Kiambu
None 53.5 55.8 64.5 61.5 10.3
1—2 28.9 30.8 21.5 21.2 49.4
3—5 12.3 9.6 8.6 17.3 27.6
6−10 5.3 3.8 5.4 0 12.6
35
Table 4.3.3: Percentage (%) range of milk production in litres per day during good (rain
season) months in western and Central Kenya
Range of milk production Litres/day Percentage (%) response by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Less than 1 2.1 5.0 1.6 2.5 0 0
1-2 19.1 10.0 18.8 25.0 1.4 4.2
3-4 29.8 15.0 28.1 17.5 0 9.7
5-6 26.6 15.0 26.6 12.5 12.5 23.6
7-8 6.4 15.0 4.7 7.5 5.6 12.5
9-10 6.4 25.0 14.1 12.5 25.0 27.8
11-12 2.1 5.0 0 2.5 8.3 5.6
Over 12 7.4 10.0 6.3 20.0 47.2 16.7
Table 4.3.4: Average milk yield in litres per day during the dry season in western and
Central Kenya
Range of milk production Litres/day Percentage (%) response by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Less than 1 17.0 17.5 15.9 12.5 1.4 4.2
1-2 45.7 17.5 34.9 35.0 5.6 19.4
3-4 22.3 27.5 27.0 15.0 20.8 34.7
5-6 10.6 20.0 12.7 5.0 16.7 19.4
7-8 2.1 12.5 3.2 5.0 16.7 9.7
9-10 1.1 2.5 3.2 12.5 19.4 6.9
11-12 0 0 0 2.5 4.2 1.4
Over 12 1.1 2.5 3.2 12.5 15.3 4.2
Table 4.3.5: Dairy cattle production system in western and Central Kenya
Livestock production systems Percentage (%) respondents by districts
Bungoma Mumias Butere Busia Kiambu Murang’a
Extensive grazing 11.5 6.8 8.9 9.5 3.6 5.4
Semi intensive 53.8 33.3 25.8 35.7 13.5 22.5
Tethering 20.0 35.0 39.5 34.5 1.6 5.4
Intensive/ zero grazing 7.7 24.8 25.8 20.2 81.3 66.7
In western the major sources of livestock feeds were own natural pasture/ fallow and rented natural
pasture/ fallow with own planted pasture contributing less than 10% of the feeds available (Table
4.2.6). On contrary, farmers in Muranga’ obtained most of the feeds from own planted pasture/
fodders and own natural pasture/fallow while those in Kiambu depended more on communal
grazing than own planted pasture/fodders. Farmers in all the districts depended more on purchasing
Napier grass followed by other grasses to meet the feed shortage gap during the dry season (Table
4.2.7). Purchased fodder was mainly from neighbouring farms and only less than 20% was obtained
from markets (Table 4.3.8).
36
Table 4.3.6: Sources forage available to farmers in western and Central Kenya
Table 4.3.7: Important copping strategies when fodder is short supply in western and
Central Kenya
Sources of forage Percentage (%) respondents by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Own planted pasture 7.7 9.2 2.4 7.9 8.6 28.8
Rented planted pastures 2.1 3.4 1.2 0 3.2 0
Own natural pasture/ fallow 62.7 57.5 70.7 58.7 12.9 27.4
Rented natural pasture/ fallow 20.4 14.9 4.9 14.3 5.4 2.7
Own planted forage 2.8 6.9 11.0 9.5 17.2 23.3
Rented planted forage 1.4 0 0 0 2.2 1.4
Communal natural pasture 2.8 8.0 9.8 9.5 50.5 16.4
Copping strategies during times of feed shortage Percentage (%) respondents by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Buy Napier grass 37.4 54.4 57.7 61.4 60.7 65.3
Feed all animals less 0.5 1.0 0 1.4 3.4 5.3
Buy other fodder 5.5 10.7 1.0 7.1 18.0 7.4
Feed some animals less 4.4 0 0 1.4 .6 0
More animals 4.9 10.7 0 11.4 0 0
Rent grazing 7.7 0 1.0 8.6 0 3.2
Feed on other grasses 25.8 16.5 26.8 7.1 13.7 13.7
Feed on crop residues 13.7 6.8 7.2 0 1 5.3
Sell animals 0 0 6.2 1.4 1.1 0
Table 4.3.8: Sources of purchased fodder in western and Central Kenya
Sources of purchased fodder Percentage (%) response by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Neighbour 78.8 88.3 87.5 90.0 71.4 94.7
Market 11.1 11.7 12.5 10.0 25.5 5.3
Public institution 10.1 0 0 0 0 0
Farmers’ group 0 0 0 0 3.1 0
37
Table 4.3.9: Area planted Napier grass in Western and Central Kenya
Table 4.3.10: Preferred Napier grass varieties in Western and Central Kenya
Land in acres under Napier grass Percentage (%) response by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Less than 0.25 57.0 45.0 44.9 30.5 31.8 39.1
0.25-0.5 23.8 37.4 23.8 32.4 25.1 33.9
0.5-1 13.1 7.6 16.3 17.1 26.1 12.2
1-2 4.7 5.3 8.2 14.3 10.9 13.0
2-3 0.5 2.3 4.1 1.9 2.8 17
3-5 0.5 1.5 2.7 3.8 3.3 0
Over 10 0.5 0.8 0 0 0 0
Napier grass variety as identied by farmers Percentage (%) response by districts
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Bana grass 51.8 53.5 52.7 57.7 42.1 33.0
Clone 13 0.6 - - 1.0 - -
French Cameroon 2.9 2.4 - 2.9 3.3 17.9
Hairless 5.3 3.1 4.1 - 1.4 4.5
Hairy 5.3 4.7 2.7 2.9 1.9 3.6
Local 7.1 9.4 22.3 3.8 18.7 34.8
Narrow leafed 27.1 24.4 16.9 30.8 8.1 3.6
Kakamega 1 - 2.4 - - 5.7 1.8
Mixture - - 0.7 - - -
Uganda hairless - - 0.7 1.0 - -
Agriculture - - - - 7.2 -
Ex-Githunguri - - - - 11.5 .9
Napier grass production and management
Area planted with Napier grass ranged between 0.25 to over 10 acres, with majority planting less than
0.5 acres (Table 4.3.9).
Most farmers plant 1-2 varieties of Napier grass while some farmers in Mumias, Busia, Kiambu and
Muranga plant 4-5 varieties. Bana is the most preferred variety in the 6 districts surveyed (Table
4.3.10) followed by French Cameroon, a local variety and narrow leaved variety. In Kiambu Napier
variety Ex-Githunguri was also one of the preferred varieties.
The most important criteria used by farmers for selecting Napier varieties were herbage yield followed
by fast growth (Table 4.3.11).
38
Table 4.3.11: Criteria used by farmers when choosing Napier grass variety to plant in
western and Central Kenya
Table 4.3.12: Period of maintaining Napier grass stand in same farm in western and Central Kenya
Farmers Napier grass selection criteria Percentage respondents on criteria for selecting Napier grass
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Fast growing 10.2 14.8 25.9 20.0 18.7 18.4
Disease resistant 6.2 3.9 2.9 4.0 2.0 0
Drought resistant 4.0 3.9 0 6.0 5.4 4.4
Herbage Yield 40 52.3 48.9 51.0 50.7 58.8
Number of tillers 0 1.6 5.8 1.0 9.9 12.3
Color of leaves 0 10.2 6.5 0 3.0 1.8
Length of reed 0 12.5 3.6 4.0 4.9 0
Any Napier material 0 0.8 6.5 10.0 4.9 3.5
No hairs 0 0 0 4.0 0.5 0.9
Period in months and years Period in
months and years
Percentage of respondents
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Less than 6 months 6.5 3.1 4.7 1.0 5.2 3.5
6-12 months 14.0 11.7 14.7 9.6 6.2 12.2
1-2 years 14.0 22.7 18.7 21.2 15.2 15.7
2-3 years 15.0 21.9 16.7 11.5 7.6 10.4
3-4 years 16.8 7.8 11.3 15.4 17.1 11.3
More than 4 years 33.6 32.8 34.0 41.3 48.6 47.0
Disease tolerance, drought tolerance and absence only accounted for less than 6%. The source of
planting materials for the preferred varieties was mainly from Neighbours (58-73.8%). This was
followed by own farms in Kiambu (19%) and Murang’a (31%). Research Institutes and Government
training institutes provided the least (< 10%) possibly because of the distance. In Busia, NGO’s was
also a major source of planting materials. Most farmers interviewed had maintained the Napier grass
for more than 4 years (Table 4.3.12) and had cut it at least 6 times in a year especially in Mumias,
Butere, Busia and Kiambu (Table 4.3.13).
The common frequency of cutting Napier grass was after every 4 weeks during the wet season and
between 6-8 weeks during the dry season. Most farmers cut their Napier when it is 80cm-100cm
tall. Most farmers don’t sell their Napier grass. A few who sell do so between February and March
and between October and November. Months of Napier shortage are between January and March
and November and December, while in Kiambu and Muranga the shortage occurs in August and
September. Most farmers who buy Napier usually do so between January and February and in
December when there is shortage due to drought.
39
Table 4.3.13: Number of harvest made on Napier grass by farmers in western and
Central Kenya
Number of harvest Percentage of respondents
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
1st harvest 5.1 3.1 3.5 1.9 4.9 2.8
2nd harvest 3.7 3.8 2.8 1.9 3.3 4.6
3rd harvest 13.6 5.3 6.3 8.6 29.0 19.3
4th harvest 18.7 10.7 12.5 18.1 8.7 35.8
5th harvest 12.6 3.8 3.5 7.6 1.6 14.7
6th harvest 44.9 73.3 71.5 61.9 52.5 22.9
7th harvest 1.4 0 0 0 0 0
Important practices used by majority of farmers to improve Napier yields are mainly weeding and
use of manure (Table 4.3.14).
Table 4.3.14: Napier grass management practices adopted by farmers to improve yields in
western and Central Kenya
Napier grass management practices Percentage of respondents
Western Kenya Central Kenya
Bungoma Mumias Butere Busia Kiambu Murang’a
Weed 53.5 68.7 81.5 85.7 55.5 43.5
Manure 35.7 26.7 15.9 13.3 42.1 56.5
Remove infected tillers 2.8 1.5 0.7 1.0 0.5 0
Remove infected plants 5.6 0.8 0.7 0 1.9 0
Add chemical fertilizers 2.3 2.3 1.3 0 0 0
Few farmers (<5%) remove infected tillers and plants. The least used methods are adding chemical
fertiliser. Most farmers in western use cuttings to establish new Napier plots, while those in Kiambu
(49.0%) and Muranga (77.2%) mostly use root splits. In western some farmers (<3%) use whole canes.
Most farmers (82.5-84.5%) especially Kiambu and Muranga districts get their planting materials from
within 1km from their farms and the majority (57 92%) plant their Napier grass in plots. In western
26–34% in addition plant Napier grass on boundaries either to control soil erosion or in the push-pull
technology to control stemborers.
Napier grass stunt and smut diseases
Most farmers in western (94-99%) had noticed Napier stunt disease in their districts and 18-28% had
noticed on their farms compared to less than 16% in Central Kenya (Table 4.3.15). On the contrary
more farmers in Central Kenya had observed smut disease their districts and farms (68.9 and 44.9%
respectively in Kiambu) and (80.5 and 47.8 % respectively in Murang’a) compared to western Kenya
where farmers only farmers in Bungoma (5.8%) and Busia (1.4 %) had observed smut the disease
(Table 4.3.15). Also fewer farmers in western Kenya had observed both diseases on their farms than
those in Central Kenya.The farmers in Central Kenya claimed that smut disease rst appeared in in
Kiambu in 1972 and stunt disease in Mumias in 1975. Smut disease became serious as from 2000 in
Muranga and 2007 in Kiambu.
40
Table 4.3.15: Presence of Napier stunt farmers own farm and within the district in western and Central Kenya
District Napier stunt disease -
Percentage respondents who
have seen the disease on their
own farm
Napier headsmut disease
-Percentage respondents who
have seen the disease within
the district
Both Napier stunt and
smut diseases - Percentage
respondents who have seen
the disease within the district
Own
farm
District No.
respondents
Own
farm
District No.
respondents
Own
farm
District No.
respondents
Western
Kenya
Bungoma 27.7 94.2 98 5.8 3.8 4 12.5 1.9 2
Mumias 22.0 97.5 78 0 0 0 12.5 2.5 2
Butere 27.7 99.0 98 0 0 0 6.3 1.0 1
Busia 18.9 95.7 67 1.4 1.4 1 12.5 2.9 2
Central
Kenya
Kiambu 2.0 15.6 7 44.9 68.9 31 43.8 15.6 7
Murang’a 1.7 14.6 6 47.8 80.5 33 12.5 4.9 2
Napier stunt disease was more severe in western Kenya than in Central Kenya (Table 4.3.16).
Table 4.3.16: Napier stunt disease severity in farmers own farm and within the district in western and Central
Kenya
District Percentage response on Napier stunt disease severity
Mild (1 in 20 stools) Moderate (1 in 4 stools) Severe (More than 1 in 4 stools)
Own farm District Own farm District Own farm District
Western Kenya
Bungoma 28.6 44.8 28.3 29.3 21.7 12.9
Mumias 14.3 31.3 25.8 37.3 33.3 27.7
Butere 28.0 50.5 28.3 33.7 17.4 11.9
Busia 20.9 48.1 15.0 22.8 18.8 16.5
Central Kenya
Kiambu 4.4 18.2 2.5 6.8 7.2 11.4
Murang’a 3.8 8.2 0 0 1.4 1.2
Among the Central Kenya districts the disease was comparatively more severe in Kiambu than
Murang’a. Napier headsmut disease on the other hand was severest in Central Kenya districts than
western Kenya with Kiambu being more affected than Murang’a (Table 4.3.17)
Both diseases usually appears after 1st cut but the severity increases between 4th and 5th cut for
stunt and between 3rd and 5th cut for headsmut disease. In terms of altitude headsmut disease was
observed mostly between altitude 1727 and 2191 meters above sea level in Kiambu and Muranga,
but was also observed at lower altitude of 1365 metres in Busia district. Some Kiambu and Muranga
said they had planted smut tolerant Napier varieties mostly Kakamega 1and had given some of those
varieties to other farmers.
Both diseases usually appears after 1st cut but the severity increases between 4th and 5th cut for
stunt and between 3rd and 5th cut for headsmut disease. In terms of altitude headsmut disease was
observed mostly between altitude 1727 and 2191 meters above sea level in Kiambu and Muranga,
but was also observed at lower altitude of 1365 metres in Busia district. Some Kiambu and Muranga
said they had planted smut tolerant Napier varieties mostly Kakamega 1and had given some of those
varieties to other farmers.
41
Table 4.3.17: Napier head smut disease severity within farmers own farm and within the
district in western and Central Kenya
District Percentage respondents of farmers on Napier headsmut disease severity
Mild (1 in 20 stools) Moderate (1 in 4 stools) Severe (More than 1 in 4 stools)
Own farm District Own farm District Own farm District
Western Kenya
Bungoma 0 0 10.5 2.6 0 0
Mumias 0 0 5.3 1.6 0 0
Butere 2.1 1.0 0 0 0 0
Busia 2.1 1.3 5.3 1.3 16.7 1.3
Central Kenya
Kiambu 54.2 37.1 47.4 12.9 33.3 2.9
Murang’a 41.7 23.5 31.6 7.1 5.0 3.5
The most important methods to control and/or minimize the spread of the disease were manure
application and weeding in all the districts. Uprooting, burning of infected plants, rotating with
other crops and mulching was only practiced in Central Kenya districts by 2-12% of the farmers. The
major sources of information on stunt and smut disease management are Ministry of Agriculture and
Livestock Extension staff (68.2%) and personal experimentation (30.3-60.6). Seminars, workshops
and Agricultural shows played a lesser role.
References
Mulaa, M. A. and Ajanga, S. (2005). A survey to collect and identify potential vectors of
Napier grass stunting disease associated with phytoplasma in Western Kenya. Report of a survey
conducted 25th-29th November 2005.
Mwendia SW, Wanyoike M, Nguguna MGJ, Wahome RG and Mwangi DM. 2006. Evaluation
of napier grass cultivars for resistance to napier head smut. In: Proceedings of the 10thKenya
Agricultural Research Institute Biennial Scientic and Exhibition of Innovations. www.kari.org/
leadmin/publications/10th proceeding. Accessed on 6th/6/2012.
42
4.4 Status of Napier Stunt Diseases in Eastern and Northern zones of Tanzania and
management strategy
Beatrice Pallangyo1, Msangi B2 , Nsami E3,Mngulwi S4
1 Plant Health Services, Ministry of Agriculture Food Security and Cooperatives, P. O. Box 9071
Dar Es Salaam, Tanzania Tel. +255 754601731 email: beatricepallangyo@yahoo.com,
2 Tanzania Livestock Research Institute, P.O.Box 5 Kongwa, Tanzania,
3 National Biological Control Program. P.O.Box 30031, Kibaha, Tanzania,
4 Tanzania Livestock Research Institute, P.O.Box 5016, Tanga, Tanzania
Introduction
From early 1970,s – 1990’s, grass pastures including Napier (Pennisetum purpurium), Guatemala
(Tripsacum laxum), and Setaria (Setaria sphacelata) were introduced in Tanzania to alleviate dairy feed
shortages and improve dairy production. Among the introduced fodder grasses, Napier is the most
widely adopted due to its’ high yielding and nutritional qualities. However, the production of this
grass is threatened by occurrence of Napier Stunt Disease (NSD) which was reported in Tanzania
in 2008 (Pallangyo et al.., 2008). Baseline survey that was conducted in 2008 reported occurrence of
the disease in Eastern, Northern and Lake agricultural zones (Pallangyo et al.., 2008). By 2013, the
disease had already spread to Zanzibar Islands (Maeda and Pallangyo, 2010) and Southern highlands
of Tanzania mainland (Pallangyo et al.., 2014).
Serious fodder shortage was experienced by farmers leading to decline in milk productivity, sale
of livestock, and shifting from Napier to alternative crops some of which had lower income value.
Decline in milk productivity due to NSD led to food and income insecurity especially in rural
households whose income depends on livestock farming. With shortage of fodder, women who
dominate the dairy business had to travel long distances to nd alternative fodder, yet fullling
household responsibilities.
Under ASARECA Napier Smut and Napier Stunt resistant project that came to an end in 2010 and the
ongoing EAAPP project titled “Exploiting Napier stunt and smut disease resistance to increase feed
availability in smallholder dairy systems”, NSD tolerant varieties were also identied which could
be integrated with cultural practices in NSD management. Public awareness on cultural practices
for NSD management was also created which led to decline of NSD incidence in affected areas. In
January 2015, survey was conducted to follow up status of the disease in previously affected areas
and establish current spread limit.
Specic Objectives
(a) Determine incidence and severity of Napier Stunt Disease in Meru, Muheza and Lushoto
districts
(b) Create public awareness on Control measures for NSD
Methodology
The survey covered the eastern (Muheza and Lushoto districts), and northern (Meru district) agro
ecological zones. The survey area represented differing agro ecological zones, presence of farmers
practicing zero grazing where Napier grass is a basic fodder and where Napier Stunt Diseases have
been reported. Focus Group Discussion Meetings of at least 10 stakeholders were conducted in each
43
district to enable the selection of village sampling frame. Ward Agricultural and Livestock Extension
Ofcers (WAEOs) were trained on enumeration, identication of NSD symptoms and control
measures. The WAEOs were expected to disseminate the knowledge during enumeration and later
during their routine visits to farmers. A scale of 1 – 4 whereby 1 = Nil (no plants with symptoms,
2 = Mild (< 25% of plants with disease symptoms), 3 = Moderate (25 – 50% of plants with disease
symptoms) and 4 = severe (> 50% of plants with disease symptoms) was used to determined NSD
incidence. NSD severity was determined using a scale of 1 - 4 whereby 1 = Nil, 2 = Mild (<25% of tillers
with disease symptoms), 3 = Moderate (25 – 50% of tillers with disease symptoms) and 4 = severe
(> 50% of tillers with disease symptoms). Farmers with NSD infected elds were advised to uproot
and burn the infected plants to avoid spreading the inoculums. Leaf samples were taken from NSD
infected plants and kept in well labeled paper bags for Disease conrmation through DNA analysis.
Results and Discussion
Survey Areas
The survey was conducted in Tanga and Arusha regions whereby 3 districts including Muheza
and Lushoto (Tanga region) and Meru (Arusha region) were covered. Forty four (44) villages were
sampled, 14 villages in Muheza, 19 villages in Lushoto and 11 villages in Meru districts. A total of
153 respondents were interviewed, 47 respondents in Muheza, 66 respondents in Lushoto and 40
respondents in Meru districts (Fig 4.4.1). The number of households varied depending on size of
district and importance of Napier grass.
Figure 4.4.1: Sampled households in Lushoto, Muheza and Meru districts.
NSD infected area
Among the sampled villages, 19 (43%) were reported to be infected by NSD. The affected villages
were found in Muheza (8), Meru (6) and Lushoto (5) (Table 4.4.1).
Table 4.4.1: NSD infected villages in Muheza, Lushoto and Meru districts
District Sampled villages NSd infected villages % infected villages
Muheza 14 8 57
Lushoto 19 5 26
Meru 11 6 54
Total 44 19 43
44
Figure 4.2.2. NSD infected households in Muheza, Lushoto and Meru districts
NSD Incidences and Severity
Low NSD incidence ranging from 1–2 was found in Muheza and Meru districts while moderate
incidence ranging from 2–3 was found in Lushoto district. In terms of NSD severity, low to moderate
severity ranging from 2–3 was found in Muheza and Meru while in Lushoto the severity was higher
ranging from 3–4. The most severely affected elds were found in Ubiri and Mbuzii villages in
Lushoto district. Among the severely affected led included the Napier Demonstration Plots and
MSc student’s research trials which were established using materials from TALIRI Tanga. In Ubiri
village, the most severely affected elds belonged to farmers who sourced planting materials from
the Demonstration Plots. According to Mbuzii Village Executive Secretary, Mr. Karim Singano, who
is also a leader of Bahati Farmers Group, at least 20 farmers have sourced planting materials from the
Table 4.4.2: Households with NSD infected elds in Muheza, Lushoto and Meru Districts
District No. of sampled
households
Households with NSD
infected elds
% affected households
Lushoto 66 15 22
Muheza 47 14 29
Meru 40 10 25
Total 153 39 25
In comparison to previous survey, the NSD infected area has expanded to cover Lushoto district
which was previously free from the disease. Considering that the disease is resent in Lushoto, the
number of affected villages indicates that the disease is spreading fast and hence a need for immediate
intervention.
Affected households
Among the interviewed respondents, 39 reported to have NSD infected elds. In terms of percentage,
Muheza district had the highest proportion of affected households (29%) followed by Meru district
(Table 4.4.2, Figure 4.4.2). Although Lushoto had slightly larger number of NSD infected households
compared to other districts, in terms of percentage the district had the least proportion of affected
households (22%) probably due to the fact that the disease has recently invaded the area compared
to Muheza and Meru where the disease is reported since 2008 (Pallangyo et al..,2008). However, the
percentage of affected households in Lushoto district is expected to increase due to famer’s tendency
of sharing planting materials. This was witnessed in Ubiri and Mbuzii villages where Farmers
reported to have shared improved Napier grass materials from infected on farm demonstration plot
for Improved Napier grass varieties.
45
Table 4.4.3. Composition of stakeholders who received information on NSD management
District Administrators Extension Ofcers Researchers Farmers
Muheza 2 20 1 50
Lushoto 2 15 2 75
Meru 1 10 60
Total 5 45 3 185
Grand total 238
Demonstration plot and some have been shared with farmers from other villages thereby posing risk
of spreading the disease further.
Current NSD levels in Meru and Muheza districts indicate that although farmers are aware of
recommended management practices, they still exchange planting materials due to lack of reliable
sources of improved planting materials. This has facilitated the spread of NSD to new areas for
example in Akheri village (Meru district) and Tongwe village (Muheza district). One participant of
focus group meeting in Muheza district, Mwalimu Mvungi, informed the participants that despite
following the recommended cultural practices he and other farmers in Mkanyageni village lost their
Napier crop due to NSD and drought stress. Due to lack of reliable source of resistant materials
they had to abandon Napier farming and shifted to alternative crops including maize and cassava
(Muheza district). The SMS dairy at Muheza district Ms. Juliana Swai also informed participants that
the number of small holder dairy farmers has dropped substantially following the occurrence of NSD
in the district.
Public Awareness on NSD management
Public awareness was created through focus group meetings at District LGAs, village meetings and
eld visits. A total of 238 stakeholders including District Executive Ofcers, District Agricultural
Irrigation and Cooperatives Ofcers, District Livestock Ofcers, District Plant protection Ofcers,
Ward Agricultural and Livestock Extension Ofcers, Livestock Researchers, Policy makers and farmers
were reached (Table 4.4.2). The current status shows that the disease is spreading fast into new villages
and districts due to inadequate awareness on control measures and shortage of improved planting
materials. While multiplication of NSD resistant varieties is going on, massive public awareness is
required especially in newly infected areas in order to prevent and control the disease. Decline in
NSD incidence has been witnessed in previously infected areas following intensive public awareness
creation and massive adoption of recommended measures for NSD management (Pallangyo et al..,
2011). Similar approach should be used to avoid further Napier yield losses.
Inspection of Napier Gemplasm in TALIRI
A visit was made in Tanzania Livestock Research Institute (TALIRI) which is located some few
kilometers from Tanga municipal. The Institute had a collection of Napier grass varieties including
Kakamega 1, Kakamega 2, Local and Hybrid which were established in 2011 using materials from
CIAT, ILRI and National Agricultural and Livestock Research Institutes. The collection served the
role of germplasm introduction and evaluation, maintenance of identied forage germplasm, and
multiplication of forage seeds for research and development. In March 2014, Napier grass materials
from the collection were sent to Lushoto district, where they were used in the establishment of on farm
demonstration plots and the MSC student’s trials in Mbuzii and Ubiri villages. According to TALIRI
Livestock Researchers, Mr. Mngulwi, Napier grass materials from the collection have also been used
in establishment of 6 demonstration plots in Babati district. The demonstration trials and Student’s
trials in Lushoto district were found to be infected by NSD during the survey. According to Mbuzii
46
Farmers Group members, NSD symptoms were observed in the demonstration trial in November
2014, after the second cutting. Inspection of Napier collection at TALIRI was done whereby all Napier
varieties were found to be infected (Figure 4.4.13 – 4.4.16) thereby associating the NSD inoculums in
Lushoto with Napier collection at TALIRI, Tanga.
Recommendations
Current NSD levels in Meru and Muheza districts indicate that although farmers are aware of
recommended management practices, framers still exchange planting materials due to lack of reliable
sources of improved planting materials. This has facilitated the spread of NSD to new areas for
example in Akheri village (Meru district) and Tongwe village (Muheza district). The shortage has
also forced some farmers in severely affected areas to abandon Napier farming and shift to alternative
crops some of which are of lower value compared to dairy farming.
To avoid further spread of the disease, farmers are advised to adhere to recommended cultural
practices for NSD management which include uprooting and burning of infected plants and tillers.
The Napier grass materials in TALIRI collection should be destroyed and the area planted with
non NSD suitable host, for example cassava or sweet potato in order to break the disease life cycle.
Arrangements should also be made to enable follow up NSD status in demonstration plots at Babati
district to enable timely intervention. Future introduction of planting materials and any other living
organisms should abide to Phytosannitary regulation as stipulated in Plant Protection Act, 1997 and
Regulations, 1999).
Shortage of improved planting materials and lack of awareness on NSD management have contributed
in spreading NSD in the affected areas for example in Lushoto where the disease was associated
with improved materials sourced from TALIRI demonstration plots. There is a need to speed up
the multiplication and distribution of NSD tolerant varieties at ARI Kibaha to address the shortage.
Intensive public awareness creation is required to enable massive adoption of recommended cultural
practices for NSD management to mitigate negative impact associated with the disease. Capacity of
Extension service also needs to be strengthened through training on NSD etiology, symptoms and
management to ensure sustainability in management of the disease.
References
Pallangyo B, Maeda C, Mkonyi S (2008) Napier grass (Pennisetum purpurium (Sachum)
diversity, uses and diseases in Eastern, Northern and lake zones of Tanzania. In document of the
1st National Plant Protection Advisory Committee Ad hoc meeting held at Sugarcane Research
Institute, Kibaha Tanzania 19th September 2008. Ministry of Agriculture Food Security and
Cooperatives. Dar Es Salaam, Tanzania Pp 38 – 66
Maeda C and Pallangyo B (2010) Field report on Napier stunt Disease baseline survey in
Zanzibar. Ministry of Agriculture Food Security and Cooperatives, Dar Es salaam, Tanzania
B. Pallangyo, J. Kabirizi, M. Mulaa, J. Proud, J. Hanson J, C. Maeda (2011) Napier Stunt
Disease incidence, severity, and management practices in Eastern and Central African region
Presented in ASARECA Livestock and Fisheries Programme Scientic Conference held in
Bujumbura, Burundi 31st October – 4th November 2011
Pallangyo B, Msangi B and Bombo F (2014) Napier grass production systems, diseases and
management practices: With a note on occurrence of Napier Stunt Disease in Mbeya region of
Tanzania. Journal of Agricultural Sciences and Technology: In Press
47
4.5 Status of Napier stunt and smut diseases and farmer management practices in Rwanda
Nyiransengimana E., M. Mutimura, B. Uzayisenga, Nsabimana J. D., Uwimana G., Umunezero O., J.
Mutabazi, P. C. Hitimana and Ebong C.
Rwanda Agricuture Board (RAB), P. Box 5016, Kigali, Rwanda
Introduction
Feed shortage is a major constraint to livestock production in Rwanda. Ruminant production in the
country is predominantly based on Napier grass, natural pastures and crop residues (Mutimura and
Everson, 2011). Napier grass is the most preferred because of high herbage yield (8-30 t DM/ha/yr)
(Kabirizi, 2006); adaptability to low and high altitudes (Boonman, 1993); and multipurpose use options
(Farrell et al., 2002). The potential contribution of the grass to livestock feed in East and Central Africa
is threatened by Napier Stunt and Smut Disease (NSD), which has been reported in neighbouring
countries of Uganda, Kenya and Tanzania (Nielsen et al., 2007). However, the presence and severity
of these diseases has not been conrmed in Rwanda. This study was conducted to determine the
incidence and prevalence of NSD in smallholder dairy systems in the country and assess farmers’
knowledge, perceptions and their coping mechanism to the threat of the diseases.
Materials and methods
The study was carried out in 2013 in 14 districts of Eastern, Kigali City, Northern, Southern and
Western Provinces. The districts lie within three agro ecological zones of the highland (altitude: 1,800
– 2,400m), lowland (Altitude: 900 - 1,400 m) and midland (Altitude: 1600 - 1800 m) that also differed
in temperature and rainfall. Reconnaissance surveys were conducted to identify farms and plants
affected NSD. Disease incidence, prevalence and severity were examined in the selected farms. The
severity of the disease was scaled from 1 to 5, and 5 was considered as very high severity. Structured
questionnaires were administered to 391 dairy farmers to determine level of farmers’ awareness of
NSD. Data were analysed using descriptive statistics.
Results
Household composition
The gender disaggregated household composition and average number persons in each province
are presented (Table 4.5.1). Majority of the male and female farmers were in the age bracket of 11 to
40 years old in all the provinces except in the Northern Province where the majority were 21 to 60
year. Most of the respondents during the survey were male though the proportion varied between
districts (Figure 4.5.1). The highest female respondents were in Gasabo followed by Nyaruguru,
Kayonza and Gakenke districts and this could be partially attributed to the of women empowerment
through education and self-employment, one-cow-poor family (GIRINKA) and the residual impact
of genocide experience.
48
Table 4.5.1: Gender disaggregated household composition (%) and average number of persons (heads per 100
households) by Provinces in Rwanda
Composition Average number of persons/100h’holds
Province Age group Male Female Male Female Total
Eastern <5 21 15 22 16 37
6-10 42 37 57 55 111
11-20 63 60 99 99 198
21-40 60 51 97 74 171
41-60 24 42 36 42 78
>60 14 22 126 24 151
Kigali City <5 20 14 20 27 47
6-10 22 26 38 52 90
11-20 54 46 108 79 187
21-40 40 48 132 70 202
41-60 43 33 43 33 77
>60 14 18 14 18 32
Northern <5 34 24 49 37 86
6-10 42 44 61 63 124
11-20 43 54 58 80 139
21-40 58 72 72 90 161
41-60 48 47 88 53 141
>60 21 22 21 14 36
South <5 31 33 39 40 79
6-10 64 50 230 233 464
11-20 79 68 247 244 491
21-40 70 69 237 95 332
41-60 55 21 194 353 547
>60 21 35 230 217 446
West <5 18 13 20 16 36
6-10 36 22 47 43 90
11-20 55 55 88 86 174
21-40 47 53 67 77 143
41-60 43 49 45 51 96
>60 25 29 25 31 56
Figure 4.5.1: Percentage of male and female headed households in sample districts
during Napier Smut and Stunted disease survey
49
Table 4.5.2: Level of participation of different gender relations in Napier Smut and Stunt
Table 4.5.3: Education levels among dairy households encountered during Napier Smut and
Stunt Disease survey in Rwanda
Relationship Male Female
Spouse 31.3 75.0
Parent 37.5 16.7
Son 6.3 -
Daughter - 8.3
Son-in-law - -
Daughter in law - -
Grand child - -
Hired worker 25.0 -
Others - -
Overall 100.0 100.0
Provinces
Education Level East Kigali City North South West Overall
Adult 0.9 - 2.4 - - 0.8
Grade Certicate 1.7 3.5 2.4 9.1 18.0 6.4
P1 0.9 3.5 1.2 1.0 1.6 1.3
P2 5.2 3.5 1.2 1.0 1.6 2.6
P3 8.7 10.5 4.8 4.0 - 5.4
P4 9.6 3.5 3.6 6.1 3.3 5.9
P5 10.4 17.2 4.8 9.1 4.9 8.5
P6 22.6 17.2 35.7 33.3 21.3 27.6
P7 4.4 3.5 4.8 - 4.9 3.4
P8 4.4 3.5 8.3 3.0 14.8 6.4
S1 0.9 - 2.4 1.0 1.6 1.3
S2 1.7 3.5 2.4 1.0 - 1.6
S3 6.1 3.5 3.6 2.0 3.3 3.9
S4 6.1 - 1.2 3.0 - 2.8
S5 - - 1.2 0.0 4.9 2.1
S6 0.9 - 2.4 - 4.9 1.6
Specialized Training
Post Primary 4.4 6.9 6.0 11.1 - 5.9
Post-Secondary 0.9 - - 4.0 8.2 2.6
Total mean of literate 89.8 79.8 88.4 88.7 93.3 90.1
Despite the high number of male headed households (Figure 4.5.1) only 31.3% of the males were
respondents in the survey compared to 75% of female head of households (Table 4.5.1). In male
headed household, parents of the spouse and hired workers acted as respondents compared self-
participation in the female-headed households. The participation of children (sons and daughter) was
generally low.
Education
The overall literacy rate was generally high across the provinces. The highest literacy was in the
Southern and Northern provinces where the majority reached grade 6 (Table 4.5.3). The reason
increase of literacy could be that the free primary education which promoted by the government
of Rwanda. The other reason is that people educated to post primary level can access alternative
livelihood opportunities to agriculture because of specialized training. Similarly Eastern Province
and Western province had more literacy than in other provinces. The reason could be that they offer
more opportunities for skilled labour than other parts of the country.
50
Housing structure
As a proxy indicator of improved welfare, the survey considered the materials farmers used for house
construction. The majority used iron sheets for the roofs, cement for the oor and brick or stones for
the walls (Table 4.5.4).
Table 1.5.4: Percentage of farmers using different housing structures
Table 4.5.5: Percentage (%) of farmers and number of parcels owned
Structure
Material Roof Wall Floor
Grass 1.5 - -
Iron sheets 69.7 11.6 -
Tiles 28.7 - 1.0
Brick/stones - 40.6 -
Mud - 33.3 -
Wood - 14.0 3.1
Cement - - 55.6
Soil - - 40.1
Others - 0.5 0.3
Land Resource endowment
Provinces
No of parcels Eastern Kigali City Northern Southern Western Overall
<1 - 3.5 - - - 0.3
1 26.7 31.0 16.0 20.5 21.4 22.9
2 48.3 48.3 21.3 25.6 35.7 . 36.8
3 13.8 17.2 24.0 38.5 3.4 21.0
4 7.8 - 20.0 5.1 14.3 10.8
5 3.5 - 16.0 10.3
- 7.1 7.7 55.6
6 - - 2.7 - - 0.7
Total land area (ha) 1±0.2 2±1 3±0.2 3±0.2 3±0.2 2±0.1
Due to population pressure farmers majority of the farmers own more than one parcels of land (Table 4.5.5). In the
Northern, Western and Southern provinces the majority of farmers owned three parcels while in Kigali City none of
the farmers owned more than two parcels.
This is because in most of the dairy farmers outside Kigali City are beneciaries of the GIRINKA (one-
cow-per poor family programme which encourage farmers to look for more land for crop and fodder
production.
Farmers experience with Napier grass varieties and planting
The majority of farmers in all provinces were familiar with only one variety (Umushingiriro= vernacular
name) of Napier grass (Pennisetum purpureum) while 23% in Northern and 29% in Southern were
aware of a second variety (Table 4.5.6). Also more than 80% of farmers planted improved Napier
varieties (French Cameroon) with the highest proportion being in Kigali. A few farmers (5 to 14%)
in the northern, southern, and western provinces planted both improved and local varieties (Table
4.5.6). Majority of the farmers (over 63%) in all the districts use cuttings for planting. Among the
provinces it is only in the northern and southern where 20 to 23% of the farmers use root splits (Table
4.5.6).
51
Table 4.5.6: Napier varieties used
Table 4.5.7: Reasons for planting Napier grass
Provinces
No of varieties Eastern Kigali City Northern Southern Western Overall
1 87.6 88.9 74.4 69.8 93.5 88.8
2 11.5 11.1 23.1 29.2 6.5 18.1
3 0.9 - 2.6 - - 0.8
No. varieties planted 3.4 21.0
Improved 80.5 96.4 76.9 75.3 88.3 80.9
Local 11.5 3.6 9.0 15.1 6.7 10.5
Both - - 14.1 9.7 5.0 8.6
Planting materials used - 0.7
Both 6.1 7.1 15.9 13.7 8.9 10.7
Cuttings 77.2 89.3 63.4 73.2 97.5 73.1
Root Splits 16.7 3.6 20.7 23.2 3.6 16.3
Reasons
Province Priority Status Feeding Erosion Control Sale Mulching Stakes
Eastern 1 91.9 4.5 3.6 - -
2 3.5 77.6 6.9 10.3 -
3 - 10.0 20.0 70.0 -
4 100.0
Kigali City 1 96.4 - 3.6 - -
2 - 64.3 35.7 - -
3 - 50.0 - 50.0 -
4 - - - - -
Northern 1 97.5 1.3 1.3 - -
2 - 60.5 39.5 - -
3 - 60.0 - 40.0
4 - - - 100.0 -
Southern 1 92.8 1.0 6.2 - -
2 - 74.3 25.7 - -
3 - 75.0 - 25.0 -
4 - - - -
Western 1 89.5 - 10.5 - -
2 - 66.7 33.3 - -
3 - - - - -
4 - - - - -
Overall 1 93.3 1.9 4.8 - -
2 1.4 71.0 4.1 22.7 -
3 - 42.9 32.1 7.1 17.9
4 33.3 66.7 - - -
Reasons for growing Napier grass
Napier grass is mainly grown for feeding livestock followed by erosion control in all the provinces
(Table 4.5.7). Use of Napier grass for mulching featured prominently in the second and third priority
in Eastern, Northern and Kigali City provinces. Growing for sale was a conspicuous feature in is
second priority level, especially in Kigali City, Western and Northern provinces.
52
Majority of the farmers in all the provinces reserved land solely for growing Napier grass but the
acreage varied between districts. The majority allocate less than 0.5 acres to Napier grass while 42.1%
of household allocated more than 0.75ha of Napier. Among the districts famers in Gicumbi (82.1% of
households) allocated the smallest area (less than 0.5 ha) while those in Nyamasheke district (56%)
allocated the largest (more than 1.0 ha per household) to Napier grass (Figure 4.5.2)
Figure 4.5.2: Land use pattern (proportion of farmers) for Napier production in selected districts of Rwanda
Figure 4.5.3: The proportion of farmers that recognized specic symptoms of the stunt disease
Sources of Napier grass planting material varied between districts. In Bugesera and Kirehe distrcts,
67.7% obtained planting materials from neighbours while in Rusizi the farmer’s eld contributed
68.6% of planting material. Research institutions played a minimal role as sources of planting material
in Gakenke (20%) and in Nyamasheke (16.1%) while extension workers and NGOs contributed less
than 2%.
Farmers’ awareness about the Diseases
The survey team encountered some farmers who could recognize Napier stunt disease in all provinces
except Kigali City. However, the level of awareness was very low, especially in the southern province,
where only 1% of the farmers could recognize the disease. The disease was new in the country because
the majority (85%) noticed it within the last two years (2011-2013). The main symptoms farmers
associated the disease with were yellowing and stunting (Figure 4.5.3). A small proportion (5%) of
farmers observed that the diseased plants dry and die. These symptoms were conrmed during eld
surveillance where clumps were severely stunted and biomass yield were low. Other symptoms
farmers associate with the disease were pale yellow-green and seriously dwarfed shoots, especially
during after or before harvesting. There was not symptoms of smut disease in all surveyed districts.
This suggested that stunt disease was the only major disease threatening Napier grass.
Napier stunt disease incidence and severity
The severity was scaled from 1 to 5 where scale 5 was considered as being very high. Napier stunt
disease was observed in only 8% (31 elds out of 383) of elds assessed. The highest disease incidences
(35.17%) were in Kirehe district followed by Rwamagana, Kayonza, Nyamasheke and Gasabo with
less than 5% (Figure 4.5.4). The disease was higher in the middle altitude than in the high and low
altitude zones. The severity of the disease was highest in Kayonza and Rusizu followed by Kirere and
Rwamagama (Figure 4.5.4) among other selected districts.
53
Figure 4.5.4: Napier stunt disease incidences (%)
in selected districts of Rwanda
Figure 4.7: Napier stunt disease severity among
selected districts of Rwanda
Napier grass management practices
Weeding is the common practice used to improve the yield of Napier grass and to control the disease
according to respondents in the districts surveyed. Some farmers combined weeding with manure
application while others use a combination of three practices i.e. weeding, manure application and
recommended harvesting methods.
Discussion and conclusion
The demographic structure of Rwanda smallholder dairy household was generally similar. However
family size in southern province tends to be larger than in other provinces. The family size in Kigali
City and Western province tend to be lower than in other provinces. The level of participation of
female farmers was higher than male spouse. Therefore they are likely to be more active in NS
management than their spouse. The majority of the economically active farmers in the dairy are
literate, but highly dominated by primary school leavers. Therefore access to education is a strategy
for creating alternative livelihood opportunities in Rwanda. The housing structures encountered
during the survey proofed that investments in the dairy sector had improved the livelihoods of the
farmers. The per capita landholdings that the farmers declared were higher than expected. In addition
to improved varieties of Napier grass that most farmers use, there are local accessions, which need to
be characterized. The survey conrmed the presence of the Napier Stunt disease in Rwanda for the
rst time but Napier head smut disease was not observed in this study. Most farmers used cuttings
as planting material and the majority source them from neighbours or own farms. The incidences
and severity was greater in the medium altitude zones, especially in Eastern province. The disease
is new in the country and only a few farmers were aware of it. Sole reliance on Napier grass as
a fodder, low awareness and propagation through vegetative cuttings from neighbours and own
farms is likely to enhance the spread of the disease. Therefore there is need for awareness creation
and dissemination of management practices including tolerant/resistant varieties that can control or
minimize the spread of the disease in Rwanda
References
Boonman, J.G., 1993. East Africa’s grasses and fodders: Their ecology and husbandry. Kluwer
Academic Publishers, Dortrecht, Nethelands.pp.343.
Farrell, G, Simons S A and Hillocks R J 2002. Pests, diseases and weeds of Napier grass New
Pennisetum purpureum: A review. Journal of pest management 48 (1) 39-48.
Kabilizi, J. 2006. Improving feed availability and animal performance: incorporating forage
legumes into farming system” Ph, D Thesis Makerere University.
Mutimura, M. and Everson T. M. 2011. Assessment of livestock feed resource-use patterns in
low rainfall and aluminium toxicity prone areas of Rwanda. African Journal of Agricultural Research
6 (15): 3461–3469.
Mutimura, M., Leonidas Dusengemungu, Musana Bernard, D. Gahakwa and Cyprian Ebong
2014. Household characteristics and livelihood strategies in pilot sites for beef enterprise development
in Eastern Province of Rwanda. Journal of Animal and Veterinary Advances 13 (10): 644–651.
Nielsen, S.L., Ebong. C., Kabilizi., J. and Nicolaisen, M. 2007. First report of 16rX group
Phytoplasma (Candatus Pytoplasma oryzae) associated with Napier grass stunt disease in Uganda.
New disease report 14. January 2007.
54
CHAPTER 5: Napier Grass Resource Evaluation
5.1 Evaluation of Napier grass (Pennisetum Purpureum) accessions for dry matter yield,
nutritive quality and tolerance to Napier stunt disease in Uganda
Kabirizi J.1, Mulaa M,2, Zziwa E.3, Mugerwa S.1, Namazzi C.1., Kawube G.4 and Nampijja Z.5
1 National Livestock Resources Research Institute, P.O. Box 96, Tororo, Uganda
2 Kenya Agricultural and Livestock Research Organization, P.O. Box 450-30200, Kitale, Kenya
3 Association for Strengthening Agricultural Research in Eastern and Central Africa, P.O. Box 765, Entebbe,
Uganda
4 National Crops Resources Research Institute, P.O. Box 7084, Kampala, Uganda
5 Makerere University, P.O. Box 7062, Kampala, Uganda
Introduction
It is estimated that 12 to 14% of the world population, or 750 to 900 million people live on dairy farms
or within dairy farming households and production of 1 million litres of milk per year on small-scale
dairy farms creates approximately 200 on-farm jobs (FAO 2010). Smallholder dairy cattle production
in Eastern and Central Africa (ECA) improves food security of milk-producing households, creates
numerous employment opportunities to many resource poor people throughout the dairy value chain
and provides manure for crop production (Njarui et al., 2012).
The success of the smallholder dairy sector in ECA region depends on Napier grass (Pennisetum
purpureum), commonly known as elephant grass (Kabirizi et al., 2006; Orodho, 2006). The grass,
whose herbage dry matter yield ranges between 16 and 30 t/ha/year is the main fodder source grown
by over 80% of smallholder farmers in ECA and contributes 60-80% of the forages fed (Jones et al.,
2007). Some farmers earn cash incomes from selling Napier grass fodder to dairy farmers who have
insufcient land to grow their own feed (Kabirizi et al., 2006).
The major threat to the use of Napier grass fodder is the Napier stunt disease (NSD) caused by 16SrXI
Group phytoplasma (Candidatus Phytoplasma oryzae) (Nielsen et al., 2007; Mulaa et al., 2010).
Studies conducted in Uganda have shown that all Napier grass accessions are susceptible to NSD
(Kabirizi et al., 2010). Affected shoots become pale yellow in colour and seriously dwarfed. Often the
whole stool is affected, with yield reductions of 40-100% and eventual death of the plants (Nielsen et
al., 2007). This has led to increased price of Napier grass in worst affected districts, insufcient feed
for cows and selling off of animals by some farmers.
Efforts to identify resistant/tolerant Napier grass accessions to NSD have intensied in the last 5
years through the Regional Dairy Centre of Excellence (RDCoE) at Kenya Agricultural and Livestock
Research Organisation and the International Centre for Insect Physiology and Ecology (ICIPE) in
Kenya (Mulaa et al., 2010). Some resistant accessions have been recorded (Mwendia et al., 2006 and
Mulaa et al., 2010). These accessions would be evaluated in Uganda and if found suitable, disseminated
to farmers.
Adoption of genetically diverse, high yielding and climatically adapted Napier grass accessions
tolerant to NSD will improve the performance of the dairy sector, alleviate the current feed shortages
and environmental crises associated with NSD. This will contribute to food and nutritional security,
55
social and gender protection, improved incomes, poverty alleviation, environmental sustainability
and sustainable natural resource use in the region. The objective of the study therefore was to evaluate
Napier grass accessions for dry matter yield, nutritive quality and tolerance to NSD.
Materials and methods
Description of study site
The study was conducted at the National Crops Resources Research Institute (NaCRRI), Namulonge
in Central Uganda. Namulonge is located on latitude 00 5’ 320 61’. The area lies at an altitude between
900 and 1340 m above sea level. Namulonge lies in the sub-humid Uganda with a mean annual rainfall
of 1270 mm per year which is bimodally distributed with peaks in March to May and September
to November, while the dry months are January to February and July to August (Figure 5.1.1).
Namulonge has a tropical wet and mild dry climate with slightly humid conditions (average 65%).
Mean annual temperature is 22.2 0C (mean maximum temperature =28.4 0C and mean minimum
temperature = 15.9 0C). The vegetation is wooded savanah with tall trees and tall grasses dominated
by Pennisetum purpureum and Parnicum maximum.
Figure 5.1.1: Monthly rainfall totals for NaCRRI (2012)
Experimental procedure
Twenty two (22) Napier grass accessions acquired from Alupe Research Institute in Kenya were
planted in plots measuring 3m x 3m with intra and inter row spacing of 1.5m at NaCRRI in September
2011. The plots were arranged in a Randomized Complete Block Design replicated three times. The
experimental plots were surrounded with stunt-disease infected Napier grass plants to facilitate
transmissibility of the disease to the healthy Napier grass accessions.
Data collection started two months after planting and the subsequent sampling was done at 8 weeks
intervals. At each harvest, scoring for disease incidence was done based on visual observations on
disease incidence per plot and carried out just before harvesting, using a scale of 1 to 5 where 1 = no
symptoms, 2 = very mild symptoms, 3 = medium mild symptoms, 4 = severe symptoms and 5 = very
severe symptoms. Herbage biomass yield was estimated by cutting fodder at ground level from the
whole plot and weighed. At each time of data collection, the grass was cut back to a height of 5 cm
above ground and left to allow regrowth. Sub-samples of about 0.3 kg of Napier grass fodder were
randomly taken and oven dried at 600C for 72 hours to constant weight. The dried samples were
used for dry matter (DM) estimation and chemical analysis. Samples were analysed for crude protein
(CP), Neutral Detergent Fibre (NDF), Acid Detergent Fibre (ADF) Calcium (Ca) and Phosphorus (P)
contents using methods described by A.O.A.C. (2001).
56
Table 5.1.1: Effect of Napier stunt disease on herbage biomass yield of introduced Napier
grass accessions
Napier grass variety Mean herbage biomass yield for 7 harvests (ton/ha/year)
Kakamega 1 (ILRI 16791) 41.95b
Kakamega 2 (ILRI 16798) 40.4b
112 39.46b
16702 36.81b
97 35.3b
16805 32.3ab
41 29.1a
75 28.0a
105 26.87a
103 26.41a
16814 26.3a
76 26.05a
Kakamega 3 (ILRI 16786) 26.05a
16815 25.75a
79 25.5a
19 24.4a
117 23.52a
16789 23.5a
Alupe Napier Field 22.85a
79Sugarcane+Napier 21.2a
104 17.92a
River Bank 17.05a
SEM 4.66
LSD 13.15
Mean with different superscript in the same column are signicantly different at P<0.05
SEM = Standard Error of the Means;
Based on total accumulated herbage dry matter yield of 7 harvests, Kakamega 1 and Kakamega 2
produced the highest yields compared to all other accessions. The lowest yielding accession was 104
(18.9 t/ha) and River bank (RBN) (17 t/ha).
Napier stunt disease severity among Napier grass accessions
Napier grass accessions signicantly differed in severity and the period taken to show disease
symptoms (Figure 5.1.2).
Analysis of Variance (ANOVA) was carried out using Genstat statistical package 14th edition
and signicantly different means separated using Least Signicant difference (LSD) at 5% level of
signicance.
Results
Effect of Napier stunt disease on herbage dry matter yield
Mean herbage dry matter (DM) yield for 7 harvests (56 weeks) ranged between 16 and 43 t/ha (Table
5.1.1).
57
Figure 5.1.2: Napier stunt disease progress on some of the Napier accessions over time
Some accessions showed disease symptoms as early as after second harvest while others showed
tolerance up to the fourth harvest. The most susceptible accessions were 104, 117, 76, and 79 SN
medium mild symptoms at the second harvest representing 18.2% of the total number of accessions.
At the 3rd harvest, accessions 104 and 117 showed medium mild symptoms while accessions 76, 41,
79, 79SN, 103, and River Bank Napier showed very mild symptoms. By the fourth harvest, 97 which
was among the high yielding promising accessions showed very severe symptoms. Accessions 105,
112, 16702, 16789, 16805, 16815, 19, 75, Kakamega 1, and Kakamega 2 did not show disease symptoms
up to seventh harvest. On the contrary, the accessions which had more disease build-up, on average
had higher biomass (t/ha).
Nutrient composition of Napier grass accessions
The nutrient composition of the Napier accessions differed signicantly (P=0.05). All the accessions
had NDF content ranging between 55.5% (79 SN) and 62.8% (ANF) (Table 5.1.2). The percentage of
crude protein was low, 6.4% (ANF) to 9.2% (79 SN). All accessions had very high dry matter content
ranging from 89.9% to 90.6%.
58
Table 5.1.2: Nutrient content (%) of different Napier grass accessions
Accessions CP (%) DM (%) NDF (%)
103 6.78 90.4 62.5
104 6.8 90.1 60.2
105 8.3 90.4 59.2
112 7.7 90.5 58.2
117 7.6 90.1 58.9
16702 7.4 90.2 58.6
16789 7.7 90.3 60.4
16805 8.0 90.3 60.1
16814 8.5 90.2 58.4
16815 8.4 90.1 58.0
19 7.3 90.4 61.2
41 8.4 90.4 58.2
75 7.4 90.4 61.8
76 6.7 90.3 62.3
79 8.5 90.6 58.5
79SN 9.2 90.0 55.5
97 7.3 90.1 59.0
ANF 6.4 90.3 62.8
Kakamega 1 7.3 89.9 58.8
Kakamega 2 7.3 90.3 59.7
Kakamega 3 7.1 90.3 61.2
RBN 8.9 90.3 56.0
LSD 1.1 0.4 2.1
Discussion
Effect of Napier stunt disease on Napier grass dry matter yield
The signicant differences in dry matter yield (DMY) of Napier accessions could be attributed to
genetic differences (Muyekho et al., 2008; Snijders et. al., 2011) and severity of NSD of the accessions.
The sharp decline in DMY for the 2nd harvest could have been due to the effect of the dry season
since the rst and second harvests were done in November and February, respectively. The low DM
yields recorded in this study could also be attributed to poor soils since no fertilizers were applied
throughout the study time. Masinde et. al. (2012) reported that total dry matter yield of Napier grass-
legume intercrops or Napier grass grown alone signicantly increased when 60 kg diamonium
phosphate per hectare or 5 t FYM per hectare +30 kg diamonium phosphate per hectare was used.
Napier stunt disease severity
The results on tolerance of Kakamega 1 differed from the ndings of Muyekho et al. (2008) who
reported that the accessions succumbed to NSD after the 3rd harvest in Kenya with very mild
symptoms. Kakamega 3 showed disease symptoms by the fourth harvest which results differ from
the ndings of (Muyekho et al., 2008) who reported the same accessions to succumb to the disease
after the rst harvest in Kenya. The difference in the ndings could have been a result of variation in
soil fertility as Napier growing on fertile soils tends to be more tolerant to Napier stunt disease (Mulaa
et al., 2007). Field observations have shown good management practices such as manure application
reduce NSD severity on affected elds and (Kabirizi et al.; 2007; Mulaa et al., 2007).
59
There was an increasing trend in incidence and severity of NSD with number of harvests with the
rst mild symptoms appearing at the 2nd harvest concurring with ndings of Mulaa et al. (2007)
who reported that NSD affects plots that have been cut more than twice. The reason for the increase
in incidence and severity with increased number of harvests could be that when the fodder grass
is harvested, the leaf hoppers that spread NSD tend to move to other plants for survival. When the
plants are regenerating, the leaf hoppers then move back to the young soft and juicier plants thus
spreading the disease.
Nutrient composition of Napier grass accessions
The results on nutritive quality showed that the protein content of Napier grass accessions was
low (6.7-9.2%). The CP levels were below the minimum recommended levels (16%) for production
and maintenance of a dairy cow (NRC, 2001). Forage yield and nutritional qualities of pastures
are inuenced by numerous factors representing genetic, ecological conditions and management
practices (Sarwat et. al., 2002; Lanyasunya et. al., 2006). Those factors include frequency of cutting,
species composition, stage of maturity of plants, climatic conditions, soil fertility status and season
of harvesting. Sarwat et. al. (2002) reported that crude protein content of grasses decreased with
maturity of plants. They further reported that highest CP (7-9.6%) was found to be at vegetative stage
and the maximum decrease in CP was found to be between the owering and mature stage. The low
CP reported in this study could therefore have been partly caused by poor soils since there was no
fertiliser application throughout the study period. Raqul et. al. (2010) reported that application of
approximately 70 kg of biogas slurry N per hectare will improve the production of biomass and nutrient
content in maize fodder. The high NDF observed in this study could have been caused by maturity
of the plants. Nutritive value of forages is greatly inuenced by the growth stage of the forage when
harvested. With advancing maturity, the plant contains low protein and high bre content (Mahala
et. al., 2012). In addition, as the plant matures, the plant cell wall of the stem becomes lignied and
bre becomes less digestible (Van Soest, 1994). Orodha (2006) reported that in East Africa, dry and
wet season inuence the dry matter yield and quality of Napier grass fed to dairy cattle. Van Soest
(1994) noted that second cuttings has lower digestibility than rst cuttings of the same chronological
and physiological age, because plant growth begins at relatively high temperatures, usually after
cutting or when rains ends a dry spell. DePeters and Kesler (1985) also observed that nutritive quality
of forage reduced at the second and third cuttings of permanent pasture harvested as dried forage.
Conclusions and recommendations
This study has shown that Napier stunt disease tolerance exhibited by the accessions such as 105, 16789,
16825, 19 and 75 despite having relatively low yields suggest that these accessions can be very useful
candidates in breeding programmes for resistance against Napier grass stunt disease. Accessions
Kakamega 2, 16805, 112 and Kakamega 1 were among the accessions with the highest DMY and were
tolerant to NSD up to the 7th harvest; therefore the accessions can be grown in NSD “hot spot” areas
as a way to improve feed availability and NSD in an environmentally friendly and cheaper means.
Farmers should be taught and encouraged to carry out specic agronomic management practices such
as; manure application to improve soil fertility, weed control, proper cutting height and frequency
and use of disease free planting materials that reduce the severity of NSD for such accessions to
be disseminated. Sudies are proposed to assess the effect of different locations (a wider range of
soil, rainfall, and temperature combinations); types of manure application and cutting intervals on
severity of NSD.
60
References
AOAC, 1995 AOAC, 1995. Ofcial methods of analyses. Association of Ofcial Analytical
Chemists, 16 ed.
DePeters, E. D., and E. M. Kesler, 1985: Yields and nutritive value of cuttings and permanent
pasture harvested as dry hay forage. J. Dairy Sci. 68, 996—999. Enoh, M.B.; Kijora, C.; Peters. K.J.
and Yonkeu, S, 2005. Effect of stage of harvest on DM yield, nutrient content, in vitro and in situ
parameters and their relationship of native and Brachiaria grasses in the Adamawa Plateau of
Cameroon. Livestock Research for Rural Development 17 (1) 2005.
FAO (Food and Agriculture Organization of the United Nations) 2010 Status of and
prospects for smallholder milk production: A global perspective, edited by Hemme T and Otte T.
http://www.fao.org/docrep/012/i1522e/i1522e0.
Jones, P., Y, Arocha., T, Zerrfy., J, Proud., G, Abebe and J, Hanson. 2007. A stunting
syndrome of Napier grass in Ethiopia is associated with 16SrIII group phytoplasma. Plant pathology
56, 345.
Kabirizi J, Mpairwe D, and Mutetika D, 2006. Effect of intercropping forage legumes with
elephant grass on fodder production in intensive smallholder dairy farms in Uganda. Uganda
Journal of Agricultural Science 2006, 12 (2): 16 -25
Kabirizi, J., Alicai, T., Molo, R., Mutetikka, D. and Musoke, A. 2007. Baseline survey report
on prevalence of Napier stunt disease in Uganda, March 2007. National Crop Resources Research
Institute, Namulonge. Kampala, Uganda.
Kabirizi, J.; Alicai, T.; Molo, R.; Nielsen. S.; Kigongo, J. 2010. Napier stunt disease in Uganda:
Farmers’ perception and effect on fodder yield. In: Thoruwa, C.;Mwangi, M.; Abukutsa-Onyango,
M.; Monda, E. Ndeda, R. Cyiza, B.; Okaka, A.; Kabirizi, Enie, R.O. 2010. African women in Science
and Engineering conference proceedings. A decade into the 21st century; The contribution of
African women scientists and Engineers, 18th - 20th August 2010, Nairobi, Kenya. pp. 149-154.
Lanyasunya, T.; Wang H Rong, Mukisira, E.A.; Abdulrazak, S.A.;and Ayako. W.O. 2006.
Inuence of manure and inorganic fertilizer on yield and quality of Vicia villosa intercropped with
Sorghum almum in Ol-joro-orok, Kenya. Livestock Research for Rural Development 18 (10) 2006.
Masinde A. A. O., M.O. Ojowi, D.M. Mbugua, J.A. Odongo and M.A. Shisya. 2012. Effect of organic
and inorganic fertilisers and their combination on Napier grass dry matter yields in
Mahala, A.G.; , Amasiab, S.O.; Monera . Yousif, A.and Elsadig. A. 2012. Effect of Plant age
on DM yield and nutritive value of some leguminous plants (Cyamopsis tetragonoloba, Lablab
purpureus and Clitoria (Clitoria ternatea). International Research Journal of Agricultural Science
and Soil Science (ISSN: 2251-0044) Vol. 2(12) pp. 502-508, December 2012
Mulaa M, Awalla B, Hanson J, Proud J, Cherunya A, Wanyama J, Lusweti C and Muyekho
F. 2010. Screening Napier grass (Pennisetum purpureum schumach) Accessions for tolerance
to Stunting disease in Western Kenya. South west Kenya. http://www.kari.org/leadmin/
publications/Legume_Project/Legume
Mulaa, M.; Muyekho, F.; Ajanga, S.; Omunyin, E.; Jones, P. and Boa E. 2007. Napier stunting
disease vector identication and containment of the disease on farm. Paper presented during the
3rd Annual International Conference, Moi University, Eldoret.
Muyekho, F.N., Onginjo, E., Lusweti ,C.M., Asaba J. N., Mulaa M. and Kiiya W. (2008).
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Wandera, J. Mutisya, J. M. Nginyi, R, Ngigi, R. Rege, and V. Kirigua. Proceedings of the 10th KARI
biennial scientic conference, 12 - 17 November 2006, KARI Headquarters, Kaptagat Road, Loresho,
Nairobi, Kenya. Volume II, 4 pgs.
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Mwendia, S. W., Wanyoike, M., Wahome, R. G. and Mwangi, D. M. 2006. Farmers’
perceptions on importance and constraints facing Napier grass production in Central Kenya.
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phytoplasma (Candidatus Phytoplasma oryzae) associated with Napier grass stunt disease in
Uganda. New Disease Reports. Volume 14. (http://www.bspp.org.uk/ndr/).
Njarui, M G; Kabirizi, J.M.; Itabari, J.K.; Gatheru, M.; Nakiganda. A.and Mugerwa, S. 2012.
Production characteristics and gender roles in dairy farming in peri-urban areas of Eastern and
Central Africa. Livestock Research for Rural Development 24 (07) 2012
Orodho, A.B, 2006. The role and importance of Napier grass in the smallholder dairy
industry in Kenya. www.fao.org/AG/AGP/AGPC/doc/newpub/napier/napierkenya.htm
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yield and quality of grasses. Pakistan J. of Agric. Res. Vol. 17 No. 2, 2002.
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Ithaca, NY
62
5.2 Epiphytology of Napier head smut disease and progress in the search for tolerant
cultivars
Omayio DO1, JV Muoma1, FN Muyekho1, SI Ajanga2 FN Muyekho1&2 and I Kariuki 3, M. Mulaa4
1 Masinde Muliro University of Science and Technology, P.O. Box 190-50100 Kakamega
2 Kenya Agricultural and Livestock Research Organization (KARI – Kakamega), P.O. Box 169-50100
Kakamega
3Kenya Agricultural and Livestock Research Organization (KARLO, Muguga South), P.O. Private Bag
Kikuyu
4Kenya Agricultural and Livestock Research Organization (KARLO, Kitale), P.O. Box 450-30200 Kitale
Introduction
Napier head smut(Ustilago kamerunensis P. & H. Sydow) is a hemibiotrophic pathogen causing very
signicant biomass losses (25-46%) in Pennisetum purpureum (Farrell, 1998; Farrell et al., 2000; NAFIS,
2012). Across the world, the disease has only been reported in Africa, especially in Eastern Africa
where almost each country in the region has had a case of the disease. In Kenya it’s widespread in the
Central region where over 70% of the smallholder dairy farmers grow the crop (Bayer, 1990; Mwangi,
1994; Staal et al., 1998). A survey by Mwendia et al. (2007) has shown that 62.8% of the farmers in
Central Kenya acknowledge the disease as a challenge to Napier grass production. The Central region
is a high potential market oriented dairy zone second to Rift-valley region (Owango et al., 1998;
Omore et al., 1999). Despite this region’s milk production potential, it’s presumed that the strain of
the pathogen in the area is the most virulent in Eastern Africa or the Country’s cultivars are more
susceptible basing on the high herbage losses comparatively (Kung’u and Waller, 2001; Farrell et al.,
2002b). In a bid to manage this disease, a host plant resistance strategy has been used due to its ease
of adoption and cost effectiveness (Parry, 1990). However, Napier head smut disease has continued
to spread gradually to new areas due to compromised cultural practices that are used in tandem with
the host plant resistance approach to combat the disease in an integrated strategy. This is manifested
by wind and through one of the common practices by farmers - uprooting diseased smutted tillers
and disposing them poorly by the roadsides, thus end up growing voluntarily. This creates natural
reservoirs of the disease which eventually reduces the efcacy of the integrated approach (Mwendia
et al., 2007).
Napier head smut disease, distribution and research
Napier head smut pathogen; Ustilago kamerunensis belongs to the Ustilago Genus, Family
Ustilaginaceae, Order Ustilaginales, Class Ustilaginomycetes and Phylum Basidiomycota (Begerow
et al., 1997; Piepenbring, 2003). This genus contains most species of the smuts of the grasses with
its spores used to distinguish the genera being characterized by smooth verruculose and reticulate
walls (Fischer, 1953; Talbot, 1971). Spores germination in the genus is via a septate promycelium
bearing sporidia that initiates the spread within a host tissue (Vanky, 1987). The genus infects at least
27 genera of angiosperms (Fischer and Holton, 1957). Napier head smut disease is currently a major
concern affecting this vital but comparatively ignored crop (Farrell et al., 2002b). This is based on the
limited research that has been conducted on the disease since it was reported (Farrell et al. 2002a;
Mwendia et al. 2007). Most of the research on the disease is centered in Kenya at KARI-Muguga and
Kakamega with the only research outside the continent having been its molecular characterization by
Arocha et al. (2009) through a collaborative research between ICIPE-Kenya and Rothamsted research
centre in the United Kingdom.
63
In Kenya the entry route of the disease to the country is mapped from West Africa, through Uganda
(1930), Rwanda (1963), Tanzania (1975), and eventual establishment in the country in the 1990s where
it was rst reported in press affecting Central’s Lari division in Kiambu district by Kung’u and
Waller (Farrell, 1998; Farrell et al., 2001; Kung’u and Waller, 2001; Farrell et al., 2002b). Since then, its
distribution within the several divisions of the region has been very notable and logarithmic (Farrell,
1998; Kung’u and Waller, 2001; Mwendia, 2007). This is compounded by some worrying reports of
its occurrence in other parts of the country like; in Rift-valley at Molo and Londiani and the lower
Eastern region at Meru north and south (Lukuyu et al., 2012).
Etiology of the disease
Ustilago kamerunensis, the causative agent of Napier head smut, grows within the plant’s cells and
slowly spreads systemically to the entire plant’s tissues. Its hyphae that are branched with internal
partitions (septate) produce lobed and curved haustoria that form the feeding structures of this parasite
in the host plant. Its ustilospores are sub-globose, slightly attened, thin walled and light brown in
colour with an estimated 5 to 7µm diameter. The spores on media germinate after 8 hours of culture
on media (in vitro) ranging from; tap water agar, malt extract agar to potato dextrose agar (Arocha
et al., 2009). At reproduction the spikelets conne the sori with the ustilospores becoming a black
loosely attached mass for easy dissemination (Farrell, 1998). Because of this, the reproductive capacity
by this systemic pathogen using the host’s resources is quite signicant that it reduces the plant’s
biomass extensively. Thus, affecting directly the importance of Napier grass as feed quantitatively
(Farrell et al., 2002a). This is compounded by its perennial life cycle, where it produces ustilospores
continuously in huge amounts to the soil (Farrell, 1998).
Epiphytology of Napier head smut
Epiphytotics of Napier head smut can be attributed to certain abiotic conditions like; temperature
range of between 5oC and 35oC with an optimum witnessed around 20oC highly favouring the
establishment of this pathogen. Moreover, high relative humidity ranging between 65-90% enhances
the disease’s initiation on susceptible host. This is after successful Ustilago kamerunensis spread from
a sick crop to a health susceptible one that is primarily facilitated by wind transfer of ustilospores.
Secondary transmission of the pathogen is through; animal carrying stuck ustilospores on them,
animal’s waste fed on the smutted crop, clothes of passersby and planting of diseased canes carrying
the pathogen within their tissues (Farrell, 1998; Mwendia et al., 2007; ASARECA, 2010; NAFIS, 2012).
The most susceptible stage of the crop is during the development stage of the buds into shoots (shoot
infection) of a respective cane or when the buds are pushing through the soil. This factor explains
why the disease is so severe in the regrowth of a second crop after the rst harvest due to the many
buds that provide extensive shoots to infect and the damaged stem tissues which also provide entry
points of the pathogen (Farrell, 1998).
Napier head smut symptoms
The disease rstly manifests itself in susceptible hosts through induced premature owering covered
in a black mass of ustilospores (Figure 5.2.1) commonly referred to as the smut. This occurs even in
plants that are below 1.5m height which is not usually the case in health plants that usually ower
in heights above 1.5 to 8 metres depending on the variety of the grass (Farrell, 1998). This visual sign
is later compounded by other severe symptoms up on rst harvest and regrowth inuenced largely
by the levels of susceptibility of the grass type including; slow regrowth after cutting, withering and
chlorosis setting in with gradual browning towards drying and death of the entire stool of the crop
within the subsequent 2-3 cuttings in severe cases (ASARECA, 2010; NAFIS, 2012). Besides the above
primary signs, other secondary characteristics of the disease like; induced dwarng (stems are thinner
64
Progress in the search for tolerant cultivars to head smut disease
The search of tolerant cultivars to head smut disease has been tremendous characterized by new
revelations and insights courtesy of the efforts of funding and technical support by the Eastern Africa
Agricultural Productivity Project (EAAPP). The major focus has been to develop an effective and
sustainable host plant resistance management strategy of the disease. Superior clones development;
in terms of yielding and resisting the disease for farmers is being done while cautious of various
intervening variables that might inuence and probably compromise the identied tolerance or
resistance; top of the list being the genotype-environment interaction effects on plant’s phenotype.
Some of the questions addressed are whether there are resistant/tolerant and high yielding Napier
grass accessions and whether such accessions remain resistant or tolerate when exposed to some of
the abiotic stresses prevalent in the farming systems in Eastern Africa.
Figure 5.2.1: A smutted Napier crop head
Progress in the search for tolerant cultivars to head smut disease
The search of tolerant cultivars to head smut disease has been tremendous characterized by new
revelations and insights courtesy of the efforts of funding and technical support by the Eastern Africa
Agricultural Productivity Project (EAAPP). The major focus has been to develop an effective and
sustainable host plant resistance management strategy of the disease. Superior clones development;
in terms of yielding and resisting the disease for farmers is being done while cautious of various
intervening variables that might inuence and probably compromise the identied tolerance or
resistance; top of the list being the genotype-environment interaction effects on plant’s phenotype.
Some of the questions addressed are whether there are resistant/tolerant and high yielding Napier
grass accessions and whether
and shorter than normal less than 1.5m in height) has been observed in serious cases, characterized by
short internodes with distorted leaves in shape that are reduced in number and size on stools, with an
increased tillering scenario (Farrell, 1998; Mwendia, 2007; NAFIS, 2012).
65
(a) IdenticationofNapieraccessionstoleranttoNapierheadsmutdisease
The management of head smut disease in Eastern Africa region has been for a long time over relied
on the host plant resistance of two varieties Kakamega 1 and 2, since their selection a decade ago as
resistant to head smut disease by Farrell (1998, Mwendia et. al. 2007). This has been largely due to the
ease of implementation and cost effectiveness of the approach (Parry, 1990). However, one factor of
concern has been the narrow pool of resistance genes within the two varieties being used to combat the
disease amidst a likely co-evolving pathogen to survive the plant’s resistance pressure. This concern
has been rife despite the enhancement efforts of the varieties resistance for a sustained management,
using compromised cultural practices, targeted in reducing the amount of initial pathogen inoculum
as explained earlier in the chapter.
One of the limitation in the adoption of Kakamega 1 resistant variety by farmers in Central and
parts of Eastern Kenya is the low leaf-stem ratio compared to the most farmer preferred susceptible
cultivars like Bana grass, French Cameroon and Clone 13. Thus, there is need to widen the genetic
diversity of resistant clones at farm level by screening for more productive and diverse cultivars
with the desired traits such as ability to produce high quality forage (Mwendia, 2007; Awalla et al.,
2010). This is to widen the pool of resistant genes used to manage the disease so as to avert a likely
breakdown of resistance soonest than anticipated.
In order to address the problem effectively, efforts have been made under the Eastern Africa
Agricultural Productivity Project to address the question. The efforts were based on the premise that;
with a very narrow pool of resistance genes provided by Kakamega 1 and 2 varieties, the pathogen
is likely to break down the genes soonest due to co-evolution phenomenon to avoid being driven
to extinction due to unsuitable host-scenario resulting from the resistance in the varieties (Rausher,
2001; Friedman and Baker, 2007).
Three studies aimed at unearthing more tolerant or resistant clones of Napier grass to head smut
were carried out by Omayio et al. (2013a). The rst experiment involved screening of 56 ex ILRI
Napier accessions for resistance against head smut disease through articial inoculation without any
other stress to the treatments in a glasshouse. The second experiment evaluate the eighteen accessions
identied from the rst experiment as being tolerant/resistant to Napier head smut disease (listed
on Table 5.2.1) under cutting and different water stresses also in a glasshouse. The third experiment
analyzed the tissues using microscopic techniques and molecular diagnosis for the presence of the
smut pathogen in the seventeen tolerant accessions identied in the rst study.
The rst experiment identied 18 accessions whose characteristics were as follows: eight of the 18
were least tolerant, two were moderately tolerant and remaining eight were highly tolerant (Table
5.2.1).
66
This was based on their smutting or non-smutting differences under disease challenge. Currently, the
accessions are under eld evaluation in different agro-ecological zones to evaluate their capacities
to handle the disease at such a level. In the second experiment these accessions were subjected to
regular cutting at eight weeks interval and regular or irregular watering without any fertilization to
mimic the damage stress they undergo at farm level. The eight identied highly tolerant accessions
did not show smut symptoms by the 11th ratoon crop (Table 5.2.2).
Table 5.2.1: The eighteen presumed tolerant accessions selected from glasshouse level
screening
Accession Neighbour joining group Origin Presumed Tolerance levels Remarks
16811 USA 1 USA Highly tolerant Not smutted by 11th ratoon
16783 Miscellaneous Tanzania Highly tolerant Not smutted by 11th ratoon
16806 Southern Africa USA Highly tolerant Not smutted by 11th ratoon
16782 East Africa Tanzania Highly tolerant Not smutted by 11th ratoon
16789 Southern Africa Swaziland Highly tolerant Not smutted by 11th ratoon
16800 Southern Africa Zimbabwe Highly tolerant Not smutted by 11th ratoon
16835 Hybrid Unknown Highly tolerant Not smutted by 11th ratoon
16796 East Africa Zimbabwe Highly tolerant Not smutted by 11th ratoon
16805 USA 2 USA Moderately tolerant Smutted at eld level
16902 Hybrid Unknown Moderately tolerant Smutted at eld level
16793 Miscellaneous Cuba Least tolerant Smutted in glasshouse
16808 East Africa USA Least tolerant Smutted in glasshouse
16785 Southern Africa Tanzania Least tolerant Smutted in glasshouse
16787 Southern Africa Swaziland Least tolerant Smutted in glasshouse
16786 Southern Africa Swaziland Least tolerant Smutted in glasshouse
16797 East Africa Zimbabwe Least tolerant Smutted in glasshouse
18448 Unknown Unknown Least tolerant Smutted in glasshouse
16836 Southern Africa Unknown Least tolerant Smutted in glasshouse
67
Table 5.2.2: Smutting proportions of the various screened susceptible accessions
Napier
Accessions
Neighbour Joining
Group
Total Number of
Tillers
Number of Smutted
Tillers
Proportion of
Smutting
Rank
14984 USA 1 92 83 90.22% 1
16821 USA 2 55 47 85.45% 2
15743 USA 2 90 73 81.11% 3
16807 USA 2 103 83 80.58% 4
16621 Miscellaneous 51 39 76.47% 5
16798 S. Africa 44 33 75.00% 6
16818 USA 2 44 32 72.73% 7
16810 East Africa 72 52 72.22% 8
14983 East Africa 47 33 70.21% 9
15357 USA 1 52 36 69.23% 10
18662 Unknown 27 18 66.67% 11
16834 Hybrid 43 28 65.12% 12
18438 Unknown 31 20 64.52% 13
16801 S.Africa 58 36 62.07% 14
16804 S.Africa 74 45 60.81% 15
16794 East Africa 40 24 60.00% 16
16840 Hybrid 28 16 57.14% 17
16813 USA 1 27 15 55.56% 18
16822 East Africa 63 33 52.38% 19
16788 East Africa 41 20 48.78% 20
16792 S.Africa 35 17 48.57% 21
16790 USA 2 25 12 48.00% 22
16802 East Africa 29 13 44.83% 23
16814 USA 2 39 17 43.59% 24
16815 USA 1 41 17 41.46% 25
16839 USA 2 33 13 39.39% 26
16817 USA 2 28 11 39.29% 27
14982 Hybrid 34 13 38.24% 28
Clone 13 Unknown 42 16 38.10% 29
16812 USA 2 29 11 37.93% 30
16799 Miscellaneous 22 8 36.36% 31
16791 S. Africa 42 14 33.33% 32
16809 East Africa 19 6 31.58% 33
16803 S. Africa 29 9 31.03% 34
16816 USA 2 33 10 30.30% 35
1026 Unknown 54 16 29.63% 36
16795 S. Africa 18 3 16.67% 37
16837 Miscellaneous 33 5 15.15% 38
16838 Hybrid 32 1 3.13% 39
68
Accession 16805 and 16902 had no smut symptoms at the glasshouse level for the entire ten ratoons
monitoring, but on eld evaluation they produced some smutted tillers in the highly infected
Murang’a and Kiambu regions of Central Kenya region. All the identied least tolerant accessions
in experiment smutted within the fourth ratoon of screening in the second experiment. This actually
afrms the quantitative nature of the tolerance that involves multiple genes of a plant which are also
involved in the general growth of the plant. As a result, unpredictable effects from the environment
that inuence the plant’s growth consequently affect the tolerance (Pratt et al., 2003).
Analysis of tissues using microscopic techniques and molecular diagnosis of the accessions identied
in experiment 1, revealed pathogen presence in their tissues despite not smutting during the initial
experiment of their selection. The strategy took taken advantage of the 56 ex-ILRI accessions that
had been molecularly characterized and grouped into six neighbour joining groups by Lowe et al.
(2003). Methodology used being the one used by Farrell (1998) but as modied by Mwendia et al.
(2006). The motivation being the variations within the neighbour joining groups; could provide a
fairly new reliable pool of resistance genes through the selected new tolerant accessions to add to
those of Kakamega 1 and 2 in combat of head smut.
(b) Evaluating the possibilities virulent strain emergence with respect to origin of Napier
accessions
Variations on head smut disease severity levels on different zones of Eastern Africa region have been
reported especially in Central Kenya where high herbage yield losses have been witnessed (Kung’u
and Waller, 2001; Farrell et al., 2002a). This report provoked the hypothetical proposition that the
high severity levels on Napier grass in some zones of the region was due to the emergence of a
virulent strain of Napier head smut disease. Further, the fear was magnied by the reports that low
genetic diversity characterized the Kenyan and East African cultivars of the fodder grass. Hence, this
had made them prone to head smut attack due to clonal propagation (Bramwel et al., 2010; Lukuyu et
al., 2012). Coupling this phenomenon was the concern especially in Kenya of the continual spread of
the disease to other parts of the country for instance, the Rift-valley’s Molo-Londiani area and lower
Eastern in Meru North and South (Lukuyu et al., 2012).
Therefore, in such a scenario where a possible virulent strain of a pathogen exists in a region, it
is attributable to certain environmental pressures, top of the list being the intensity of resistance
subjected to the pathogen by the host plants (Rausher, 2001). If the presumption holds according
to Rausher (2001) and Friedman and Baker (2007), the scenario of a plant’s resistance forcing the
pathogen to evolve into a virulent strain is preceded by an initial phase, when the pathogen itself
forces the plant to develop resistance against it rst, through natural selection to limit overexploitation.
Clues about this scenario can be estimated or predicted if the origin of the test materials and the
disease’s temporal and spatial distribution are known. Napier head smut is an African disease; as it
has not been reported elsewhere outside the continent. It was hypothesized in a study by EAAPP that
Napier grass being indigenous to the Zambezi valley in the South African region, a trend could be
established based on origin of the test accessions skewed to or from the Zambezi region. This was in
terms of the proportions of tolerant or resistant accessions that were likely to be selected due to effects
of co-evolution after screening.
The efforts towards addressing virulent strains under the Eastern Africa Agricultural Productivity
Project were based on the premise that; pathogenicity and plant’s resistance inuence the emergence of
each other so that an equilibrium state is attained, where no subject is disadvantaged in an interaction
between a pathogen and host (Rausher, 2001).
69
Therefore, through a study by Omayio et al. (2013a) a study was carried out to determine possibility
of virulent strain emergence by evaluating the tolerant Napier grass’ accessions trend of selection
with respect to their center of origin. The evaluation took advantage of the 56 ex-ILRI accessions
whose respective origins are known (Lowe et al., 2003). The motivation being that the information on
the accessions origins could help establish some possible selection trend to the Zambezi valley region
where Napier grass is considered native (Boonman, 1993). This study revealed that USA 2 and USA
1 neighbour joining groups had the most smutted accessions at 90.9% and 80% respectively. Also,
these groups had the least non-smutted (asymptomatic) accessions at 9.1% and 20% respectively.
The Southern Africa group had the least smutted accessions at 57.1% and the most non-smutted
(asymptomatic) at 42.9%. Further, as observed in Table 2, the top four most smutted accessions came
from the USA 2 and 1 neighbour joining group. Whereas of the least smutted four accessions (Table
5.2.2) non USA 1 and 2 neighbour joining groups’ accessions were observed.
Coupling the above observations, the study also showed that majority of all the selected asymptomatic
(non-smutted) accessions accounting for 55.56% had their origin from Africa (Figure 5.2.2). This
was followed at a far second by those from outside the African continent that accounted for 27.77%
proportion. Moreover, a further analysis of the accessions neighbour joining groups, a selection bias
was observed. The Southern Africa neighbour joining group had majority of its member accessions
selected as asymptomatic against the disease at 35.29% of the total asymptomatic accessions selected.
The South Africa group was followed by East Africa group at 23.53% and the USA 1 and 2 groups
exhibited the least asymptomatic accessions selected at 5.88% each (Figure 5.2.3). Moreover, within
each neighbour joining group still the Southern Africa group exhibited the highest proportions of
asymptomatic accessions at 42.9% (Figure 5.2.4), whereas the USA 1 and 2 had the highest proportions
of smutted accessions within their neighbour joining groups (Figure 5.2.5).
This study clearly focused the conclusions towards the effects of co-evolution discussed earlier, where
the pathogen being an African disease had led to development of resistance in the accessions over
time in a bid to co-exist and limit severe pathogen damage (Rausher, 2001; Friedman and Baker,
2007). This is afrmed in Figure 5 where the phenomenon seems to intensify its effects towards the
Zambezi valley where Napier grass traces its origin (Boonman, 1993). This convergent increase of the
probability of a likely selection of an accession whose origin is closer to Zambezi valley as tolerant is
explained by the East Africa neighbour joining group coming second after the Southern Africa one.
Whereas USA 1 and 2 groups which are relatively far away from the region had the lowest numbers
of tolerant accessions selected (Figure 5.2.6). Such a scenario is worrying as it predicts the interplay
between new virulent strain emergence of U. kamerunensis and selection for resistance against the
pathogen in Napier grass. A scenario likely to be owed to a second phase’s selection pressure on the
pathogen arising from the widespread use of selected resistant accessions against the pathogen to
date.
Figure 5.2.2: Potential effects of co-evolution on the selected asymptomatic (tolerant) Napier
grass accessions in a region biased selection scenario during screening for resistant accessions.
70
Figure 5.2.4: Proportions of asymptomatic versus
symptomatic accessions selected within each neighbour
joining group
Figure 5.2.5: Global chart showing
the Z- region (Zambezi valley)
where napier grass is indigenous
and the proximity of each
neighbour joining group (NJG)
to the region in terms of majority
member accessions’ origin.
Figure 5.2.3: Proportions of asymptomatic
accessions out of the total selected per neighbour
joining group showing the selection orientation
towards some groups in having the largest
number of accessions expressing resistance
selected against the head smut disease.
71
The closest groups as indicated had their highest asymptomatic accessions selected: Southern Africa
group leading with 35.29% followed by East Africa group with 23.53%. The furthest USA 1 and 2
groups with the least each had 5.88% proportion.
(c)Determinationofanefcientscreeningprocedureforresistanceagainstheadsmutinterms
of time and cost
The screening for resistant or tolerant Napier grass accessions against head smut disease has been a
lengthy and costly mainly due to lack of a reference point of selection, on which pathologist can rely
on. This problem was noticed during the lengthy unrened screening protocol that was used by Farrell
(1998) and Mwendia et al. (2006) in selection of two very dependable tolerant varieties Kakamega 1
and 2. They screened for over 40 weeks before they identied tolerant varieties; Kakamega 1 and
2 after 48 and 42 weeks, respectively. Therefore, a study was necessary to aid in the determination
of a critical time line that could rene the screening procedure for resistance against head smut to
reduce the cost involved. Also, to act as reference point in the phytosanitary regulation measures
during Napier clones transfer across various zones by farmers, thus aid in management of the disease
through legislative approach.
Efforts were made through Eastern Africa Agricultural Productivity Project towards determining an
efcient screening for resistance/tolerance to Napier smut disease. This was based on the premise
that; the breakdown of genetically controlled resistance in a species population occurs in a continuous
manner due to variations in the threshold levels of the quality in different individuals of the population
(Freeman and Beattie, 2008). Therefore, if such a breakdown and elimination of susceptible accessions
can be tracked, then a stationary phase is reached where no more accessions succumb to the disease.
The point marking the beginning of the stationary phase can be equated to the reference point that
marks the selection point of tolerant of Napier grass accessions within their population. Therefore, to
achieve this; the selection of asymptomatic accessions and the time line that determines the onset of
the resistance response against the disease was determined through screening of the Napier accessions
by Omayio (2013), using the methodology described by Farrell (1998) but as modied by Mwendia
et al. (2006). The accessions used were the 56 ex-ILRI accessions acquired from ILRI germplasm bank
which had been molecularly characterized by Lowe et al. (2003).
The results revealed the breakdown of susceptible accessions as from week 8 when the rst accession
succumbed. A plot of the total number of accessions screened against time showed a stationary phase
that commenced as from the 21st week, which was characterized by only asymptomatic accessions
(Figure 5.2.6). This 21st week timeline is considered the reference point; as it marked the onset of
selecting the tolerant accessions that did not succumb. Only accession 16836 smutted (produced a
single smutted tiller) after the timeline at the 28th week during the experiment (Figure 6), after the
24th week harvest point. This observation is attributed to the declining soil fertility after the long
monitoring period and cutting stress introduced at week 24 on the accession during its harvesting
that intensied the severity of the disease similar to what had been observed in Napier stunt infected
Napier crop (Orodho et al., 2005). Also, increased tillering capacity among susceptible (smutting)
accessions was observed. This result depicts survival strategy by the grasses whereby they try to
compensate for the damage caused by disease on their tissues by producing more tillers. A similar
case has been observed in sugarcane infected by smut pathogen Sporisorium scitaminae (Dalvi et al.,
2012).
72
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napier grass Pennisetum purpureum in Kenya: Proceedings of the ASARECA/ILRI Workshop on
Mitigating the Impact of Napier Grass Smut and Stunt Diseases for the Smallholder Dairy Sector-
sharing Results: June 1-3, 2010, Addis Abba, Ethiopia.
Barnes, R.F., Nelson, C.J., Moore, K.J. and Collins, M. 2007. Forages: the Science of Grassland
Agriculture, 6th edition. Blackwell Publishers, 792pp.
Bayer, W. 1990. Napier grass- a promising fodder for smallholder livestock production in the
tropics. Plant Research Development 31: 103-111.
Begerow, D., Bauer, R. and Oberwinkler, F. 1997. Phylogenetic studies on nuclear large subunit
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Boonman, J.G. 1993. East Africa’s Grasses and Fodders, their Ecology and Husbandry. Kluwer
Academic Publisher, Dordrecht, Netherlands.
Bramwel, W., Muchugi, A., Mulaa, M., Obonyo, M., Harvey, J., Skilton, R., Proud, J. and
Hanson, J. 2010. Molecular characterization of napier grass germplasm by uorescent labeled
amplied- fragment length polymorphism (FL-AFLP). Proceedings of the ASARECA/ILRI Workshop
on Mitigating the Impact of Napier Grass Smut and Stunt Diseases for Smallholder Dairy Sector-
sharing Results: June 1-3, 2010, Addis Abba, Ethiopia.
Dalvi, S.G., Vasekar, V.C., Yadav, A., Tawar, G.B., Prasad, D.T. and Deshmukh, R.B. 2012.
Screening of promising sugarcane somaclones for agronomic traits and smut resistance using PCR
amplication of inter transcribed region (ITS) of Sporisorium scitaminae. Sugar Technology 14: 68-75.
Farrell, G. 1998. Towards the management of Ustilago kameruniensis H Sydow and Sydow, a
smut pathogen of napier grass in Kenya. PhD Thesis, University of Greenwich, United Kingdom.
Farrell, G., Simons, S.A. and Hillocks, R.J. 2000. A novel technique for measuring biomass loss
in a diseased tussock grass. Tropical Grasslands 34: 118-124.
Figure 5.2.6: Trend of Napier grass
accessions’ selection against time
without cutting back in experiment
one’s screening showing the 21st
and 24th weeks that represent the
critical timeline that marks the onset
of resistance and the harvest point
respectively.
73
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Farrell, G., Simons, S.A. and Hillocks, R.J. 2002a. Ustilago kamerunensis on napier grass in
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Farrell, G., Simons, S.A. and Hillocks, R.J. 2002b. Pests, diseases and weeds of napier grass,
Penisetum purpureum: a review. International Journal of Pest Management 48: 39-48.
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75
5.3 Evaluation of Napier stunt and smut tolerant napier grass clones and alternative
fodder grasses for forage yield in Kenya
F.N. Muyekho1&2, J.W. Munyasi2, S. Mwendia3, E.O. Auma4, L. Ngode4, S. Ajanga2, L. Okitoi2 and
P. O. Mudavadi2
1 Masinde Muliro University of Science and Technology, P.O. Box 190-50100 Kakamega
2 Kenya Agricultural and Livestock Research Organization (KARI – Kakamega), P.O. Box 169-50100
Kakamega
3 Kenya Agricultural and Livestock Research Organization (KARLO, Muguga South), P.O. Private Bag
Kikuyu, email
4 University of Eldoret, P.O Box 1125-30100 Eldoret
Introduction
Napier stunt disease is the main limiting factor to Napier grass production in the east Africa region.
Through the Eastern Agricultural Productivity Programme (EAAPP), Napier grass clones and
alternative fodder grasses tolerance to Napier stunt disease and Napier head smut disease were
identied (Wamalwa 2003 and Omayio 2003). However, for proper utilization of the fodder, there
is need for adequate information on its biomass yield, which is currently lacking.. If found suitable,
these fodder grasses will increase feed availability and thus, reduce the impact of the diseases to the
livestock industry. Therefore, the objective of the study was to determine biomass production of the
recently identied tolerant NSD and smut disease Napier grass and alternative fodder grass species.
Materials and methods
The study was conducted at KALRO Kakamega (high rainfall area), Alupe (low rainfall area), Muguga
(high rainfall) and Katumani (low rainfall) regions of Kenya. Experiment 1 was setup at KALRO
Kakamega to evaluate yield attributes of Napier stunt disease tolerant Napier grass clone cv. Ouma,
South Africa, Brachiaria var. Mulato 1 and the susceptible Bana grass. Experiment 2 was setup at
KARLO Kakamega and KARLO Alupe to evaluate yield attributes of two alternative fodder grasses,
Guinea grass (Panicum maximum Jacq) and Guatemala grass (Tripsacum laxum Scrib and Merr)
and Napier cv. Ouma 3.While Experiment 3 evaluated nine (9) ILRI Napier grass accessions tolerant
to Napier head smut disease (16806, 16837, 16783, 18448, 16790, 16835, 16809, 16796 and 16808) at
KARLO Muguga and KARLO Katumani. At both sites, a positive check - Kakamega 1 was included.
The experiments were setup in randomized complete block design. Napier grass was planted at a
spacing of 1 m by 1 m to maintain optimum plant density (Muia et al. 1999). Fertilizer was applied at
the rate of 60kg/ha of P2O5 top-dressed with 100 kg of CAN.
Biomass yield was determined by hand clipping internal stools at an interval of 8 weeks for Napier
grass and 4 weeks for Panicum and Guatemala grass, respectively while leaving out the outside rows.
The samples were oven dried at 60 0C for 48 hours to determine percentage dry matter. Statistical
analysis was done using the statistical analysis system (SAS). The data were subjected to analysis of
variance (ANOVA) and the means were separated using Duncan’s Multiple Range Test (DMRT) at
the 5% level of signicance
76
Table 5.3.2: Dry matter yield of selected alternative fodder grasses and, Napier stunt
disease and smut disease tolerant clones at KARLO Kakamega and KARLO Alupe in
western Kenya
Forage species Mean yield (tha-1year-1)
KARLO Kakamega KARLO Alupe
Napier 26.09a 25.43a
Guatemala 15.36b 12.68c
Panicum 14.71c 13.45b
Mean 18.72 17.19
CV% 5.6 3.6
LSD0.05 5.73 3.37
Within a column, means marked by different letters are signicantly different at p<0.05 signicance
level; Source: Munyasi (Unpublished data)
The ndings on tolerant Napier stunt clones on the basis of dry matter yields suggest that Napier
grass cv Ouma and South Africa have the potential of being an alternative fodder to the current
susceptible farmer preferred varieties of Bana grass, Clone 13 and French Cameroon, while Panicum
maximum can be an alternative to Napier grass in the event that there are no long term tolerant
Napier grass clones.
For the Napier clones tolerant to head smut disease, accession 16809 produced 23─52% more biomass
yield than 16808, 16790 and 16837 in either of the sites while 16790 on overall yielded the least at both
sites (Figure 5.3.1). The differences in the accessions 16809 and 16790 at Katumani of about 7.4 t/ha
of DM is capable of feeding a cow (taking about 15 kg DM per day) for an extra 16 months. This is
an appreciable difference in smallholder farms where at least 35% of costs in a dairy enterprise go to
feeding (Lukuyu et al., 2012). Accessions 16790 and 16837 had high leaf to stem ratio than accessions
16809 and 16790 (Simon Mwendia personal communication). Cultivar 16796 had higher neutral
Table 5.3.1: Dry matter yields of Napier stunt disease and smut disease torelant at KARLO
Kakamega in western Kenya
Napier grass/alternative fodder grass DM Yield (t/ha)
Year 1 (4 Harvests) Year 2 (4 harvests)
Ouma 28.54a 23.21a
Bana grass 33.78a 18.87c
South Africa 32.79a 24.37b
Brachiaria var. Mulato 1 18.93b 7.43d
Source: Muyekho (Unpublished data)
Results and Discussion
Results of the experiments are presented in Table 5.3.1, 5.3.2 and Figure 5.3.1. In all the three
experiments, signicant differences (p≤0.05) were observed in cumulative biomass yield. The Napier
stunt tolerant clones cv. Ouma and South Africa produced dry matter yields that were not signicantly
different from the susceptible farmer preferred Bana grass, while Brachiaria var. Mulato 1 produced
signicantly lower yields at KARLO Kakamega (Table 5.3.1). An evaluation of Napier stunt disease
tolerant Napier grass clone cv. Ouma against the tolerant alternative fodder grass showed that cv.
Ouma produced signicantly (P<0.05) higher yields than Panicum maximum and Guatemala grass
at both high and low rainfall areas. However, Panicum maximum produced signicantly higher dry
matter yields than Guatemala grass (Table 5.3.2).
77
Figure 5.3.3: Napier grass cumulative dry matter yields from six harvests at eact
References
Lukuyu B, Gachuiri CK, Lukuyu MN, Lusweti C, Mwendia S. (2012) ‘Feeding dairy cattle in
east Africa.’ (East Africa Dairy Development Project, Nairobi: Kenya)
Muia JMK, Tamminga S, Mbugua PN and Kariuki JN (1999). Optimal stage of maturity for
feeding Napier grass (Pennisetum purpreum) to dairy cattle in Kenya. Tropical grasslands 33:182-190
Omayio, D. 2013. Resistance of Napier grass Pennisetum purpureum accessions to head
smut pathogen Ustilago kamerunensis. Masters Thesis, Masinde Muliro University of Science and
Technology. Kakamega, Kenya.
Orodho, B.A. 2006. The role and importance of napier grass in the smallholder dairy industry
in Kenya. www.fao.org/AG/AGP/AGPC/doc/newpub/napier/napierkenya.
Wamalwa N. W. (2003). Screening for resistance in Napier and other forage grasses to Napier
stunt disease. MSc Thesis. Masinde Muliro University of Science and Technology. 85p.
detergent bre (NDF) than the others (Simon Mwendia personal communication). Based on yield and
NDF, cultivar 16809 would be preferable in the low rainfall area than the other cultivars in the study.
From the foregoing, Napier grass is still the best fodder for livestock feeding. Napier grass clones cv
Ouma and South Africa are high yielding, as such should be promoted among farmers. However,
in areas highly infested with Napier head smut disease, Cultivar 16796 should be recommended to
farmers. In situations where Napier grass is not available, Panicum maximum can be a good a good
substitute.
78
5.4 Screening Napier accessions for resistance/tolerance to NSD using the loop mediated
isothermal amplication of DNA (LAMP)
Wamalwa N.I. E1, Midega C.A.O2, Ajanga S3, Omukunda N. E1, Ochieno M.W. D1, Muyekho F.N1,3,
Mulaa M4, Zeyaur R. K2
1 Masinde Muliro University of Science and Technology, P.O. Box 190-50100 Kakamega,
emaiemily_wamalwa@yahoo.com, omukundaelizabeth@gmail.com, dwochieno@yahoo.com
2 International Centre of Insect Physiology and Ecology (ICIPE–Mbita), P.O. Box 30-40305 Mbita, Kenya,
email cmidega@mbita. icipe.org, zkhan@icipe.org
3 Kenya Agricultural Research Institute (KARI – Kakamega), P.O. Box 169-50100 Kakamega
emails_ajanga@yahoo.com, fnmuyekho57@gmail.co
4 Kenya Agricultural Research Institute (KARI – Kitale), P.O. Box 450-30200 Kitale,
email margaretmulaa@yahoo.com
Introduction
Napier grass (Pennisetum purpureum Schumach) (Poaceae) is an important fodder crop grown in
Kenya and, East and Central Africa (Abate 1992; Muyekho et al., 2003) and is associated with intensive
and semi-intensive livestock production systems for milk and meat (Kabirizi et al. 2007). It is also
used by more than 53, 000 farmers in eastern Africa as a trap plant for the management of cereal stem
borers (Midega et al. 2013). Additionally, it serves as a wind break in maize elds and stabilizes soil
by holding particles together thereby preventing soil erosion (Jones et al. 2004; Mulaa et al. 2004; Cook
et al. 2007; Khan et al. 2008). Surplus Napier grass is a source of income to smallholder farmers to cater
for school fees and household needs (Kabirizi et al. 2007). Napier grass has advantages over other
grasses because of its high yielding capacity and ease of propagation, and management within a wide
ecological range (0 < 2,000m ASL) (Orodho 2006). It has so far become the most important fodder for
cut-and-carry especially in Kenya, where it is mainly propagated through cuttings (Humphreys 1994).
In recent years, a disease associated with stunting, causing overall loss in biomass and death of Napier
grass has been reported in Kenya, Uganda, Tanzania and Ethiopia (Jones et al. 2004, 2007). The disease
known as Napier Stunt Disease (NSD) is caused by the phytoplasma Candidatus phytoplasma oryzae
belonging to the 16SrXI group, is transmitted through infected planting materials (Jones et al. 2004).
Symptoms expressed by phytoplasma-infected plants include small chlorotic leaves, proliferation
of tillers, and shortening of internodes to the extent that clumps appear very stunted, ultimately
resulting in death of the plant (Ajanga 2005). In Kenya, symptoms of Napier stunt disease were rst
identied in the western in mid 1990s. The disease currently affects up to 90 % of Napier plants in
smallholder farms of western Kenya (Mulaa and Ajanga 2005), and has spread to central and rift
valley provinces of Kenya. The dairy sector in eastern and central Africa is now under threat of this
disease (Nielsen et al. 2007). A signicant reduction in milk output has been reported in areas ravaged
by the disease, and has led to decline in household incomes (Khan et al. 2014). The current mitigation
strategies that include use of fertilizer, rouging and careful visual selection of planting material are
not effective in controlling this disease. The objective of this study was to select Napier plants with
resistance/tolerance to the NS-Phytoplasma among ILRI accessions (Muyekho et al. 2006) and local
clones that did not develop disease symptoms in a eld screening trials at Alupe, Kenya Agricultural
Research Institute (KARI) farm (Mulaa et al. 2012); using the Loop-Mediated Isothermal amplication
of DNA (LAMP).
79
Materials and methods
Napier grass accessions and preliminary screening for phytoplasma
Napier grass varieties/accessions used in the study included ILRI accessions (Muyekho et al. 2006)
and those clones that did not develop disease symptoms in a eld screening trials at Alupe, Kenya
Agricultural Research Institute (KARI) farm (Mulaa et al. 2012). Table 1 gives the lists of accessions
screened for resistance/tolerance to stunt disease, their source of origin and potential dry matter yields.
These accessions were grown at same time in a screen house at icipe. One plant was planted in each
pot and each accession was replicated three. Preliminary Loop mediated isothermal amplication of
DNA (LAMP) screening was carried out on plants in the three replicates of all the Napier accessions
to determine their phytoplasma status. Leaves were systematically sampled from the three replicates
of each accession and their respective total plant DNA extracted using the CTAB procedure adapted
from Doyle and Doyle (1990). Leaf samples weighing 0.3g were powdered in liquid nitrogen and
DNA extracted based on Doyle and Doyle 1990. The DNA was taken through the LAMP procedure
as described below by Obura (2011) to determine presence or absence of Ns-Phytoplasma.
80
Table 5.4. 1: Napier grass accessions, locality of origin and Dry matter yield recorded in Kenya
Napier accession Country or
locality of origin DM yield
(t/ha) Source of information
Gold coast Ghana West
Africa 19.83 Muyekho et al. 2006
French Cameroon Cameroon 21.67 Muyekho et al. 2006
Cameroon 4E Cameroon 17.97 Muyekho et al. 2006
Congo Kinshasa Republic of Congo 13.53 Muyekho et al. 2006
Ex-Nigeria Humid west-
Central Africa 17.13 Muyekho et al. 2006
Uganda hairless Uganda 11.63 Muyekho et al. 2006
Uganda L11 Uganda 17.83 Muyekho et al. 2006
Uganda border Uganda 19.23 Muyekho et al. 2006
ILRI 15743 Mott USA - Lowe et al. 2003
Clone 13 Kitale, Kenya 21.90 Muyekho et al. 2006
Nairobi L8 Nairobi, Kenya 19.47 Muyekho et al. 2006
Nairobi L9 Nairobi, Kenya 12.5 Muyekho et al. 2006
Muguga bana Muguga, Kenya - Muyekho et al. 2006
Ex-Bakole Unknown 16.3 Muyekho et al. 2006
Ex-Matuga Unknown 19.0 Muyekho et al. 2006
Ex-Mariakani Unknown 9.53 Muyekho et al. 2006
Ex-South Africa L4 South Africa 11.47 Muyekho et al. 2006
Ex-South Africa L13 South Africa 22.30 Muyekho et al. 2006
Ex-Malawi Malawi 15.80 Muyekho et al. 2006
Pakistan hybrid Unknown 12.3 Muyekho et al. 2006
ILRI Acc. 16621 (N16621)* Namibia - Lowe et al. 2003
ILRI Acc. 16791 (N16791)* (Kakamega 1) Swaziland 23.83 Muyekho et al. 2006; Lowe et al. 2003
ILRI Acc. 16837 (N16837)* Unknown 14.0 Muyekho et al. 2006; Lowe et al. 2003
ILRI Acc. 16812 (N16812)* USA - Lowe et al.
ILRI Acc. 52503 (N52503)* Gold Coast 14.43 Muyekho et al. 2006; Lowe et al. 2003
ILRI Acc. L16 (L16)* Unknown 17.53 Muyekho et al. 2006
ILRI Acc. 16785 (N16785)* Tanzania - Lowe et al. 2003
ILRI Acc. 16484 (N16484)* Unknown - Lowe et al. 2003
ILRI Acc. 16805 (N16805)* USA - Lowe et al. 2003
ILRI Acc. 16804 (N16804)* USA - Lowe et al. 2003
ILRI Acc. 16792 (N16792)* Mozambique - Lowe et al. 2003
ILRI Acc. 16815 (N16815)* USA - Lowe et al. 2003
ILRI Acc. 16814 (N16814)* USA - Lowe et al. 2003
ILRI Acc. 16794 (N16794)* Mozambique - Lowe et al. 2003
ILRI Acc. 16822 (N16822)* Malawi - Lowe et al. 2003
ILRI Acc. 14984 (N14984)* Unknown - Lowe et al. 2003
ILRI Acc. 16803 (N16803)* Zimbabwe - Lowe et al. 2003
ILRI Acc. 16789 (N16789)* Swaziland - Lowe et al. 2003
ILRI Acc. 16702 (N16702)* Unknown - Lowe et al. 2003
ILRI Acc. 16817 (N16817)* USA - Lowe et al. 2003
ILRI Acc. 16787 (N16787)* Swaziland - Lowe et al. 2003
ILRI Acc. 16808 (N16808)* USA - Lowe et al. 2003
ILRI Acc. 16807 (N16807)* USA - Lowe et al. 2003
ILRI Acc. 16840 (N16840)* Unknown - Lowe et al. 2003
81
ILRI Acc. 16809 (N16809)* USA - Lowe et al 2003
ILRI Acc. 15743 (N15743)* cv.Mott - Lowe et al 2003
ILRI Acc. 16822 (N16822)* Malawi - Lowe et al 2003
ILRI Acc. 16798 (Kakamega 2) Zimbabwe 20.8 Muyekho et al. 2006; Lowe et al. 2003
ILRI Acc. 16786 (N16786)* (Kakamega 3) Swaziland 22.83 Muyekho et al. 2006
ILRI Acc. 16838 (N16838)* Unknown 6.8 Muyekho et al. 2006
ILRI Acc. 16811 (N16811)* USA - Lowe et al. 2003
ILRI Acc. 16836 (N16836)* Unknown - Lowe et al. 2003
ILRI Acc. 18438 (N18438)* Unknown - Mulaa et. al. 2012
Bgm3(b)31 Local variety - Mulaa et. al. 2012
Bgm 76 Local variety - Mulaa et. al. 2012
Btr89 Local variety - Mulaa et. al. 2012
Btr23 Local variety - Mulaa et. al. 2012
Bgm1(A)10 Local variety - Mulaa et. al. 2012
Bgm3(A)16 Local variety - Mulaa et. al. 2012
BSA105 Local variety - Mulaa et. al. 2012
Btr86 Local variety - Mulaa et. al. 2012
Bgm20 Local variety - Mulaa et. al. 2012
Bgm3(B)28 Local variety - Mulaa et. al. 2012
BSA60 Local variety - Mulaa et. al. 2012
BSA31 Local variety - Mulaa et. al. 2012
BSA112 Local variety - Mulaa et. al. 2012
* Refers to coding used in Wamalwa (2013) MSc thesis
Rearing of the healthy insect vector
The insect vector Maiestas banda used in the study was obtained from the rearing screen house at
icipe. These insects colony had been collected from clean Napier elds in 2007 using sucking machine,
counted and introduced into the insect in wooden cages measuring 45cm x 45cm x 60cm high and
surrounded with a 0.25mm netting material cages. They were reared on pearl millet. The top of each
cage was covered with the net. The bottom of the cage was reinforced with a three-ply wood which
supported potted plants. One side (front) of the cage was fastened with hinges to allow potted plants
placed in and watered. These cages were placed on a bench 1.5m high. The bench’s supports rested
in plastic containers with soapy water (mots). These stopped ants from accessing the cages (Obura et
al. 2009). The tness of the vector to transmit disease in the screen house was maintained by frequent
introduction of 25 males and 25 females eld collected M. banda into the rearing cages to mate with
the cultured insects after every two months ve times in a year. In preparation for inoculation set
up, fty gravid M. banda were transferred into insect cages with diseased Napier grass var. Bana
(conrmed by PCR and LAMP) in a separate screen house and set up for 30 days for the insect to
acquire the phytoplasma by acquisition feeding.
Esatblishment of the accessions in the cages and introduction of Insect vector for transmission
of the phytoplasma
Twenty three Napier accessions were multiplied by planting 12 stem cuttings per accession in 500
ml cups, consisting of fertile sterilized black cotton soil. The plants grown in a screen house for 50
days and were watered once daily. At 50 days of growth, six plants per accession were introduced
into two of the already set up inoculation cages in a separate screen house, each with a one month
set up of diseased plant (conrmed by PCR and LAMP) and fty gravid female M. banda allowed
to sufciently acquire the stunt phytoplasma (acquisition feeding). The diseased plant was placed
at the centre of the cage surrounded by 6 healthy phytoplasma free potted plants (Figure 5.4.1). For
82
each accession there were 12 replicates planted in a randomized complete block design. The vector
was used as inoculum carrier to infect the test plants following the protocol described by Obura et al.
(2009). The vector was allowed to feed back and forth for a period of one month feeding to sufciently
transmit the Napier Stunt Phytoplasma to the healthy plants. Occasionally the insects were disturbed
in the inoculation cages to redistribute the population. After 30 days, the inoculation setup was
terminated and the exposed plants transferred to a separate screen house for phytoplasma testing
and disease symptoms expression. The grasses were tested monthly until symptoms appeared. This
involved taking leaf samples of the plants for phytoplasma testing through the LAMP procedure. The
period taken for the plant to express the symptoms was taken as an indicator of the ability of the plant
to tolerate the disease. The controls were not inoculated with the Ns-phytoplasma.
DNA Isolation from inoculated plants
Thirty day old re-growth leaves from the plants in the screen house were sampled systematically
and placed in well labeled 1.5 mL reaction tubes. DNA was extracted using methodologies adapted
from Doyle and Doyle (1990). Samples of 0.3g of the leaf were powdered in liquid nitrogen and DNA
was extracted by adding 600 µL of Chloroform: Iso-amyl alcohol solution (24:1) and centrifuged at
4000 rpm for 10 minutes. The DNA was precipitated by adding 600µL of ice cold Iso-propanol to the
aqueous isolate and incubated at -20˚c for 2 hours. The samples were centrifuged at 14,000 rpm for 30
min and the DNA pellet was rinsed in 1000µl of 70% alcohol. The DNA pellet was then dried at room
temperature for two hours and then suspended in 50 µL of double distilled water(ddH2O) providing
a ready DNA template that was used in the LAMP process (described below)extracted based on
Doyle and Doyle (1990) procedure.
LAMP screening
The DNA isolated above was used in the LAMP protocol to amplify the 240 bp 16S gene segment
(Obura et al. 2011).The LAMP screening was at two levels; a) before inoculation (Preliminary LAMP
screening) where-by the phytoplasma status of the test plants was conrmed according to the
protocols described in Obura et al. (2011) and b) after inoculation where-by all materials inoculated
with the Ns-phytoplasma were screened for detection of the presence of the Ns-phytoplasma. In both
cases total plant DNA templates were taken through LAMP procedure as described by Obura et al.
(2011) but the volumes of the master mix was modied to 11.9 µL of distilled de-ionized water, 2.5 µL
of 10x buffer, 2.5µL of dNTPs, 4.0µL of 4M Betain and 1.1 µL of primer mix.
Inoculation of Napier plants with the Ns-phytoplasma
The plants that were free of phytoplasma at the preliminary LAMP screening level were planted in an
insect cage measuring 45cm x 45cm x 60cm. A diseased plant (conrmed by LAMP procedure) was
placed at the centre of the cage surrounded by 6 healthy phytoplasma free potted plants (Figure 5.4.1).
For each accession there were 12 replicates. The vector was used as inoculum carrier to infect the test
plants following the protocol described by Obura et al. (2009). Then fty gravid female M. banda
insects from colony rearing cages in the screen house were introduced into each inoculation cage and
allowed to feed back and forth for a period of one month for acquisition feeding to allow the insects to
sufciently acquire and transmit the stunt phytoplasma (acquisition feeding). Occasionally the insects
were disturbed in the inoculation cages to redistribute the population. After 30 days, the inoculation
setup was terminated and the exposed plants transferred to a separate screen house for phytoplasma
testing and disease symptoms expression. The grasses were tested monthly until symptoms appeared.
This involved taking leaf samples of the plants for phytoplasma testing through the LAMP procedure.
The period taken for the plant to express the symptoms was taken as an indicator of the ability of the
plant to tolerate the disease. The controls were not inoculated with the Ns-phytoplasma.
83
Figure 5.4.1: Arrangement of potted Napier plants in experimental cages during inoculation. The middle plant
is the source of inoculum. The six plants surrounding it get inoculated by 50 insect vectors (Maiestas banda)
Evaluation of symptom expression
The plants were monitored for disease presence based on leaf symptoms after the rst cut back (30
days after terminating the inoculation). The plants were scored using the disease response rate to
show levels of tolerance. This was done on the rst re-growth (two months of incubation), second re-
growth (three months of incubation) and the third re-growth
Evaluation of symptom expression
The plants were monitored for disease presence based on leaf symptoms after the rst cut back (30
days after terminating the inoculation). The plants were scored using the disease response rate to
show levels of tolerance. This was done on the rst re-growth (two months of incubation), second
re-growth (three months of incubation) and the third re-growth (four months of incubation) at an
interval of 30 days each.
Evaluation of the effect of NSD on plant yield parameters
The study on the effect of the Ns-Phytoplasma on the Napier grass yield was carried out on eight Napier
accessions which were carefully selected based on their unique response to the disease (based on both
LAMP and symptom development).These Napier accessions included; Nigeria 14 (Napier accession
that was 100% susceptible to the Ns-phytoplasma), Bungoma 20 and N15743 (Napier accessions that
lost 100% of their plant population after the second month of incubation), N16808 (with 63.64% of
plants symptomatic yet 91.91% of its plant population negative of the Ns-phytoplasma by LAMP by
the third month of screening),N16807 (that indicated tolerance), N16789 (that indicated resistance)
and N16812 (had symptomatic plants that reverted to asymptomatic from rst re-growth to second
re-growth). The yield related parameters that were studied for these Napier accessions were the effect
of the Ns-Phytoplasma on plant height, leaf length and leaf width.
Plant height was measured using a tape measure from the soil surface to the tip of the youngest
growing leaf. Similarly leaf length was measured from the petiole end (excluding the petiole) to the
tip (Karimi et al. 2009) of two of the longest leaves per plant using the tape measure, and an average
taken for the scores of each individual plant in inches. On the other hand measurements of the leaf
width were carried out on the two longest leaves and an average taken for the score per plant using a
ruler and was scored in centimeters.
84
Figure 5.4.2: A set up for collecting honeydew of Maiestas banda (adopted from Khan and Saxena 1984)
Data analysis
Data were analyzed using SAS software (Version 9.1). The percentage of plants that tested positive
of phytoplasma by LAMP was generated by proc freq. Percentage of plants that developed Napier
stunt disease symptoms was generated in a similar manner. The scores for LAMP results, symptom
development and the death of plants were analyzed using correlation analysis in proc corr. The
analysis of data on plant growth parameters (leaf length, leaf width and plant height) was done by
one-way Analysis of Variance (ANOVA) and single tailed t-tests. Means having signicant differences
were separated using Turkey’s Studentized Range Tests.
Assessment of Maiestas banda’s feeding behavior on the resistant Napier accession
The feeding behavior of the vector on the resistant Napier accession was evaluated using a technique
developed by Khan and Saxena (1984). Four stem cuttings of Napier accession N16789 were grown
in plastic pots separately as well as four stem cuttings of the Bana variety of Napier that was used as
the control in this study. When the seedlings were 14 days old, they were removed without damaging
their roots and washed thoroughly to remove soil particles. Each of the plants was then immersed in
an aqueous solution of 0.2% safranine for 4 hours. The translocated dye coloured the xylem vessels
red throughout the entire length of the seedlings. The treated seedlings were removed and excess
dye washed off. Each single plant from each Napier cultivar was placed in a separate 250-ml beaker
containing enough water to immerse the roots of the plant. Each beaker was covered with a medially
perforated, 12.5 cm Petri dish through which the seedlings emerged (Figure 5.4.2). A 10.8 cm diameter
Whatman lter paper disc was placed on each Petri dish around the base of the seedling and the
seedling and the Petri dish were enclosed in a plastic bottle 10.5 cm width and 26.2 cm height, covered
by an insect netting to allow air in. Fifteen gravid female M. banda which had been starved for one
and a half hours were introduced in each set up and allowed to feed overnight. The honey dew
excreted by the leaf hoppers dropped on the lter paper and was readily absorbed. The lter papers
were treated with 0.1% ninhydrin-acetone solution, oven dried for one hour at 40˚C and the area
marked by bluish amino acid spots calculated for each Napier cultivar.
85
Figure 5.4.3. Comparisons of Napier accessions at LAMP 1 screening
At the second month of screening (after two months of incubation), 10 accessions were found to be
phytoplasma negative by LAMP (16794, 16822, 16815, 16817, 16789, 16809, Uganda hairless, Clone
13, Ex-Bakole and 16808), while 11 accessions were phytoplasma positive (Figure 5.4.4. Among the
accessions, the proportions of plants bearing the pathogen ranged from 10% in N16807 to 100% in
Ngr14 (Figure 5.4.4). However, there was total mortality of accessions N15743, Ex-bokole and Bgm
20.
Results
LAMP screening results for Napier grass accessions
At the preliminary LAMP screening, a total of 18 accessions were free of 16SrX1 phytoplasma (16621,
Uganda hairless, Nigeria 14, 16791, Malawi, Clone 13, Uganda L11, Mariakani, 16812, 16794, 16822,
16789, 16817, 16808, 16840, 16809, 15743 and Bungoma 20) while 49 had the phytoplasma. The
proportional infection of the accessions ranged from 33.33 to 100%. Out of the 49 accessions that had
phytoplasma, ve were asymptomatic indicating absence of the stunt symptoms. These were 16798
and Ex- Bakole (both with 100% plants that were phytoplasma positive by LAMP); and 16815, 18438
and 16807 (all with 66.67% plants that were phytoplasma positive by LAMP). These together with the
18 negative accessions were subjected to further screening.
Results of the selected 23 that were entered in further screening are compared at the rst LAMP,
second LAMP and third LAMP screening. At rst level (LAMP 1) of screening (after one month of
incubation), out of the 23 accessions screened, 4 accessions (Nigeria 14, Malawi, Mariakani and 15743)
had the Napier stunt phytoplasma. However, the propotion of plants found with phytoplasma were
less than 50% (Figure 5.4.3).
86
At the third month of screening, accessions 16789, Uganda hairless and Clone 13 were found to be
phytoplasma negative, while 15 accessions (16794, 16798, 16822, 16815, 18438, 16817, 16840, 16621,
16809, 16791, Malawi, Mariakani, 16812, 16807 and 16808) were found to carry the stunt phytoplasma.
The proportions of plants within acessions bearing the pathogen ranged from less than 10% in N16822
and 16808 to slightly over 90% in N16794 (Figure 5.4.5). However, there was total mortality of plants
belonging to accessions Ngr 14.
5.4.5. A chart showing comparisons of Napier accessions at LAMP 3 screening
Symptom expression
The development of NSD symptoms on the accessions was also observed after the rst re-growth,
second re-growth and third re-growth at an interval period of 30 days. Out of the 23 Napier accessions
screened, 10 accessions were symptomatic for NSD in the rst re-growth (N16794, N16840, N16791,
Mariakani, N15743, N16812, Uganda hairless, Clone 13, Exbakole and N16808) and the proportional
symptom expression ranged from 8.33% to 33.33% (Table 5.4.3). In the second re-growth, 12 accessions
(N16794, N16798, N18438, N16840, N16621, N16791, Ngr14, Malawi, Mariak, Ughless, Clone 13,
N16808) were symptomatic. The proportional range for the symptom expression was from 9.09% in
accession N16791 to 50% in accession Mariakani indicating an increase from the proportional range
of the previous month (rst re-growth). The number of symptomatic Napier accessions increased to
14 (N16794, N16798, N16815, N18438, N16840, N16621, N16809, N16791, Malawi, Mariakani, Uganda
hairless, Clone 13, Exbakole, N16808 in the third re-growth (fourth month of incubation) with the
proportional range of 10% in Exbakole to 63.64% in N16808. At the end of the experiment, 45.50% of
the total plants in the 23 accessions that were screened died as a result of the Napier stunt disease
compared to 10.51% that died although asymptomatic.
Figure 5.4.4 A chart of comparisons of Napier accessions at LAMP 2 screening
87
When comparing the proportions of the asymptomatic plants in the 23 accessions of Napier screened,
a total of 12 Napier accessions were asymptomatic for NSD in the rst re-growth (Table 5.4.3).
The proportion of asymptomatic plants for these accessions ranged from over 75% to 100%. In the
second re-growth only 7 out of the 12 accessions (asymptomatic in the rst re-growth) did not show
symptoms for NSD with a proportional range of about 25% to 100%. At the third re-growth, only 4
accessions (N16822, N16817, N16807 and N16789) remained symptomless with a proportional range
of about 50% in accessionN16822) to 90% in accession N16817, N16807 and N16789. Out of the three,
accessions 16817, 16807 and 16789 remained asymptomatic at almost constant proportions throughout
the period of scoring for symptom development while accession 16822 greatly varied in the third re-
growth.
Table 5.4.2. Proportions of data on symptom appearance in Napier accessions
Napier
accession
Total plants %+m1 %-m1 %+m2 %-m2 %+m3 %-m3 %+dead %-dead
N16794 12 16.67 83.33 16.67 83.33 16.67 75.00 8.33 0.00
N16798 12 0.00 100.00 16.67 83.33 25.00 66.67 8.33 0.00
N16822 12 0.00 83.33 0.00 83.33 0.00 50.00 0.00 50.00
N16815 12 0.00 100.00 0.00 100.00 25.00 75.00 0.00 0.00
N18438 11 0.00 100.00 27.27 72.73 45.45 54.55 0.00 0.00
N16817 9 0.00 88.89 0.00 88.89 0.00 88.89 0.00 0.00
N16840 12 25.00 75.00 33.33 58.33 41.67 25.00 25.00 8.33
N16789 12 0.00 91.67 0.00 91.67 0.00 91.67 0.00 0.00
N16621 12 0.00 100.00 25.00 41.67 25.00 8.33 0.00 66.67
N16809 11 0.00 100.00 0.00 100.00 18.18 72.73 0.00 9.09
N16791 11 9.09 81.82 9.09 81.82 27.27 36.36 0.00 63.64
Ngr14 5 0.00 100.00 20.00 0.00 0.00 0.00 0.00 0.00
Malawi 11 0.00 72.73 18.18 27.27 18.18 27.27 0.00 0.00
Mariak 12 25.00 75.00 50.00 41.67 50.00 41.67 0.00 0.00
N15743 12 8.33 41.67 0.00 0.00 0.00 0.00 0.00 0.00
N16812 12 33.33 41.67 0.00 0.00 0.00 0.00 0.00 0.00
UgL11 12 0.00 100.00 0.00 25.00 0.00 0.00 0.00 0.00
Bgm 20 12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Ughless 12 8.33 91.67 25.00 75.00 16.67 75.00 8.33 0.00
Clone 13 12 16.67 83.33 16.67 75.00 16.67 58.33 25.00 0.00
N16807 10 0.00 90.00 0.00 90.00 0.00 90.00 0.00 0.00
Exbakole 10 20.00 50.00 0.00 50.00 10.00 40.00 20.00 40.00
N16808 11 27.27 72.73 36.36 63.64 63.64 27.27 9.09 0.00
Total 45.50 10.51
%+m1= Proportion of plants symptomatic after 1st month cut back, %-m1= Proportion of plants
asymptomatic after 1st month cut back, %+m2= Proportion of plants symptomatic after 2nd month
cut back, %-m2= Proportion of plants asymptomatic after 2nd month cut back, %-m3= Proportion of
plants asymptomatic after 2nd month cut back and %+m3= Proportion of plants symptomatic after
3rd month cut back.
Accessions 16807 remained asymptomatic at the end of the experiment. This accession had high
proportion of positive plants by LAMP (60%) but did not develop the Napier stunt symptoms nor die
from stunt disease (Figure 5.4.6 and Figure 5.4.7).
88
1 - + 4 5 6 7 8 9 10 11 12 13 14
Figure 5.4.6. A picture of the third re-growth of Napier
accession 16807 four months after inoculation with the
Ns-Phytoplasma.
Figure 5.4.7. Amplication of accession 16807 DNA of the
third re-growth (1 -100 Bp ladder (Genscript), - negative,
+ positive, 6 positive
Accession 16789 remained asymptomatic and had no plant that were positive by LAMP throughout
the three months of LAMP screening (Figures 5.4.8 and 5.4.9)
1 - + 2 3 4 5 6 7 8 9 10 11 12
Figure 5.4.8. A picture of the third re-growth
of Napier accession 16789 four months after
inoculation with the NSD phytoplasma
Figure 5.4.9. Amplication of accession 16789 DNA of the
third re-growth (1 -100 Bp ladder (Genscript), - negative, +
positive, 11plants negative by LAMP at the third month of
screening).
Figure 5.9.10. A morphological
comparison of the accessions 16789
(resistant), 16807 (tolerant) and 16840
(susceptible) after four months of
incubation
The two Napier accesions (N16789 and N16807) when compared to the most susceptible accession
N16840 (which had high proportion of plants positive by LAMP) showed severe stunt symptoms
as shown in Figure 5.4.10 indicating the variation in the napier accessions’ response to the Ns-
Phytoplasma.
89
In accessions Bgm 20, Ex-Bakole, N15743, N16807, N16808 and Nigeria 14 plant height was signicantly
reduced while the differences between accessions 16789, and 16812 were not signicantly (P< 0.001)
different (Table 5.4.3). Leaf length was signicantly reduced in accessions Bgm 20, Ex-Bakole, N15743,
N16807, N16812 and Nigeria 14 but not between accessions 16789 and 16808. The leaf width was
not signicantly reduced in 16789, 16812 Bgm 20, Ex-Bakole, N15743 (P < 0.001) while in accessions
N16807, N16808 and Nigeria 14 the leaf width was signicantly reduced.
Table 5.4.3. Mean proportional changes in plant height, leaf length and width
Napier variety Mean proportional difference
in plant height ± (SE)
Mean proportional changes
in leaf length ± (SE)
Mean proportional change in
leaf width ± (SE)
BGM20 -16.71±10.64abc -5.04±5.7a 22.27±9.89ac
ExBakole -35.28±7.89ab -3.97±3.01a 0.15±4.41abc
N15743 -19.61±2.95abc -7.18±0.93a 4.55±4.55abc
N16789 17.97±6.32d 16.67±7.72ab 7.71±9.38abc
N16807 -6.68±2.35cd -1.29±0.72a -4.33±1.43abc
N16808 -7.74±4.73bcd 1.63±4.93a -12.42±4.55ab
N16812 48.72±8.91e -1.29±0.72b 0.12±8.43abc
Nigeria1 -53.99±7.80a -23.15±6.44a -17.06±4.99a
F 19.03 5.3 2.1
p <0.001 <0.001 <0.001
Assessment of Maiestas banda’s feeding behavior on the resistant Napier accession
The treatment of the lter paper discs with 0.1% ninhydrin-acetone solution resulted in Bluish amino
acid spots, indicating that Maiestas banda fed on the phloem of both the resistant Napier accession
N16789 and the susceptible (control) Bana variety (Figure 5.4.11 a & b).
Fig. 5.4.11a: Bluish amino acid spots for the honey dew droppings of Maiestas banda on Bana variety (control)
Figure 5.4.11b. Bluish amino acid spots for the honey dew droppings of Maiestas banda on accession N16789 (resistant )
90
Discussion
The 23 Napier accessions screened in this study differed in the time to express the Napier stunt
symptoms consistent to the ndings of a eld experiment by Muyekho et al. (2006). At the end of the
three months of screening, accession 16789 remained asymptomatic and all plants were phytoplasma
negative by LAMP. At the same time the stunt phytoplasma had no signicant effect on the yield
parameters an indication of possible resistance/ high level of tolerance. The assessment of Maiestas
banda’s feeding behavior on this accession indicated that the vector was able to feed on it and hence
absence of the stunt phytoplasma could not be attributed to plant escape from the vector during
inoculation. These ndings do point ability of accession 16789 to resist the effects of the stunt
phytoplasma.
Although Napier accession 16817, 16822, 16807 remained asymptomatic, they had proportions of
the test plants containing phytoplasma by LAMP hence could be considered as being tolerant. The
lack of symptoms in these three accessions could be linked to uneven distribution of phytoplasmas
in the phloem of infected plants, or low concentrations (especially in woody hosts) and variations
in titer according to season and plant organ (Firrao et al. 2007). However, accession 16807 had the
highest proportion of plants positive with the stunt phytoplasma by LAMP but with least effect of
the phytoplasma on the yield parameters. Seemüller and Harries (2010) reported that phytoplasma
severely affect the phloem function in susceptible plants impairing transport of soluble organic
material especially to the roots; and the symptoms are mild or absent in such resistant plants. This
accession could therefore be considered as being highly tolerant. On the other hand, symptomatic
plants in Napier accession 16812 reverted to asymptomatic state in the second re-growth and there
was insignicant effect of the stunt phytoplasma on the yield parameters of this accession indicating
tolerance to the pathogen. Although there is scarcity of information on recovery responses of
gramminacious plants from phytoplasma infections, this effect has been observed in grapevines
infected with Bois noir disease known to be associated with the stolbur phytoplasma (STOL), which
is a member of the 16SrXII-A group (Romanazzi et al. 2007), and grapevines infected with Flavescence
dorée disease caused by Flavescence dorée Phytoplasma (FD) a member of the 16SrV taxonomic
group (Musetti et al. 2007).
Uganda hairless and Clone 13 indicated absence of the Ns-Phytoplasma but were symptomatic for
Napier stunt. This could be alluded to poor correlation between phytoplasma presence and phloem
aberrations or external symptoms occurring in some parts of infected plants, where by a long-distance
effect of phytoplasmal infections is hypothesized (Marcone 2010). Other factors that could contribute
to the inconsistence of symptom development and detection of the Ns-Phytoplasma in the inoculated
plants include strain virulence, strain interference, phytoplasma concentration, toxins, plant hormone
imbalance and attachment of phytoplasmas to host cell membrane (Marcone 2010). There is need for
further study on these accessions to clearly determine which among these factors led to this response.
Clone 13 in this study was symptomatic; inconsistent with the ndings of Muyekho et al (2006). This
could be because greenhouse screening provides conducive conditions for infestation and is more
reliable and rapid than eld screening that depends on chance (TNAU 2008). Also eld screening has
a weakness such that the insect population cannot be uniformly controlled to ensure that plants that
escape infestation are not graded as resistant (TNAU 2008).
91
Conclusion
Napier accession N16789 had no plants containing the pathogen and also showed no phytoplasma
symptoms throughout the screening period. This accession could be a good source of resistance
for future development of Napier grass varieties with good agronomic traits for release to farmers.
Napier accession N16807 indicated high level of tolerance with high proportions of test plants positive
with phytoplasma and remained asymptomatic throughout the screening period. Napier accessions
N16822 and N16817 had moderate tolerance because they remained asymptomatic throughout the
screening period despite the presence of the Ns-phytoplasma in some of their plant population by the
third LAMP screening.
Recommendations and future research
1. Napier accession 16879 be tested under multi-location sites for yield and duration of the
tolerance/resistance
2. Napier accessions 16817, 16822, 16812, 16807 were moderately tolerant should be evaluated
for yield under multi-locational sites
3. Mechanism of tolerance/resistance in accession 16879 be established
4. Evaluate IPM strategies that combine tolerance/resistance in accessions 16789, 16817, 16822,
16812, 16807 and other management strategies to sustain the resistance/ tolerance
5. Tolerant materials identied for stunt and smut be subjected to study on disease interaction
between phytoplasma & smut
Acknowledgments
This study was made possible through the nancial support of the McKnight Foundation and EAPP.
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94
CHAPTER 6: Epidemiology of Napier stunt disease in Eastern and Central
African region
6.1 Genetic Characterization of Alupe Napier Grass Accessions Based on Simple Sequence
Repeat Markers
Geofrey Kawube1,, Jolly Kabirizi2 and Clementine Namazzi2
1 Root Crops Program, National Crops Resources Research Institute - National Agriculture Research
Organisation, P. O. Box 7084, Kampala, Uganda.
23 Livestock Nutrition Program, National Livestock Resources Research Institute – National Agriculture
Research Organisation, P. O. Box 96, Tororo, Uganda.
Introduction
Napier grass (Pennisetum purpureum), also known as elephant grass is a robust perennial forage
indigenous to sub-Saharan Africa (Lowe et al., 2003). The grass is dominant in the fertile crescent along
north of Lake Victoria and the western Rift Valley in Uganda (Farrel et al., 2002). Currently, Napier
grass is the principal fodder crop in smallholder intensive and semi intensive livestock production
systems in East Africa (Staal et al., 1999), constituting 40 – 80% of forages used to meet the increasing
demand for milk. The demand for Napier grass is growing, mostly among poor households in densely
populated areas due to its desirable traits such as tolerance to drought, ability to grow in a wide range
of soil conditions, high photosynthetic and water-use efciency (Andreson et al., 2008). The grass can
also withstand repeated cutting with rapid regeneration, producing a high yield that is very palatable
to cattle in the leafy stage (Lowe et al., 2003).
Napier grass productivity in the East African region is limited by several factors especially the emerging
new diseases like Napier Grass Stunt Disease and Napier Grass Head Smut Disease, thus constraining
the growth of smallholder dairy industry (New Agriculturists, 2009). Therefore, continued utilization
of Napier grass as a fodder will depend on exploitation of the genetic variability within and among its
populations (Faisal et al., 2007) in search for resistance to these production constraints. This requires
a well characterized and inventoried germplasm; which is lacking in the case of Napier grass in East
African countries including Uganda (Kawube et al., 2014). In East Africa Kenya Agricultural Research
Institute – Dairy Research Centre at Alupe maintains a collection of Pennisetum purpureum; obtained
from within Kenya and the International Livestock Research Institute, in Ethiopia whose genetic
diversity is not known.
Various methods for estimating diversity in a plant population exist and use of simple sequence
repeats (SSRs) has become the method of choice because of the markers multi-allelism, genome
specicity, even distribution and high polymorphism. However, the genome of Napier grass has
not been sequenced, therefore, Napier grass SSR markers are not known. Besides, Napier grass is
a tetraploid (2n = 4x=28) with triploid and hexaploid hybrids occurring between it and pearl millet
[8]. This makes establishing microsatellites that adequately discriminate the different ploidy levels
difcult. The available option is through cross-amplication using SSR markers of closely related
species (Azevedo et al., 2012). This study, therefore, determined the genetic variability among
Napier grass clones maintained Kenya Agricultural Research Institute – Alupe station through cross-
amplication using SSR markers of closely related organisms.
95
Materials and methods
Sample Collection and Analysis
Twenty two Napier grass clones (19, 41, 75, 76, 79, 97, 103, 104, 105, 112, 117, 16702, 16789, 16805,
16814, 16815, 79SN, ANF, Kakamega1, Kakamega2, kakamega3 and RBN) obtained from Kenya
Agricultural Research Institute – Dairy research Center Alupe and one clone - 16785 obtained from
International Livestock Research Institute – Ethiopia were planted in the eld at National Crops
Resources Research Institute at Namulonge in Uganda in 6 replicates. Two months after planting,
samples were collected from the inner most unfolded leaf on one tiller of each plant, placed in a paper
bag with silica gels, packed in a box. These were transferred to Bioscience Eastern and Central Africa
at International Livestock Research Institute (BecA-ILRI) - Nairobi for genotyping.
In the laboratory, 1.5 g of a leaf was extracted from each leaf sample and ground in mortar in liquid
Nitrogen. Total plant DNA was extracted using cetyltrimethylammonium bromide (CTAB) method
(Doyle et al., 2005) and diluted to 100µ using double distilled water. The DNA concentration was
determined using Nanodrop UV spectrometry at A260 and A280 while the integrity of DNA was
tested on 1.2% agarose gel electrophoresis in TBE buffer stained with gel red. From these, template
DNA was made from an aliquot in a 1.5 ml tube and diluted to 50ng/µ.
DNA Amplication with Microsatellite Markers
A total of 17 simple sequence repeat microsatellite primer pairs, originally identied in maize, pearl
millet and sorghum were conjugated with different dyes (VIC, NED, PET and 6-FAM). These were
used in the PCR amplication in 20µl AccuPower® Taq Premix (Bioneer) to which 17µl of water and
0.5µl of 5 picomoles of each of the primer pair and 2µl of template DNA were added. The reaction
mixture was subjected to the following PCR conditions: an initial denaturation of 94oC (3min) followed
by 35 cycles of 94oC (30sec); specic primer annealing temperature (1min) (Table 6.1.1); extension at
72oC (2min), nal extension at 72oC (10min) and nal hold at 4oC. The PCR products were run on
1.2% agarose gel electrophoresis stained with gel red in 0.5X TBE buffer at 80 V for 50 minutes and
visualized on trans UV and photographed in UVP DIGIDOC – IT system (UVP BioImaging systems,
USA). The PCR products with clear single band amplication on the agarose gel were subjected to
capillary electrophoresis with ABI3730 DNA genetic analyser for fragment analysis and allele calls
were made using GENEMAPPER software v.3.7 (Applied Biosystems). Primers whose PCR products
generated high quality electropherogram peaks of uorescent intensity above 50 at differing positions
in the samples were selected (Table 6.1.1) and used for amplication of all the samples.
Data Analysis
Microsatellite allele distribution data obtained from Genscan®software Version 4.1 were converted
into suitable formats for statistical analysis. Allelic size data for each SSR locus was used to estimate
percentage of polymorphic loci, Shannon’s information index (I), Nei’s gene diversity, observed (Ho)
and expected (He) heterozygosities using Power Marker version 3.25 (Liu et al., 2005). Cluster analysis
was performed based on Nei’s distance matrix using GenALEX6.2 (Peakall et al., 2009).
96
Figure 6.1.1. PCoA scatter plot showing the clustering of the 23 Napier grass clones
Results
The SSR markers used in this study generated 90 alleles in 23 Napier grass accessions. The number
of alleles detected for each primer pair ranged from 2 (CTM10, CTM59, PSMP2235, PGIRD25) to 13
(CTM8) with average of 5.29 (Table 6.1.2). The frequency of the major alleles in each marker locus
ranged from 0.23 (PSMP2267) to 0.98 (PGIRD25). Polymorphic Information Content for the assayed
marker loci ranged from 0.04 (PGIRD25) to 0.85 (PSMP2267) with average of 0.5. The observed and
expected heterozygosity generated by the markers was moderate. Marker PSMP2267 had the highest
expected and observed heterozygosity of 0.86 and 0.95, respectively while PGIRD25 exhibited the
least expected and observed heterozygosity both at 0.04 (Table 6.1.2).
The proportion of rare alleles (private alleles) within the Napier grass accessions was very low with
seven clones ranged from 0.00 in clones 41, 75, 76, 79, ANF, kakamega1 and RBN having while the
highest number of private alleles was recorded in clone 16814. The highest Shannon information
index was recorded in clone 16785 while the least was recorded in clone 16814 and 105. In relation, the
highest expected heterozygosity was recorded in clone 16785 while the least was recorded in clone
16814 and 105. Napier grass accession 16785 showed the highest number of effective alleles) while
accession 105 had the least. Similarly, percentage polymorphic loci ranged from 27.8% in clone 16814
and 105 to 77.8% in clone 16785 (Table 6.1.3).
Pairwise comparison of genetic distance revealed big difference among the Napier grass clones
ranging from 0.11 (between Kakamega 1, Kakamega 2, Kakamega 3 ) to 1.00 between clone 16814 and
105 (Table 6.1.4). Principal Coordinate Analysis was calculated from dissimilarity coefcients for two
rst axes coordinates with positive eigen values. The axes accounted for 52.8% variation with rst
axis accounting for 29.8% while the second axis accounted for 23.0%. Principal Coordinate Analysis
did not group the clones into clear structures. However, clones Kakamega 1, Kakamega 2, Kakamega
3 and 16805 and clone 112 and ANF grouped together, respectively (Figure 6.1.1). The UPGMA
dendogram based on pairwise Nei’s genetic distance showered two major clusters; one consisting of
only clone 16814 and the other consisting of the rest of the clones (Figure 6.1.2).
97
Figure 6.1.2. UPGMA neighbour joining
dendogram of 23 napier grass clones
computed from 17 ssr markers using
darwin hierachial clustering
Table 6.1.1: SSR primers used to assess genetic diversity in 23 Napier clones
Primer
name
Sequence left primer
(forward 5’ – 3’)
Right primer
(reverse 5’ – 3’)
Annealing
temperature
(oC)
CTM-10 GAGGCAAAAGTGGAAGACAG TTGATTCCCGGTTCTATCGA 52
CTM-27 GTTGCAAGCAGGAGTAGATCGA CGCTCTGTAGGTTGAACTCCTT 52
CTM-59 TCCTCGACATCCTCCA GACACCTCGTAGCACTCC 54
CTM-8 GCTGCATCGGAGATAGGGAA CTCAGCAAGCACGCTGCTCT 52
PGIRD21 GCTATTGCCACTGCTTCACA CCACCATGCAACAGCAATAA 54
PGIRD25 CGGAGCTCCTATCATTCCAA GCAAGCCACAAGCCTATCTC 58
PGIRD57 GGCCCCAAGTAACTTCCCTA TCAAGCTAGGGCCAATGTCT 56
PSMP2235 GCTTTTCTGCTTCTCCGTAGAC CCCAACAATAGCCACCAATAAAGA 54
PSMP2248 TCTGTTTGTTTGGGTCAGGTCCTTC CGAATACGTATGGAGAACTGCGCATC 58
PSMP2255 CATCTAAACACAACCAATCTTGAAC TGGCACTCTTAAATTGACGCAT 54
PSMP2266 CAAGGATGGCTGAAGGGCTATG TTTCCAGCCCACACCAGTAATC 58
PSMP2267 GGAAGGCGTAGGGATCAATCTCAC ATCCACCCGACGAAGGAAACGA 60
Xipes0093 GGATCTGCAGGTTTGGACAT CCAAGCACTGAAACATGCAC 57
Phil227562 TGATAAAGCTCAGCCACAAGG ATCTCGGCTACGGCCAGA 56
Xcup14 TACATCACAGCAGGGACAGG CTGGAAAGCCGAGCAGTATG 53
Xcup63 GTAAAGGGCAAGGCAACAAG GCCCTACAAAATCTGCAAGC 53
XTXP278 GGG TTT CAA CTC TAG CCT ACC GAA CTT
CCT
ATG CCT CAT CAT GGT TCG TTT TGC
TT
50
98
Table 6.1.2. Genetic diversity parameters averaged across all groups and loci for 23 Napier
grass clones
Primer Major allele
frequency
Number of
alleles
Gene diversity/
expected
heterozygosity (He)
Observed
heterozygosity (Ho)
Polymorphic
information content
(PIC)
CTM10 0.52 2 0.49 0.87 0.37
CTM59 0.96 2 0.08 0.09 0.08
CTM8 0.29 13 0.82 0.89 0.80
CTM27 0.43 4 0.64 0.96 0.57
PGIRD21 0.37 9 0.80 0.52 0.78
PGIRD57 0.76 5 0.40 0.04 0.38
PSMP2248 0.63 4 0.53 0.22 0.47
Xipes0093 0.60 5 0.58 0.80 0.53
Phil227562 0.54 4 0.58 0.93 0.50
Xcup14 0.79 4 0.35 0.36 0.38
PSMP2266 0.47 5 0.66 1 0.61
PSMP2235 0.59 2 0.48 0.65 0.37
PGIRD25 0.98 2 0.04 0.04 0.04
PSMP2267 0.23 11 0.86 0.95 0.85
PSMP2255 0.33 7 0.76 0.78 0.72
XTXP278 0.64 6 0.53 0.72 0.47
Xcup63 0.48 5 0.66 0.96 0.61
Mean 0.57 5.29 0.54 0.63 0.50
Table 6.1.3: Mean number of effective loci (ne), shannon index (i), proportion of private
alleles, expected heterozygosity(he) and percentage polymorphism across the 23 Napier grass
clones
Population Ne I Proportion of private Alleles He %Polymorphism
19 1.500 0.385 0.222 0.278 55.6
41 1.667 0.462 0.000 0.333 66.7
75 1.444 0.347 0.000 0.250 50.0
76 1.667 0.462 0.000 0.333 66.7
79 1.556 0.385 0.000 0.278 55.6
97 1.389 0.347 0.111 0.250 50.0
103 1.556 0.424 0.056 0.306 61.1
104 1.611 0.424 0.111 0.306 61.1
105 1.000 0.193 0.056 0.139 27.8
112 1.278 0.308 0.111 0.222 44.4
117 1.556 0.462 0.056 0.333 66.7
16702 1.222 0.308 0.056 0.222 44.4
16785 1.778 0.539 0.111 0.389 77.8
16789 1.500 0.385 0.056 0.278 55.6
16805 1.556 0.385 0.111 0.278 55.6
16814 1.222 0.193 0.278 0.139 27.8
16815 1.556 0.424 0.056 0.306 61.1
79SN 1.444 0.347 0.056 0.250 50.0
ANF 1.333 0.308 0.000 0.222 44.4
kakamega1 1.500 0.385 0.000 0.278 55.6
kakamega2 1.556 0.385 0.056 0.278 55.6
kakamega3 1.556 0.385 0.056 0.278 55.6
RBN 1.222 0.308 0.000 0.222 44.4
99
Table 6.1.4: Nei’s Unbiased genetic distance of the 23 Napier grass clones based on SSR analysis
19 41 75 76 79 97 103 104 105 112 117 16702 16785 16789 16805 16814 16815 79SN ANF kaka1 kaka2 kaka3 RBN
0 19
0.263 0 41
0.312 0.259 0 75
0.208 0.239 0.179 0 76
0.345 0.105 0.207 0.181 0 79
0.6 0.288 0.519 0.442 0.207 0 97
0.412 0.155 0.315 0.238 0.262 0.373 0 103
0.587 0.426 0.612 0.426 0.38 0.503 0.562 0 104
0.938 0.839 0.872 0.795 0.725 0.749 0.913 0.699 0 105
0.974 0.57 0.852 0.822 0.552 0.576 0.635 0.674 0.698 0 112
0.683 0.365 0.511 0.434 0.292 0.377 0.359 0.535 0.634 0.57 0 117
0.741 0.608 0.647 0.775 0.587 0.685 0.897 0.597 0.852 0.922 0.87 0 16702
0.464 0.123 0.35 0.273 0.149 0.318 0.179 0.367 0.693 0.342 0.241 0.588 0 16785
0.652 0.292 0.563 0.486 0.26 0.207 0.444 0.38 0.687 0.422 0.353 0.7 0.233 0 16789
0.652 0.235 0.462 0.451 0.158 0.285 0.38 0.55 0.805 0.453 0.292 0.783 0.176 0.234 0 16805
0.615 0.563 0.424 0.496 0.427 0.541 0.738 0.913 1.000 0.939 0.672 0.939 0.693 0.687 0.687 0 16814
0.55 0.209 0.469 0.359 0.157 0.315 0.294 0.419 0.822 0.635 0.327 0.758 0.179 0.319 0.29 0.699 0 16815
0.637 0.288 0.423 0.377 0.258 0.336 0.286 0.538 0.788 0.447 0.377 0.808 0.201 0.232 0.285 0.64 0.344 0 79SN
0.828 0.465 0.685 0.731 0.422 0.417 0.635 0.459 0.698 0.47 0.534 0.599 0.342 0.23 0.392 0.735 0.526 0.388 0 ANF
0.504 0.13 0.462 0.451 0.158 0.258 0.349 0.478 0.725 0.453 0.385 0.661 0.149 0.182 0.158 0.582 0.235 0.232 0.335 0 kaka1
0.47 0.235 0.399 0.353 0.234 0.285 0.262 0.444 0.764 0.453 0.385 0.741 0.122 0.158 0.234 0.651 0.29 0.232 0.335 0.11 0 kaka2
0.575 0.235 0.43 0.417 0.158 0.258 0.319 0.319 0.725 0.453 0.353 0.783 0.176 0.158 0.208 0.582 0.182 0.232 0.281 0.134 0.11 0 kaka3
0.7 0.465 0.611 0.534 0.364 0.332 0.597 0.561 0.629 0.708 0.465 0.634 0.475 0.308 0.422 0.698 0.459 0.509 0.533 0.392 0.422 0.422 0 RBN
100
Discussion
Genetic characterization of cultivars is an important step in any breeding programs for selection of
appropriate parental lines (Xie et al., 2009). Several DNA marker systems for germplasm genetic
characterization are available and SSRs have been found most adequate in detecting relationships
among closely related materials as well as obtaining specic genetic ngerprints (Munoz-Falcon et
al., 2009). In this study, 17 SSR markers used produced high mean polymorphic information content
suggesting that they are highly informative and able to discriminate among the different clones.
According to Elibariki, et al. (Elibariki et al., 2013) the ability to discriminate, however, varies from
one marker to another, thus the most polymorphic marker was CTM8 while the least polymorphic
was PGIRD25.
Both gene diversity and observed heterozygosity averaged across all loci was moderate. This result
is in agreement with the ndings of Wanjala et al. (2013) who while working on Napier grass from
east Africa region using AFLPs found moderate diversity among accessions. According to Bhandari
et al. (Bhandari et al., 2006), Napier grass is of free pollination and high genetic diversity is expected
from its natural crossings. The moderate genetic diversity revealed in this study is due to the fact that
Napier grass grown onfarm is predominantly propagated by cuttings and subjected to high selection
intensity by farmers. The markers revealed high number of private alleles in majority of the Napier
grass clones. These, if included in breeding programs increase the chances of getting clones with
farmer preferred traits.
The genetic distance revealed between the clones was generally high, with the highest distance being
between clones 16814 and 105. This was further supported by the dendogram in which clone 16814
clustered different from the rest. This provides a basis for developing heterotic pool (Fregene et al.,
2003) from which crosses between genetically diverse parents can be made to produce progenies
with higher genetic variation than those produced by closely related parents. The grouping of clone
16814 different from clone 16815 and 16805, yet all originate from United States of America (Wouw
et al., 1999) shows that the clustering was not based on the origin of the clones. This view contradicts
the ndings of Lowe et al. (2002) who while using RAPDS reported that Napier grass accessions
cluster corresponding to geographical location. However, it is in agreement with Wanjala et al. (2013)
who while using AFLPs reported that Napier grass did not cluster depending on their origin. The
clustering together of the other clones most of which originate in Africa is a proof that Africa is the
center of diversity (Azevedo et al., 2013), as such it houses majority of the pennisetum gene pools
(Techio et al., 2012). The loose clustering of accessions as revealed by PCA is possibly due to absence
or low gene ow since Napier grass is clonally propagated. The genetic closeness of Kakamega 1,
Kakamega 2 and Kakamega 3 indicates that they share most alleles and were collected from the same
area known as Kakamega in Kenya.
Conclusion
Based on the foregoing, clones evaluated in this study are diverse with multitudes of private alleles
which if found useful can be exploited in breeding to improve Napier grass. As such, Clone 16814,
which is the most distant to all, is better suited for improvement of the rest of the clones if its attributes
are found superior to those in others. Clones Kakamega1, Kakamega2, and Kakamega3 are more less
the same, hence if any genetic improvement is to be carried out; it has to be with other distant clones.
101
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102
CHAPTER 7: Evaluation of alternative forages and feed resources to improve
feed availability in smallholder dairy production systems
7.1: Dry season forages for improving dairy production in smallholder systems in Uganda
1 Kabirizi, J.; 2Zziwa, E.; 1Mugerwa, S., 1Nanyeenya, W. and 2Ndikumana, J.
1 National Livestock Resources Research Institute (NaLIRRI), Tororo, Uganda Association for Strengthening
Agriculture Research in Eastern and Central Africa (ASARECA), Uganda
Introduction
Smallholder dairy farming systems dominate in the rural in Eastern and Central African region,
employ over 70% of the region’s population and contribute 70–90% of the total meat and milk
output in the region (Njarui et al. 2012). Small-scale dairy production plays a crucial role in food
security, human health and overall household livelihoods, particularly among climate change-prone
resource-poor households in the region. Zero-grazing dairy systems are increasingly promoted,
owing to grazing land shortage and intensive dairy production requirements. Women are immense
contributors to and beneciaries from smallhold-er dairy production systems (Njarui et. al. 2012),
which are progressively being devastated by rapid climate change and its attendant extreme weather
conditions. The availa-bility of livestock feeds in rural households is being affected by climate change.
The lack of effective adapta-tion to the adverse effects of climate change is likely to jeopardize the
achievement of Millennium Development Goals 1 (eradicating extreme poverty and hunger), 7 (en-
suring environmental sustainability) and 3 (promoting gender equality and empowering women)
(United Nations 2010).
Napier grass (Pennisetum purpureum) is the major for-age in zero-grazing production systems in Masaka
district, Uganda (Kabirizi 2006). However, grass productivity is constrained by long droughts, poor
agronomic practices, such as lack of fertilizer application and improper cutting frequency and cutting
height, and by pests and diseases, the napier stunt disease being particularly important, re-sulting in
a reduction in fodder yield of up to 100% during the dry season. Brachiaria hybrid cv. Mulato (Mulato)
has high biomass yield and tolerates long droughts and poor soils (CIAT 2001) and could be used to
complement Napier grass. It is recommended that Mulato be grown to provide forage, when Napier
grass production is low.
It is generally recommended, furthermore, that forages be grown in grass-legume mixtures in order
to not only ensure energy-protein balance for livestock, but also har-ness atmospheric nitrogen (N)
via the legume component (Thomas 1995; Kabirizi 2006). Among the best-known, but not widely
used forage legumes in Uganda are Centrosema molle (syn. C. pubescens; Centro) and Clitoria ternatea
(Clitoria); both are deep-rooting and considered as drought-tolerant. However, regardless of whether
sown as a monocrop or in mixture with a legume, the ofcially recommended 0.5-ha Napier grass
area is not sufcient to provide year-round forage for 1 cow and its calf.
This study was designed to develop economically feasi-ble strategies for year-round feed supply
to dairy cattle in order to improve feed resource availability, milk yield and household income, by
comparing in on-farm trials the newly introduced drought-tolerant Mulato with commonly used
Napier, both grown with a drought-tolerant legume.
103
Methodology
Description of the study site
The study was conducted in Masaka district, Central Uganda (00°15’- 00°43’ S, 31°- 32° E; 1150 m
above sea level) (Figure 7.1.1). Annual average rainfall is 800–1000 mm with 100–120 rainy days, in
2 seasons. Mean temperature ranges between 16°C and 30°C, while relative humidity is 62%. The
district is typically dependent on crop-livestock systems, with vegetable production as a key income
generator.
Figure 7.1.1: Maps showing study sites
The study targeted zero-grazing dairy farmers with 1–2 cows and at least 2 ha of land of which 0.5
ha was already planted with Napier grass fodder. The treatments involved 2 grass-legume mixtures:
Napier with Centro and Mulato with Clitoria (Figure 7.1.2). These mixtures were established as forage
banks in 0.5 ha each on 24 randomly selected farms using methods described in Humphreys (1995)
and CIAT (2001). The mixtures were compared with the farmers’ practice of growing Napier grass
alone.
Brachiaria fodder bank Brachiaria fodder harvested from an area of 1 m x 1 m
Figure 7.1.2: Drought tolerant Brachiaria hybrid cv Mulato 11
104
Farmers participated in all stages of project implementation to enhance rapid uptake of emerging
knowledge and practices. The study was laid out in a randomized complete block design with
household farms as replications. Fodder and milk yields from all 24 farms were recorded for 2
years. Dry matter yields and associated feeding periods were estimated using methods described by
Humphreys (1995). Data were analyzed with costs of inputs and returns from milk (including home-
consumed) recorded for protability evaluation using partial budgeting.
Farmers participated in all stages of project implementation to enhance rapid uptake of emerging
knowledge and practices. The study was laid out in a randomized complete block design with
household farms as replications. Fodder and milk yields from all 24 farms were recorded for 2
years. Dry matter yields and associated feeding periods were estimated using methods described by
Humphreys (1995). Data were analyzed with costs of inputs and returns from milk (including home-
consumed) recorded for protability evaluation using partial budgeting.
Beneciaryassessmentofdroughttolerantforages
A second study was conducted comparing the beneciaries of the drought-tolerant forage technology
(0.5 ha Napier + Centro mixture plus 0.5 ha Mulato + Clitoria mixture) with the non-beneciaries
(0.5 ha Napier monocrop). Beneciaries (n=24) of the interventions and non-beneciaries (n=24)
were purposively selected with equal number of women and men. Three data collection approaches
namely Systematic Client Consultations based on semi-formal beneciary assessment case studies,
objective data verication by direct observation and Community group discussions were used. Data
associated with costs of inputs and returns from milk (including home consumed) were recorded for
protability evaluation using partial budgeting. Data was analysed using Statistical Packages for
Social Sciences package (SPSS, 2002).
Results and Discussion
Intercropping Centro with Napier grass increased fodder availability by 52%, crude protein (CP)
concentration by 20% and feeding period (number of days a cow was able to feed on fodder from a
given area of land) by 52% (Table 7.1.1).
Table 7.1.1: Fodder availability and quality, and feeding period for different forage banks
Forage banks
Parameter Napier grass and
Centrosema molle
mixture
Brachiaria and
Clitoria ternatea
mixture
Napier grass
monocrop
SEM
Mean Dry matter yield (kg ha-1) 15,790 12,119 10,354 307
Feeding period (days) from 0.5 ha 254.6 195.5 167.0 20.9
Crude protein content (%) 8.4 12.1 7.0 0.14
SEM: Standard error of mean
The Mulato-Clitoria mixture provided dry matter yields and a feeding period that were intermediate
between the 2 Napier treatments but the increase in CP concentration was 73 respectively 44% higher.
Higher total fodder yields and CP concentrations in in-tercrops (Table 7.1.1) could be attributed to
the presence of forage legumes that improved growth of the grass. The legume acted as a cover crop
to control weeds and con-serve soil moisture during the dry periods, apart from the possibility of
augmenting N supply to the grass component through symbiotic N-xation (Kabirizi 2006).
105
Table 7.1.2: Socio-economic benets of introduced forages
Beneciaries(n=20) Non- beneciaries (n=20) F-test IA
Household characteristics Mean SD Mean SD
Land size (ha) 1.7 1.2 1.6 0.9 0.12NS
Cattle (number) 1.5 0.5 1.3 0.7 0.03NS
Fodder area (ha) 1.1 0.3 0.5 0.3 14.4** 134.1
Feed offered cow-1 day-1 (fresh) 55.4 12.3 31.4 7.2 5.7* 76.4
Milk yield (L day-1) 10.6 7.2 5.9 3.1 4.3* 79.7
Revenue (US $) from milk yield
cow-1 year-1
676.9 48.2 444 64.1 1.66NS 52.4
***=signicant at 1%, ** = signicant at 5 %; NS = not signicant SD: Standard deviation; IA: Intervention
advantage
The results conrmed that the currently recommended acreage of 0.5 ha of a mixture of Napier grass
with a for-age legume (Samanya 1996) will produce additional forage of higher quality than Napier
grass alone but cannot sustain an economically producing dairy cow and its calf for a full year.
Therefore, establishment of an additional 0.5 ha of a mixture of the drought-tolerant Mulato with a
forage leg-ume is recommended for feeding during the dry season, when production of Napier grass
monocrop is disadvan-taged due to drought, the napier stunt disease and poor agronomic practices.
A second study was conducted comparing the bene-ciaries of the drought-tolerant forage technology
(0.5 ha Napier + Centro mixture plus 0.5 ha Mulato + Clitoria mixture) with the non-beneciaries (0.5
ha Napier monocrop) (Table 7.1.2).
There were no signicant (P>0.05) differences in land size and number of cattle kept between the
beneciaries and non-beneciaries of the interventions but sowing 0.5 ha of each of the grass-legume
mixtures improved milk yield and household income by 80 and 52%, respectively, over 0.5 ha Napier
grass. The bene-ciaries fed 76% more high-quality forage, i.e. the milk yield response was largely
due to simply feeding more. Beneciaries, however, had 120% more land sown to fodder, implying
they were not harvesting as much forage per ha (if all harvested forage was fed to cows) or were able
to sell fodder to others.
In assessing the overall benets of this production sys-tem, it is important to remember that an extra 0.5
ha was sown to a grass-legume mixture and was no longer availa-ble for other agricultural purposes.
Conclusion
Replacing traditional Napier grass forage banks with grass-legume mixtures, including the drought-
tolerant Brachiaria hybrid cv. Mulato and the deep-rooted legumes Centro and Clitoria, is a promising
strategy for year-round feed supply to smallholder dairy cattle in Central and East Africa. The income
foregone from the additional area sown to pasture must be taken into consideration in assessing the
protability of this practice.
106
7.2: Homecoming of Brachiaria: Improved hybrids prove useful for African animal
agriculture
Brigitte L. Maass,1* Charles A.O. Midega,2 Mupenzi Mutimura,3 Volatsara B. Rahetlah,4
Paulo Salgado,5 Jolly M. Kabirizi,6 Zeyaur R. Khan,2 Sita R. Ghimire,7 and Idupulapati M. Rao,8
1 CIAT (International Center for Tropical Agriculture), PO Box 823-00621, Nairobi, Kenya
2 icipe (African Insect Science for Food and Health), PO Box 30772-00100, Nairobi, Kenya
3 RAB (Rwanda Agriculture Board), PO Box 5016, Kigali, Rwanda
4 Centre de Développement Rural et de Recherche Appliquée, BP 198, Antsirabe 110, Madagascar
5 CIRAD, UMR SELMET, Mediterranean and Tropical Livestock Systems, 7 Chemin Irat, Ligne Paradis,
97410 Saint-Pierre, La Réunion, France
6 NaLIRRI (National Livestock Resources Research Institute), PO Box 96 Kampala, Uganda
7 BecA (Biosciences in Eastern and central Africa) Hub/ILRI, PO Box 30709-00100, Nairobi, Kenya
8 CIAT (International Center for Tropical Agriculture), AA 6713, Cali, Colombia SA
Background
Species of the genus Brachiaria originate primarily from eastern, central and southern Africa, where
they are natural constituents of grasslands (Boonman 1993). The largest impact of Brachiaria in
agriculture, though, is in the Americas, especially in Brazil. Due to their adaptation to acidic, low-
fertility soils, an estimated 99 million hectares of Brachiaria species have been sown in Brazil alone
as improved pastures (Jank et al. 2014). This refers especially to B. brizantha cv. Marandu and B.
decumbens cv. Basilisk.
Despite Africa being their center of origin and diversity, Brachiaria species had not been selected
for pasture improvement in eastern Africa, when grassland research was most active in the 1960s
and 1970s (Boonman 1993). The then available commercial cultivars of B. brizantha, B. decumbens, B.
ruziziensis and B. humidicola were evaluated in small-plot agronomic trials in western and central
Africa in the 1990s (Ndikumana and de Leeuw 1996). However, none of them appears to have found
its way into commercial agriculture at a signicant scale in any African country (Boonman 1993).
Only Congo Signal grass (B. ruziziensis, K5832 ) has been used as a cultivated grass in some areas of
Congo (DRC, formerly also Zaïre), Uganda and Kenya according to Boonman’s (1993) review. This
nutritious and persistent grass has been in commercial seed multiplication since 1960.
Brachiaria improvement in the Americas
Due to the susceptibility to spittlebug insect pests of B. decumbens in the Americas, CIAT in Colombia
and EMBRAPA in Brazil initiated breeding programs in the late 1980s (Miles et al. 2004). Accessing
useful resistance genes for cross-breeding was a particular challenge due to the apomictic nature of
the grass. This was only made possible by applying modern biotechnological tools then available
(Miles et al. 2004). The rst inter-specic hybrids from CIAT’s Brachiaria breeding program (cv.
Mulato und cv. Mulato-II) were released in the Americas in early and mid-2000s by Grupo Papalotla
(Table 7.2.1). Since 2012, cv. Cayman – as a plant with higher waterlogging tolerance – has been made
commercially available by Grupo Papalotla (Pizarro 2013), and the new, relatively taller cv. Cobra
that is more suitable for cut-and-carry will be soon on the market.
107
Table 7.2.1: Commercially available hybrid Brachiaria cultivars
Cultivar name CIAT ID Special characteristics Country, year of variety
protection (rst release)
Reference
cv. Mulato CIAT 36061 Spittlebug-resistant, high forage yield
and nutritive quality, poor seed ll
Mexico, 2004 (2001) Argel et al. 2007;
Miles et al. 2004
cv. Mulato-II CIAT 36087 Spittlebug-resistant, high forage yield
and nutritive quality, good seed yield
Mexico, 2007 (2005) Argel et al. 2007
cv. Cayman BR02/1752 Higher tolerance to water logging
than other hybrids
Mexico, 2013 (2012) Pizarro 2013
(cv. Cobra) BR02/1794 Relatively taller than other hybrids,
suitable for cut-and-carry
Mexico, 2013 Pers. comms. E. Stern, M.
Peters – cv. name not yet
ofcial
These interspecic hybrids originate from crosses between two (B. ruziziensis x B. brizantha) or three
Brachiaria species (B. ruziziensis x B. decumbens x B. brizantha) and subsequent screening conducted
by CIAT’s Tropical Forages Program in Colombia (Argel et al. 2007). Being apomictic hybrids (i.e.,
reproducing asexually by seed), these cultivars are true-breeding and will not segregate from one
generation to the next.
Commercialization of hybrid Brachiaria
In 2000, the Mexican seed company Grupo Papalotla/Tropical Seeds entered into agreement with CIAT
for 10 years, for obtaining rights to commercialize CIAT hybrid Brachiaria cultivars by receiving rst-
generation hybrids bred during that period for further evaluation and determination of their possible
commercial value. Papalotla is paying royalties for protected and commercialized cultivars during
protection duration (E. Stern, pers. comm. 2013). After expiry of protection 15 years from rst sale,
according to the International Union for the Protection of New Varieties of Plants (UPOV), cultivars
will pass into the public domain and no other right may prevent free use. Global variety protection
for the released cultivars has been obtained in Mexico (Table 7.2.1). While Grupo Papalotla/Tropical
Seeds has been marketing the seeds directly in the Americas, so far the Australian company Heritage
Seeds has been responsible for countries of Oceanea, Asia, and Africa. Commercial seed production
of the hybrids at low latitude in the tropics was a major challenge. Therefore, Papalotla transferred
seed production of cv. Mulato-II to sites of higher latitude (≥15 °N) in Mexico and Thailand, from
where most exports have been realized (Hare et al. 2009).
This study reviews research, development and incipient uptake of new hybrid Brachiaria cultivars in
Africa in order to document the existing knowledge on their current use.
Hybrid Brachiaria in Africa
The rst cultivars released from CIAT’s breeding program, cv. Mulato and cv. Mulato-II, have likewise
been researched and distributed in Africa. Seed sales (2001-2013) by Grupo Papalotla/Tropical Seeds
to African countries (pers. comm. M. Peters) suggest that an area of at least 1,000 ha has been sown
hitherto.
The new hybrid Brachiaria cultivars have been distributed since 2001 to Eritrea, Ethiopia, DR Congo,
Uganda, Rwanda, Burundi, Kenya, Tanzania, Malawi and Madagascar according to combined
information from seed sales and published research. While the largest share of known commercial
seed sales of hybrid Brachiaria cultivars went to Kenya, this only reects the fact that a big project is
being conducted from Kenya (ADOPT – see further details below), from where the seed is further
distributed to participants in Ethiopia and Tanzania.
108
Key ndings from both on-station and on-farm research and develop¬ment, emphasizing agro-
ecological adaptation of the plants and their acceptability for farmers, are described below.
Small-scale agronomic and participatory evaluation
Rwanda. During participatory research with farmers on sites with low rainfall and acidic soils in 2007
funded by BMZ-GIZ, Germany, cv. Mulato-II was preferred because of producing green forage all
year round without any fertilizer input, high above-ground biomass production, palatability, drought
tolerance, quick regrowth, persistence, being a perennial and easy for cut-and-carry (Mutimura et
al., 2012). Therefore, cv. Mulato-II is considered an excellent alternative to traditional Napier grass
(Pennisetum purpureum) predominantly used in zero-grazed dairy systems of the region. Napier
grass, though, has been widely suffering from Napier stunt disease and smut that both decrease
severely herbage production and, thus, put dairy-dependent livelihoods at risk (Khan et al. 2014b).
More than 150 individual farmers and over four farmer cooperatives are now using cv. Mulato-II as
erosion control on contour bunds, livestock forage and hay-making for income generation. Currently,
>50 ha are planted with cvs. Mulato-II, Marandu and Basilisk to increase planting material in order to
satisfy the high demand in the country.
Kenya. The Kenya Agricultural Research Institute (KARI) set up small-plot agronomic experiments
in several KARI research stations throughout the country in order to compare the performance of cv.
Mulato-II with other available grasses and to assess its agro-ecological adaptation (D. Njarui, pers.
comm. 2011). At KARI-Kiboko Research Station, cv. Mulato-II was found superior to native range
grasses such as buffel (Cenchrus ciliaris) and horsetail grass (Chloris roxburghiana) in both primary
dry matter production and subsequent regrowth (Machogu 2013). It also had higher nutritive quality,
especially in terms of high DM digestibility (65%) assessed in 12-week-old plants, whereas crude
protein content (13.3%) was similar to that of the other grasses. While this trial was conducted with
irrigation until 16 weeks after sowing, cv. Mulato-II in another rainfed trial at Kiboko was heavily
infested by red spider mite and both biomass production and plant survival were hampered by
drought.
Eritrea. Wolfe et al. (2008) evaluated cv. Mulato at two agricultural research stations in Eritrea, Halhale
in the Central Highlands and Shambuko in the Western Lowlands, from 2006 to 2007 and found it
was among the most promising grasses in Halhale.
Eastern Democratic Republic of the Congo (DRC)
Both cv. Mulato and Mulato-II were introduced to assess their agro-ecological adaptation in Sud-
Kivu province of DRC. Small plots for agronomic evaluation were established at the INERA (Institut
National pour l’Etude et la Recherche Agronomiques) Research Station in Mulungu and on farmers’
elds in Kabare and Walungu ‘groupements’. Cv. Mulato was also evaluated when planted on contour
bunds for erosion control within CIALCA (Consortium for Improving Agriculture-based Livelihoods
in Central Africa) (B.L. Maass, unpubl.). Unfortunately, the plants became so severely diseased that
evaluation was disrupted and plots abandoned. Not only symptoms of fungal diseases (e.g., rust –
probably caused by Uromyces setariae-italicae Yosh – and anthracnose) were found, but also of mites
(H. Maraite 2010, pers. comm.). J. Linné (2010, pers. comm.) explained this undue susceptibility of
hybrid Brachiaria as a re-encounter phenomenon induced by returning plants (hosts) selected under
completely distinct biotic challenges back to the species’ centers of origin and, consequently, center of
diversity also of its diseases and pests.
109
Systems integration
Dairy production systems in Uganda. Cv.
Mulato was introduced as an alternative to Napier grass, the predominant forage for dairy cattle
in zero-grazing systems (Kabirizi et al. 2013). After initial on-station and further participatory on-
farm evaluation in Masaka district, incipient uptake of cv. Mulato took place (Mugerwa et al. 2012).
Demand for cv. Mulato has been increasing since (Kabirizi et al. 2013). Mainly in smallholder dairy
systems, cv. Mulato is being used for cut-and-carry together with legumes like Clitoria ternatea or
Centrosema molle (Kabirizi et al. 2013). Cv. Mulato along with other grasses like B. brizantha cv.
Toledo is now being promoted by NGOs such as ‘Send a Cow’ (Kato 2011). It is recommended to feed
drought-tolerant cv. Mulato with a forage legume during the dry season, when Napier grass mono-
crops are disadvantaged due to drought, Napier stunt disease and/or poor agronomic practices
(Kabirizi et al. 2013). As no seed is available commercially, farmers, even with only small plots,
sell vegetative planting material (splits) (B.L. Maass unpubl.). This, hence, creates small-scale agro-
business opportunities, especially for women. In the more sub-humid area around Jinja, cv. Mulato
also appears to be an ideal solution for grazing of calves due to its relatively high nutritive quality (R.
Jones, pers. comm. 2014).
The push-pull-system in Kenya, Tanzania and Ethiopia
The largest uptake of hybrid Brachiaria cv. Mulato-II is currently taking place in eastern Africa, where
the grass is used as a trap plant in the push-pull system that helps control maize stem borers and the
parasitic weed, Striga hermonthica (Khan et al. 2014). The push-pull-system has been developed and
promoted by the International Centre of Insect Physiology and Ecology (icipe) (Khan et al. 2014). This
smart technology successfully harnesses agro-biodiversity. Initially, its components included Napier
grass and Silverleaf desmodium (Desmodium uncinatum). However, on the systems’s niche to semi-
arid lands (500-700 mm rainfall p.a.), cv. Mulato-II has been identied as a new trap crop together
with Greenleaf desmodium (D. intortum) as the intercrop; both are currently being disseminated. The
two components are more drought-tolerant than the traditional ones, and their seed is commercially
available. In addition, hybrid cv. Mulato-II Brachiaria is resistant to Napier stunt disease. About
15,000 smallholder farmers beneting from the ADOPT project in Kenya, Tanzania and Ethiopia
have already planted cv. Mulato-II (C. Midega, unpubl.). Farmers in Kenya claimed that their milk
production has doubled due to the availability of the improved grass and Greenleaf desmodium.
They prefer cv. Mulato-II over Napier grass for several reasons: it is highly palatable for livestock,
easier to handle as cut-and-carry and for making hay to be used during the dry season. As the push-
pull-system has been developed to control maize stem borer, thus far little attention has been paid to
the possible importance of livestock production improvements for the uptake and further spread of
the technology.
Conservation agriculture and dairy systems in Madagascar. In Madagascar, cv.
Mulato has been tested for soil structure improvement, high biomass production and carbon
accumulation in the soil by its root system as a rst step to prepare for direct seeding on compacted
soils (conservation agriculture). However, the systems did not spread as they require herbicides for
grass control, which are not easily accessible in Madagascar (O. Husson pers. comm. 2013). On the
other hand, in dairy production systems in the highlands, specically in the Vakinankaratra region,
almost 20 ha were planted with cv. Mulato in 2011 (V.B. Rahetlah unpubl.). Owing to its better
palatability and higher biomass yield as compared with other Brachiaria spp., cv. Mulato has been
rapidly adopted by small-scale dairy farmers. It is mainly grown for green forage production under
cut-and-carry systems during the warm and rainy season extending from November to April.
110
Research and development of new hybrid Brachiaria for Africa
Despite all the enthusiasm and demand in the region, Mulato-II seed is not yet available on the
African market, except for experimental purposes. Therefore, Papalotla has requested varietal
release from Kenyan authorities, possibly being granted later in 2014. A new research project led
by the Biosciences eastern and central Africa (BecA)/ILRI-Hub that, among other outputs, focuses
on integrating improved Brachiaria grasses into mixed smallholder crop-livestock systems, while
considering climate-relevant effects on the environment (Djikeng et al. 2013), will most likely push
further the adoption of hybrid Brachiaria in the region.
Outlook
Apparently, hybrid Brachiaria has a role to play in improving African animal agriculture. Yet, new
pest and disease challenges have emerged that require further research attention. On the other hand,
an array of diverse hybrids is still in the pipeline for release (Pizarro et al. 2013; E. Stern, pers. comm.,
2013); some of these new materials may better address the specic biotic and abiotic challenges
identied as well as the requirements for particular production systems in African locations. In
order to maximize benets for smallholder farmers and deploy the new hybrid Brachiaria cultivars
effectively, the following research needs and opportunities have been identied:
(a) Researchable knowledge gaps (e.g., agronomy of system-integration, value for animal
production in crop-livestock systems, socio-ecological niche – considering gender and
economics, adoptability by smallholder farmers);
(b) Upcoming research needs (e.g., biotic challenges, such as red spider mite, sorghum shoot y,
fungal diseases; possible seed production on the continent); and
(c) Research and development opportunities (e.g., testing advanced hybrids under biotic
and abiotic stress as well as in representative African production systems, tting the right
cultivars into different production systems and further develop their agronomy).
Brachiaria, so far neglected grasses on their continent of origin, have not only come home in the form
of improved hybrids, but they have been very welcome by African farmers.
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Hare MD, Tatsapong P, Phengphet S (2009) Herbage yield and quality of Brachiaria cultivars,
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Kabirizi J, Ziiwa E, Mugerwa S, Ndikumana J and Nanyennya W (2013) Dry season forages
for improving dairy production in smallholder systems in Uganda. Tropical Grasslands-Forrajes
Tropicales 1(2): 212-214.
Khan Z.R., Midega C.A., Pittchar J.O., Murage AW, Birkett MA, Bruce TJ and Pickett JA (2014)
Achieving food security for one million sub-Saharan African poor through push–pull innovation by
2020. Philosophical Transactions of the Royal Society B: Biological Sciences 369(1639): 20120284
Miles JW and Escandon ML (1997). Further evidence on the inheritance of reproductive mode
in Brachiaria. Canadian Journal of Plant Science 77(1): 105-107.
Mutimura, M., and T. Everson. 2012. On-farm evaluation of improved Brachiaria grasses in
low rainfall and aluminium toxicity prone areas of Rwanda. International Journal of Biodiversity and
Conservation 4(3): 137-154.
Ndikumana, J. and de Leeuw, P.N. 1996. Sustainable Feed Production and Utilization of
Smallholder Livestock Enterprises in Sub-Saharan Africa. Proceedings of the Second African Feed
Resources Network (AFRNET), Harare, Zimbabwe, from 6th to 10th December 1993. AFRNET
(African Feed Resources Network), Nairobi, Kenya. pp. 5-9.
Pizzaro E,A. , Michael D. Hare, B., Mpenzi Mutimura. and Bai Changjun, D. 2013.
Brachiaria hybrids: potential, forage use and seed yield. http://www.tropseeds.com/wp-content/
uploads/2013/01/Brachiaria-Hybrids-potential-forage-use-and-seed-yield.pdf.
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7.3 Losses due to Napier Stunt Disease and the impact of promoting alternative forages in
smallholder dairy systems in Uganda
1Nanyeenya, N.W., 1Kabirizi.J.M ., 1Namagembe. A1., 1Namazzi C., and21Sali.A.L
1National Livestock Resources Research Institute (NaLIRRI), P.O. Box 96, Tororo, Uganda
2National Crops Resources Research Institute (NaCRRI), P.O. Box 7084, Kampala, Uganda
Introduction
In Uganda agriculture contributes up to nearly 20 percent of GDP, and accounts for 48 percent of
exports. The livestock sub-sector contributes about 5.2% and 19% to total GDP and agricultural GDP,
respectively. The dairy industry is estimated to contribute about 40 to 50% of the livestock GDP
(MAAIF, 2011). This implies that the dairy industry contributes about 50% of the total output from the
livestock sub-sector. It employs many people that are involved in various economic activities such as
milk production, collection, transportation, processing, distribution and marketing as well as provision
of inputs and support services (Dairy Development Authority - DDA, 2008). Sustainable agricultural
development depends on appropriate, efcient and effective technologies and innovations. In
addition, farmers adopt new technologies that are economically superior to the existing ones. Before
changing from one production method to another, farmer consider many factors including agro-
ecological requirements, availability of required additional production resources (labor, investible
cash, skill, farmland and equipment), additional costs, and additional income resulting from the
change. Besides they also consider the technology in respect of socio-cultural circumstances, goals,
and the whole farming system compatibility. Farmers will therefore consider the implication of the
proposed technological change on farm costs and incomes. They will seek to nd answers to the
following question. Will the extra income earned by changing to the new technology justify the
extra cost? One of the tools in economics used to compare the economic benets of technologies is
farm budget analysis. A budget is a farm management method that is intended to assist researchers,
extension workers, and farmers in the decision-making process. It is a hence a decision-support tool
that quanties and compares the effects of a proposed technologies farm protability. Partial budget
analysis shows the level of protability of and helps to decide whether to adopt a new technology or
not. A budget is a formal quantitative expression of plans on production inputs and output. Budgets
indicate the type, quality, quantity and cost of production resources or inputs needed, and the type,
quality, quantity and value of output or product obtained. An enterprise budget considers all income
and costs of a specic enterprise to provide an estimate of its prot. According to Orodho, 2006 the
major cattle feed are natural grass and planted fodder, mainly Napier grass (Pennisetum purpureum).
The major constraining factors are: lack of adequate and quality feeds particularly in the dry season,
animal genetics and disease challenges on livestock and on Napier grass which is the major livestock
feed. The napier disease is much more severe and prevalent in poorly managed elds and farmers
have noted that in well-weeded and heavily manured elds, disease severity is reduced.
Napier (elephant grass) was infested by a disease about 13 years ago. This disease was later conrmed
to be Napier Stunt Disease (NSD) (Nielsen et. al., 2007). The disease was rst observed on farmers’
elds in Masaka district in 2000. This disease has decimated Napier fodder crop to the extent that
in some cases farmers have lost up to 100 per cent economic biomass (Kabirii et al., 2007). Often the
whole the stool is affected with NSD and this may lead to complete loss in yield and eventual death.
Mubiru et al., 2011 observed that a common challenge that dairy farmers in Uganda face is low milk
production. The current average yield is approximately 2400 kg per cow per lactation from cross-
bred (Holstein Friesian S - East African Zebu) cows, which is only about 50% of their milk production
potential. Milk production from dairy cattle is low in some cases ranging from 2-5 litres per cow per
day (Mubiru et al., 2003).
112
The Livestock nutrition Program of NaLIRRI is currently addressing the constraint of NSD through a
range of interventions. There has not been any assessment of the effects of NSD to small scale dairy
keepers, non-cattle farmers selling Napier forages and temporal stability in small scale dairy feed
resource availability. Besides, Brachiaria is being promoted to compensate for the lost biomass and
incomes due to effects of NSD on Napier. A study was conducted to quantify the negative effects of
NSD to dairy based livelihoods.
Methods
Study area and sampling procedure methods of data collection and analysis
The study was conducted in Masaka and Wakiso districts. Masaka district is bordered by Sembabule
in the North West, Mpigi district in the North, Rakai district in the west and south and Kalangala
District in the East. The District Headquarters is 120 km from Kampala. Masaka district has a
population of 831,300 people with 420,000 females and 411,300 males. The population of is basically
rural, with 754,000 rural dwellers and 77,300 urban dwellers. The major economic activity in Masaka
District is agriculture with major crops being bananas, pineapples, and tomatoes), cash crops and
coffee cotton integrated with livestock notably dairy and multipurpose local cattle, goats, pigs and
chickens. The district lies in the Lake Victoria crescent agro-ecological zone and has a mix of peri-
urban and rural settings with both densely and sparsely populated sub-zones. Dairy production
ranges from extensive communal grazing of composite village herd and tethering dominated by local
zebu cattle, perimeter fenced farm with a mix of low grade crosses and local breeds to semi-intensive
and intensive (paddock fenced and stall fed) systems rearing mostly high grade crosses and exotic
dairy breeds (Nanyeenya, 2008). Wakiso district lies in the Greater Kampala peri-urban zone. The
effects of NSD was assesd in Masaka district where households sampled were drawn from Kitenga,
Bukulula, Lusango and Kabonera. In Wakiso district, the study was conducted to document and
evaluate challenges and benets of adoption and integration of brachiaria in the small holder systems
households covered were located in Buso, Namulonge and Kiwenda
Study respondents were selected purposive and snowball sampling procedures. All farmers selected
intensively managed their cattle through stall feeding and semi-intensive management systems. All
project intervention farmers (10 each for NSD tolerant clones and Brachiaria seed multiplication)
were selected. Each of these named two other farmers to whom they have disseminated the planting
materials given to them. In addition ve dairy keepers in each of the study areas were identied
and interviewed. In total 35 households were covered per district. Data were collected using semi-
formal and formal approaches in each of the two sites based on formal survey techniques using direct
interviews supported by standard questionnaires and Systematic Client Consultation (SCC) using
check-lists. Data were analysed using enterprise and partial budgeting techniques. One of the most
basic and important production decisions is choosing the combination of products or enterprises to
produce. An enterprise is dened as a single crop or livestock commodity that actually produces a
marketable product. An enterprise budget is a listing of all estimated income and expenses associated
with a specic enterprise to provide an estimate of its protability. The effects of integration of
Brachiaria forage seed production into existing farming systems were examined using enterprise
budgets. The effects of NSD on dairy enterprise farm performance through resource re-allocation
and cash ow changes were assessed using nancial analysis based on partial budgeting techniques.
This low yield can be attributed to poor cattle nutrition resulting from inadequate feeding. With
improved feeding dairy yields for direct beneciary and secondary beneciary households registered
10.6 and 5.9 litres/cow/day, respectively (Kabirizi et al., 2013).
113
Results and discussion
Findings of the study on effects of promoting Brachiaria forage seed multiplication and NSD on
dairy resource allocation and cash ow due to adjustments in dairy feed management in the pre and
post Napier Stunt Disease (NSD) periods are discussed in this section. Data on enterprise budgets
on Brachiaria Mulato (Table 7.3.1) indicates that dairy farmers who received Brachiaria mulato for
multiplication and integrating it into livestock feed have on average established 0.75 acres, sell up to
230 bags of splits of planting materials to other farmers in a year and fetch net prots of about Uganda
shillings 3.4 million (USD 1360) per acre per annum.
Table 7.3.1: Enterprise budgets on Brachiaria Mulato for cattle and non-cattle households
Gross income Cattle household Non-cattle household
1 Area (acres) 1 1
2A Bags of splits sold season1 (Number) 135 135
2B Bags of splits sold Season2 (Number) 90 90
2C Annual sales (Bags) 230 260
3 Price (Shillings/Bag) 20000 20000
4 Sales revenue (Shillings) (2 x 3) 4600000 5200000
Variable Input costs (Shillings/acre)
5A Bush clearing (Shillings/Acre) 100000 100000
5B Land preparation labour (Shillings/Acre) 120000 120000
6A Quantity of planting material (Bags) 8 8
6B Price of planting materials (Shillings/Bag) 20000 20000
6C Cost of planting materials (Shillings/Acre) 160000 160000
6D Planting and manure application labour (shillings/Acre) 50000 50000
7A Weed control labour (shillings/Acre) 160000 160000
8A Manure - 2 truck loads per annum (Shilllings/Acre) 0 80000
8B Seasonal manure application labour (Shillings/Acre) 80000 80000
9 Harvesting, packing and loading labor (shillings/Acre) 460000 520000
Total variable input costs (Shillings/Acre) 1130000 1270000
Net prot (Shillings/Acre) 3,470,000 3,930,000
Non-cattle households whose elds regenerate faster given that they are not frequently cut to feed
cattle registered net prots of shillings 3.93 million (USD 1572) per acre per annum.
Farmers have indicated that they have been able to use proceeds of Brachiaria income through buying
household assets like chairs, investing in other farm enterprises like vegetable production, maize
and sweet potato growing by especially hiring labour, improved promptness in settling school fees
and others stated that they can now buy building materials in bulk to invest in construction of rental
housing units.
Findings on effects of NSD on dairy farm resource allocation and cash ow are presented in Table 7.3.2.
The disease led to reduction in area under Napier by about 40 per cent. This concurs with Kabirirzi et
al., 2007 who noted that Napier Stunt Disease (NSD) occurred in 97 per cent of farmers’ elds causing
114
Table 7.3.2: Financial analysis of effects of Napier Stunt Disease on resource use and cash ow
Enterprise Resources and Cost Items Quantity/
Value
Change
(%) Added income
+ Reduced Costs
Reduced revenue
+ Added Costs
Napier area (Acres) 1.80 38.00 N/A N/A
Napier Post NSD (Acres) 1.11
Cattle herd size (Number) 4.60 0
Cattle Post NSD (Number) 4.60
Milking cows (Number) 2.40 0
Cows Post (Number) 2.40
Milk/cow/day (Litres/day) 13.95 (18.00) 0 596,800
Milk/cow/day Post NSD (Litres/day) 11.46
Cost of feed Supplements (shillings/day) 1,500.00 193.00 0 870,000
Cost of feed Supplements Post NSD (shillings/
day)
4,400.00
Forage Collection Labour (Person-hours/day) 1.29 43.00 0
Forage Collection. Labour Post NSD (Person-
hours/day)
1.84
Manure Application Cost (Shillings/Per
Annum)
3600 956.00 0 34,400
Manure Application Cost Post NSD (Shillings/
Per Annum)
38,000
Net Financial Effect (Shillings Per Annum) (1,501,200) 80000
Summary, Conclusions and Recommendations
From the ndings of the study it can be concluded that:
a) Both cattle households and non-cattle households were able to obtain reasonable prots
from Brachiaria forage seed sales. They have also variously beneted by improving human
capital, welfare, farm enterprise diversication and other long-term commercial investments
b) Farmers have adjusted to NSD effects but in nancial terms have not fully compensated for
the negative effects of NSD
stunting, curling/twisting of leaf tips leading to up 50 per cent reduction in biomass yield. Contrary
to Orodho, 2006 who stated that many smallholders have lost up to 100 percent of their Napier crop
and are forced to de-stock or sell off their entire herd because of lack of sufcient feeds farmers in the
study area retained their herd sizes (4.6 heads of cattle). They, however, struggled to make up for
the lost biomass due to NSD by stepping up feed supplementation resulting into an increase in cost
of supplements per day by 200 per cent. Time taken to fetch feeds was also greater than before by 43
per cent. As noted y Orodho, 2006, the disease is much more severe and prevalent in poorly managed
elds and farmers have noted that in well-weeded and heavily manured elds, disease severity is
reduced. Similarly farmers in the study area raised the quantities of manure applied per acre by one
tone (1000 Kilograms). This changed the cost of manure application by shillings 34,400 per acre per
annum. These corrective adjustments notwithstanding, milk yields per cow per day dropped about
twenty per cent. The net nancial effect of reduction in milk incomes and added cost resulted in a
negative net nancial effect of about shillings 1,500,000. This implies that the disease led to a nancial
drain equivalent to 54 per cent of the gross revenues from milk. This amount of money can settle
two school fees terms of a child going to elite primary or secondary school or tuition for a university
student for one semester (half of the year).
115
It is recommended that:
a) Brachiaria propagation model explores manure application regimes since the crop is
challenged by frequent cutting and splitting
b) Distribution of NSD tolerant clones should be accelerated so that farmers regain the original
Napier acres and biomass to stabilize dairy revenues and reduce on the high cash outows.
References
Dairy Development Authority - DDA (2008): Overview of the Status and Performance of
Uganda’s Dairy Industry, February 2008
Kabirizi, J., Niellsen, S.L., Nicolasen, M., Byenkya, S and Alacai, T (2007): Napeir stunt Disease
in Uganda: Farmers’ perceptions and impact on fodder production ACSC Proceeding Vol 8 pp 895-89
MAAIF (2011): Ministry of Agriculture Animal Industry and Fisheries Statistical Abstract,
Entebbe Uganda
Mubiru, L. S.., C., Kabirizi, J., Odur, A.G., Nakiganda, A., Ndyanabo, W., Bareeba, F.B.,Halberg,
N., Namagemebe, A., Kayiiwa, S. and Kigongo, J. 2003. “Introduction of improved techniques of feed
resource utilization on smallholder dairy farms in Uganda.” Uganda Journal of Agricultural Sciences
8(10): 383–394
Mubiru S. L., Wakholi, P., Nakiganda, A., Sempebwa, H N., Namagemebe, A., Semakula. J.,
Lule, A and Kazibwe, P (2011): Development of Endiisa Decision Support Tool for Improved Feeding
of Dairy Cattle in Uganda CTA and FARA. 2011. Accra, Ghana, 2011. pp. 45-50.
Nielsen, S.L.; Ebong, C.; Kabirizi J.M. and M. Nicolaisen. 2007. First report of a 16SrXI Group
phytoplasma (Candidatus Phytoplasma oryzae) associated with Napier grass stunt disease in Uganda.
New Disease Reports. Volume 14. (http://www.bspp.org.uk/ndr/).
Orodho A.B. (2006): The role and importance of Napier grass in the smallholder dairy industry
in Kenya
116
7.4 Production characteristics of smallholder dairy farming in the Lake Victoria agro-
ecological zone, Uganda
1Andrew M. Atuhaire, 1S. Mugerwa. S.; 1Kabirizi, J. M., 2Okello, S.;3Kabi, F.
1National Agricultural Research Institute (NARO), National Livestock Resources Research Institute
(NaLIRRI), P. O. Box 96, Tororo, Uganda
2Department of Livestock and Industrial Resources, College of Veterinary Medicine, Animal Resources and
Bio-security., Makerere University, P. O. Box 7062, Kampala, Uganda
3Department of Agricultural Production, College of Agricultural and Environmental Sciences., Makerere
University, P. O. Box 7062, Kampala, Uganda
Introduction
Smallholder dairy farming system constitutes an important source of livelihoods to the majority of
mixed crop-livestock farmers involved in agricultural production in Uganda (Kabirizi et al., 2006).
While, smallholder dairy farmers make a shift towards market-oriented dairy production, they are
faced with persistent challenges of low productivity, coupled with limited labour inputs. This practice
has condemned smallholder dairy farmers to subsistence production, resulting to low income, low
saving and low investment in the dairy sector, triggering vicious cycle of low inputs, low productivity,
low technology applications and environmental degradation, which translate into abject poverty
(Muia et al., 2011). Uganda’s slow growth in the dairy sector is evidenced by declining production
yields lower than the potential production estimated growth of about 70% (MAAIF, 2010) considering
that over 85% of dairy farmers are smallholders. The annual Gross domestic product (GDP) growth
rate of agriculture in year 2012/13 was 1.4% and unstable (MFPED, 2013), yet population growth is
estimated at 3.2 percent per annum and appears to be on the rise (UBOS, 2012). Therefore, it was
important, to understand production characteristics of smallholder dairy farming so as to
identify their opportunities and strength, and build on their threats and weakness to benchmark
future research processes aimed at extracting famers out of abject poverty and extreme hunger.
Dairy production has become increasingly intensive to cope with nutritional needs of increasing human
population and declining per capita land holding (Lukuyu et al., 2011). This has led to intensication
of smallholder dairy farming adopting stall-feeding (also known as “cut and carry”) where one to
three heads of cattle are fed indoors instead of in-situ grazing (Tibayungwa et al., 2010). Smallholder
dairy farming has become an important source of milk and has created employment for many resource
poor households in Uganda (Kabirizi et al., 2006), partly due to Uganda’s national development plan
(NDP) policy whose objective is to eradicate poverty through agricultural transformation (MAAIF,
2010). Smallholder dairy farming, usually 1 or 2 heads of cattle, has the highest economic
returns compared to other cattle management systems (MAAIF, 2010). However, low productive
performance reduces its protability (Kabi et al., 2013). For example, annual average milk yield per
cow per lactation year of 305 days in developed countries is in excess of 8000 kg, while on smallholder
dairy farm in Uganda it is less than 2000 kg per cow per lactation year [9]. Such low milk productivity
is to a large extent a result of feed scarcity that leads to poor nutrition (Kabi et al., 2013). Smallholder
dairy farming is based on stall feeding as major feeding system, because of its efciency compared to
other feeding systems. However, little information is currently available on production characteristics
of smallholder dairy farming in Lake Victoria Agro-ecological Zone (LVZ), in Uganda.
Moreover, production characteristics of smallholder dairy farming inuence decisions on technology
dissemination for future protability. Since interaction between production and management
revolve mostly around the supply of nutrients and energy through dairy feeds, there is need to
117
characterize smallholder dairy farming system in order to predict their performance and benchmark
strategic research innovations to address declining smallholder dairy farmer productivity. However,
although several studies based on farm characteristics have been conducted among smallholder dairy
farmers; little success has been achieved in extricating them out of the persistent extreme hunger and
poverty. The objective of this study was to characterize smallholder dairy farming system from
farmers’ point of view so that together with scientists the farmers inform the process of identifying
various intervening strategies to develop dynamic optimization interventions aimed at increasing
milk productivity based on the most pressing challenges and un exploited resource endowments
peculiar to each region.
Materials and Methods
Description of the Study Area
Three districts namely Buikwe (0°18’4.32 N and 33°3’6.63 E), Jinja (0°25’28 N and 33°12’15 E)
and Mayuge (0°27’35 N and 33°28’49 E) (Figure 7.4.1) were purposively selected for the study. The
mean daily temperature ranged between
16 - 28 °C, 18 - 28 °C and 17 - 27°C for Buikwe, Jinja and Mayuge Districts, respectively. The mean
annual rainfall ranged between 1279 to 1544 mm, 1200 to 1500 mm and 1100 to 1500 mm for Jinja,
Mayuge and Buikwe, respectively. The three districts are located in Lake Victoria Agro-ecological
Zone (LVZ).
Figure 7.4.1: Map of Uganda showing the study
locations of Buikwe, Jinja and Mayuge districts
The districts experience bimodal rainfall pattern typical often tropics, characterized by two rainy
seasons (March to May and September to November), with two dry spells (December to February
and June to August). The high rainfall puts the region in one of those ecological zones with the
highest potential for crop cultivation, pasture production and intensive livestock, signifying a huge
possibility to integrate crop and smallholder dairy farming for efcient natural resource exploitation
and management. According to the Uganda Population and Housing Census (2002), the estimated
mean population density was 256, 66, and 92.55 people per square kilometre for Buikwe, Jinja and
Mayuge, respectively [5]. Agriculture is the main economic activity, but has of late suffered from
seasonal unpredictable seasons characterized with unprecedented extremes of weather such as oods
and severe droughts that lead to crop failure and increased feed scarcity. The mean agricultural area
is 529, 601.1 and 603.3 km2 for Buikwe, Jinja and Mayuge districts, respectively.
118
Sampling Procedure, Sample Size, Data Collection and Analysis
Three districts were purposively selected based on the reported intensity of smallholder dairy farms
(MAAIF, 2010). A three stage stratied multi-stage cluster sampling procedure was done; the rst
stage involved considering each of the districts as a homogenous group stratum (Domain of analysis).
The second stage involved simple random sampling of three sub-counties per district in consultations
with the district extension staff and sub-county extension ofcers. All the smallholder dairy farmers
in the sampled sub-county were considered. Selection of households was also by simple random.
Sampling sample size was estimated using the following formula (Israel, 2009)
where n = Sample size, Zα/2= Condence interval at 95% (Standard value of 1.96) p =
10% of proportion of smallholder dairy farmers in LVZ, Uganda (UBOS, 2012) and e
= desired levels of precision at 5%.
The chosen sample required then 14 respondents in each study site which was a sub-county totaling
to 42 respondents per district 81 men and 45 women participated. Altogether, 81 men and 45
women participated in the three districts. Data was obtained using structured and semi- structured
questionnaires administered by way of one-on-one direct interviews. Focus group discussions (one
per sub-county) were also held to corroborate the information gathered in direct interviews. The
questionnaires and focus group discussions were intended to capture information on production
characteristics on smallholder dairy farms. The data captured was on household demographics,
highest education level of household head, major sources of income into household, herd size,
general challenges and available feed resources, labour activities and challenges in milk marketing.
In order to establish differences among farmers’ ranking of the different variables, farmers’ responses
were pooled and subjected to nonparametric statistics analysis (Kruskal – Wallis one-way analysis of
variance) (XLSTAT., 2013). Variables were ranked by farmers using a scale of 1 to 5 with ve being
the most important factor. The computed mean of ranks were compared using multiple pair-wise
comparisons to establish if there were signicant differences in variables (Dunn , 1964). XLSTAT
(2013) was used to generate summary statistics (frequencies, percentages and means) for the variables
and later tabulated. Means of ranks of variables were analyzed using Chi square and were considered
different at P<0.05.
Results
Household Demographics
Household demographics led into understanding of farming decisions, choice and levels of adoption
of agricultural technologies in smallholder dairy farming system (Njarui et al., 2011). Across
the household stratication, the majority of smallholder households in Lake Victoria
Agro-ecological Zone (LVZ) were headed by males (Table 7.4.1). Household head is that person in
the household who takes the overall social and economic decisions, assigns responsibilities, allocate
resources and shoulders all the challenges and threats in the household. Besides, a household
is dened as a group of persons who live and have meals together (UBOS, 2012).
)1(
2
2
2
pp
e
z
n−=
α
119
The proportion of the female-headed households was higher in Jinja than in Mayuge and Buikwe
districts. The age range of household heads was between 37 to 60 years indicating socially active
middle aged strong household heads with high energy levels of ambitions, expectations and high
ability to take risks on investment for increased productivity. There was big range of variation in
farming experience ranging between 2 to 20 years. The more years a household had in dairy farming,
the more experienced and skilled it was in managing dairy cattle for improved productivity.
Typically, household members comprised of husband, wife and children (Table 7.4.1). The household
membership ranged from 4 to 9 members which directly impact on labour input availability in
smallholder dairy farming system.
Education Level
The education level of the household heads in smallholder dairy farming system was relatively
high in the study districts with majority having attained primary seven and above (Figure 7.4.2).
Table 7.4.1: Household demographic prole of the smallholder dairy farmers in Lake Victoria
agro-ecological zone, Uganda
Household characteristics Buikwe (n = 42) Jinja (n= 42) Mayuge (n=42)
Female headed, % 28.57 66.67 30.95
Male headed, % 71.43 33.33 69.05
Average age of household head (years) Mean± SD
51 ± 9 51 ± 9
48 ± 11 48 ± 11
50 ± 9 50 ± 9
Average household size (persons) Mean± SD 6 ± 2 5 ± 1 6 ± 3
Dairy cattle farming experience (years) Mean± SD 10 ± 8 12 ± 8 11 ± 7
Figure 7.4,2: The highest level of education of the household heads in the smallholder dairy farming system in Lake Victoria
Agro-ecological Zone, Uganda
Source of Income of Household Heads
There were variations in major sources of income of household heads between the three districts. The
highest percentages of household heads in Jinja district were full time farmers (68.24%) compared
with Buikwe (35.73%) and Mayuge (45%) where over 52.9% of household’s heads were engaged in
other businesses and employment apart from farming as indicated as in Figure 7.4.3.
120
Figure 7.4.3: The major sources of income of household heads of smallholder dairy farmers in
Lake Victoria Agro-ecological Zone, Uganda
Herd size and structure on smallholder dairy farms
Smallholder dairy households in the districts of Buikwe had a relatively larger dairy herd size
(4.29 ± 0.86) compared to Jinja and Mayuge districts with herd size (3.12 ± 1.45 and 2.43 ± 1.12),
respectively (Table 7.4.2). Cows constituted the highest proportion (48.3%) of the herd in Buikwe
followed by heifers (22.34%). Smallholder dairy farmers in LVZ kept bulls for breeding purposes
because articial insemination services were reported to be unreliable.
Table 7.4.2: Mean ± SD dairy herd structure among smallholder dairy farmers in Lake
Victoria agro-ecological zone, Uganda
Heard structure Mean number
Buikwe Jinja Mayuge SEM
Mature Bulls 1± 0.00 1 ± 0.00 1 ± 0.00 0.00
Cows 2.05 ± 0.44 1.14 ± 0.35 2.14 ±0.01 0.67
Heifer 1.02 ± 0.16 1.00 ± 0.00 1.00 ± 0.00 0.11
Male calves 1.00 ± 0.00 1.00 ± 0.00 1.00 ± 0.00 0.00
Female calves 1.15 ± 0.37 1.00 ± 0.00 1.00 ±.0.00 0.29
Farmers ranking on challenges in smallholder dairy farming system
The farmers’ ranking of the challenges facing smallholder dairy farming system in LVZ is as presented
in Table 7.4.3. Chi square analysis showed that challenges in smallholder dairy farming system are
highly signicant p<0.0001 in all the districts. Feed scarcity which was highly pronounced during the
dry season was unanimously ranked as the major challenge in all the three districts by farmers as one
of the biggest challenge to productivity in smallholder dairy farming system in LVZ, Uganda.
121
Table 7.4.3: Smallholder dairy farmers ranking of challenges in Lake Victoria Agro-
ecological Zone
District Variable Sum of ranks Mean ranks Rankings (Chi2, df =4 , p = 0.001)
Buikwe
Feed scarcity 2817.00 93.9c1 47.62
Lack of basic knowledge 2304.00 76.8bc 2
Livestock health 2037.00 70.24bc 3
Limited Labour 1052.50 47.84ab 4
Limited land 567.50 27.02a5
Jinja
Feed scarcity 1587.50 72.16b1 46.14
Livestock health 1217.50 55.34b2
Limited land 1173.50 53.34b3
Limited Labour 372.50 24.83a4
Lack of basic knowledge 305.00 20.33a5
Mayuge
Feed scarcity 2659.00 91.69c1 45.56
Livestock health 2114.00 72.89bc 2
Lack of basic knowledge 1929.50 68.91bc 3
Limited Labour 1019.50 46.34ab 4
Limited land 534.00 26.70a5
The current feeding regimes of dairy cattle in smallholder dairy farming system in LVZ is highly
dependent on natural pastures and elephant grass as fodder only and alone they cannot lend
themselves as good dairy cattle feed for balanced nutrition of high milk producing dairy cattle.
Farmers Ranking on Challenges in Smallholder Dairy Farming System
The farmers’ ranking of the challenges facing smallholder dairy farming system in LVZ is presented in
Table 7.4.4. Chi square analysis showed that mean ranks of challenges faced within smallholder dairy
farming system signicantly varied (p<0.0001) in all the districts. Feed scarcity which was highly
pronounced during the dry season invariably topped the challenge rank and it was unanimously
ranked as the major challenge in all the three districts by farmers as one of the biggest challenge to
productivity in smallholder dairy farming system in LVZ, Uganda.
The current feeding regimes of dairy cattle in smallholder dairy farming system in LVZ is highly
dependent on natural pastures and elephant grass as fodder. However, feeding elephant grass and
natural pastures without supplementation cannot lend itself into a good dairy cattle feeding practice.
Natural pastures and elephant grass if fed as sole feed resource would never meet the nutrition
requirements of high milk producing dairy cattle.
Farmers Ranking on Feed Resource Utilization in Smallholder Dairy Farming System
Chi-square test showed that there was a signicant difference (p = 0.0001) among farmers’ ranking
on availability of different feed resources in LVZ. The signicant differences in farmers’ ranking on
levels of availability of feed resources were maintained among the districts (Table 7.4.4).
122
Table 7.4.4: Smallholder dairy farmers ranking of feed resources utilization in Lake
Victoria agro-ecological zone
District Feed resources Sum of ranks Mean of ranks Ranking (Chi2, df=4 p-value)
Buikwe
Natural pastures 4865.5 121.6c 1 28.28, p < 0.0001
Crop residues 4797.0 119.9c 2
Legumes 4102.5 105.2bc 3
Fodder pastures 3235.5 83.0ab 4
Agro-industrial by-products 2700.5 67.5a 5
Jinja
Natural pastures 2603.0 76.6a 1 9.53, p = 0.049
Agro-industrial by-products 2700.5 67.5a 2
Crop residues 1350.0 64.8a 3
Fodder pastures 1343.5 58.4a 4
Legumes 1264. 50.6a 5
Mayuge
Natural pastures 4643.0 129.0b 1 47.76, p < 0.0001
Crop residues 4133.0 114.8b 2
Agro-industrial by-products 2741.0 76.1a 3
Fodder pastures 2458.0 68.3a 4
Legumes 2315.0 64.3a 5
Farmers’ ranking on utilization of natural pastures was ranked highest in all the districts of Buikwe,
Jinja and Mayuge with mean rank of 121.6, 76.6 and 129.0, respectively. In Jinja district, smallholder
farmers ranked agro-industrial by-products as immediate alternative (mean ranks = 67.5). Farmers
ranked utilization of crop residues as a second alternative in Mayuge and Buikwe (Mean rank = 114.8,
119.9) respectively. The farmers reported that utilization of natural pastures is limited to wet seasons.
It was further identied that milk uctuations in wet season and dry season in smallholder dairy
farming system was because of high dependence on natural pastures that depend on natural rains/
seasons. Other feed resources utilized were fodder pastures and legumes. The high cost of commercial
feeds affected its utilization which was attributed to limited investment by entrepreneurs in value
addition to the abundant agro industrial by-products. The ndings are in line with [6] who identied
poor livestock nutrition, lack of basic knowledge as well as unfair balance of trade in smallholder
farms as the important challenges that require urgent attention.
Availability of Labour in Smallholder Dairy Farming
The activities performed in the smallholder dairy cattle farming system in LVZ, Uganda are shown
in Table 7.4.5. Most of these are performed daily, indicating that smallholder dairy farming is labour
intensive system. There were no distinct age and sex division of labour, but all gender contributed
to all farm activities. However, there were disparity in level of labour contribution between men,
women and children for activities related to dairy production. In Buikwe and Mayuge on average,
men contributed more labour (41.4 and 40.9%, respectively) in the dairy unit than women (22.1 and
24.1%, respectively). Women’s labour activities were highest in shade cleaning than in any other
activity while men’s highest labour activities were in chopping and feeding, milking, marketing of
milk and spraying against ticks as indicated in Table 7.4.5.
123
In general, women tended to contribute highest to activities that did not directly involve money
transactions while men mainly concentrated on tasks that immediately generated income. Irrespective
of whether dealing with more pastures urban or rural districts, milking and marketing of milk was
preserved for men while cleaning the shed was an activity for women. In Jinja, labour activities to the
dairy units were carried out mainly on hired labour.
Challenges of Milk Marketing in Smallholder Dairy Farming System
Chi-square test showed how farmers ranked the challenges associated with raw milk marketing in
LVZ in the three districts (Table 7.4.6). Poor price was the top most challenge identied by the farmers
while unstable price of milk was ranked the second major challenge in all the districts all the districts
(Table 7.4.6). Limited value addition to the highly perishable milk rendered it rather difcult to fetch
reasonable prices despite its high local demand at the farms. Instability in milk price proves the high
dependence on natural pastures as source of nutrients, which was dependent on weather situation.
Generally, during the wet season, there was improved feed availability leading to increased milk
output per household that would result into reduced milk prices, while in the dry season milk output
was low resulting in increased prices.
Table 7.4. 5: Labour activities in smallholder dairy farming system of Lake Victoria
Agro-ecological Zone, Uganda
Activity Number of individuals performing the activity %
Buikwe Jinja Mayuge
W H C HR W H C HR W H C HR
Garden preparation and crop
planting
52 21 10 17 63 9 7 21 69 5 8 18
Harvesting and transportation of
feed
11 41 14 34 16 23 8 53 19 25 1 55
Chopping and feeding 8 54 7 31 8 38 4 50 5 35 6 64
Water collection and watering
animals
47 12 13 28 18 9 6 67 22 26 0 52
Shed cleaning 48 10 10 32 42 8 4 46 51 5 4 40
Milking 2 66 14 18 5 34 5 56 9 77 2 12
Marketing 2 66 14 18 5 34 5 56 9 77 2 12
Spraying the animals 7 61 14 18 5 34 5 56 9 77 2 12
Average 22.1 41.4 12 24.5 20.2 23.6 5.5 50.6 24.1 40.9 3.1 33.1
124
Discussion
Demographic Characteristics of the Households
The possible explanation of proportion of higher female households heads in Jinja district than in
other districts of Buikwe, Mayuge was because, Non-Governmental Organizations (NGO), “Heifer
Project International”, which operated in the region prior to the study targeted women for economic
empowerment and those who had been widowed by HIV/AIDS for receipt of in calf heifers, hence a
relatively high proportion of women household heads who owned dairy cattle. This is supported by
the fact that the average age of household head in Jinja was lower compared to Buikwe and Mayuge.
Average household members in Jinja were also lower than those in Buikwe and Mayuge respectively.
Typically, household members comprised of husband, wife and children. The size of household
members could inuence labour availability in dairy farming with Jinja having less labour available
to perform dairy activities and relied most on hired labour. Availability of labour in any production
system has a signicant inuence on productivity and since smallholder dairy farming system is
labour intensive (Njarui et al., 2011) labour costs and availability had fundamental inuence on
productivity.
Buikwe district had more farmers who had nished tertiary institutions of learning, suggesting
that adoption levels in Buikwe for a new innovation can be high compared to other districts. [15]
noted that raising in education levels is proportional to level of adoption of agricultural technologies
which is consistent with the general belief that adoption levels are positively correlated with levels
of education. This is possibly because education inuences the ability of farmers to interpret the
technical recommendations that may require some level of education. Furthermore, [16] noted that
literate farmers can comprehend the benets from extension information and they are aware of the
consequences of the prevailing challenges if they are not addressed in time.
Table 7.4.6: Smallholder dairy farmer’s rankings of challenges on milk marketing in Lake
Victoria agro-ecological zone, Uganda
District Variables Sum of ranks Mean of ranks Ranking (Chi2 , df=4, p-value)
Buikwe
Poor price 1633.50 71.02c 1 32.79, P = 0.0001
Fluctuation in price 1296.50 56.37bc 2
Perishable product 1165.50 52.98bc 3
Delayed payments 634.50 37.32ab 4
Long distances to market 320.00 21.33a 5
Jinja
Poor price 579.50 41.39b 1 17.52, P = 0.002
Fluctuation in price 498.50 35.61ab 2
Long distance to market 412.50 31.73ab 3
Perishable product 187.00 18.7a 4
Delayed payments 152.50 16.94a 5
Mayuge
Poor price 1269.00 63.45c 1 33.12, P = 0.0001
Fluctuation in price 966.00 48.3bc 2
Perishable product 902.00 47.47bc 3
Long distances to market 473.50 31.56ab 4
Delayed payments 217.50 16.73a 5
125
Majority of the farmers in Buikwe and Mayuge had other main sources of income, while smallholder
dairy farmers in Jinja relied on dairy farming as their main source of income. This is consistent with
(Njarui et al., 2011) who made similar observation where high number of female-headed households
in Masaka district in Uganda, who received animals from NGO (send a cow), had no other alternatives
form of employment and household income. However, smallholder dairy farming in LVZ seems
to be unstable venture due to low investment levels unreliable inputs and lack of infrastructural
development such as milk collection centers and coolers to preserve milk which is not immediately
consumed. Thus farmers seek other alternative livelihood complimentary means for their livelihoods
that sometimes become competitive, deny smallholder dairy farming an opportunity for further
knowledge and capital investment.
Challenges in Smallholder Dairy Farming System
While increased animal productivity has been identied as one of the options for increasing incomes,
household nutrition and livelihood of the rural households (MAAIF, 2010) feed scarcity was
unanimously identied by the farmers as one of the biggest challenge to increased milk productivity
in LVZ. The consequence of feed scarcity to smallholder dairy farming system is poor milk yield,
distortion of the estrus cycles, poor body condition and long calving intervals (Kaunda, 2011). Farmers
therefore miss opportunities on proceeds from milk sales and offspring as a result long calving interval
(Lukuyu et al., 2011). The generally high cost of commercial supplementary feeds irrespective of
seasons in LVZ, despite the abundance of agro-industrial by-products points to limited investment
of both knowledge and capital in value addition. This is in agreement with earlier observation by
(Mubiru et al., 2011) who observed that low milk yield in Uganda is attributed to poor feeding methods
resulting from not meeting the right nutritional requirement of dairy cattle. Similarly, limited value
addition to highly perishable milk renders it rather difcult to fetch reasonable prices despite its local
demand right at the farm. These results are consistent with earlier ndings (Njarui et al., 2011) which
indicated that poor milk price is a major challenge to increased dairy productivity in peri-urban areas
of East and Central Africa.
Labour Activities in Smallholder Dairy Farming
Most activities were performed daily, implying that dairy farming is a labour intensive enterprise.
There were no distinct age and sex division of labour, but all gender contributed to smallholder dairy
activities. However, there were disparities in level of labour contribution between men, women and
children. In Buikwe and Mayuge districts, on average, men contributed more labour in the dairy unit
than women, but in Jinja, men contributed marginally more labour than women. Women contributed
labour highly in shed cleaning than in any other activity while men contributed highest in milking,
marketing milk and spraying against ticks. Possibly, cultural inclinations in majorly patriarchal
societies in the study area where men are seen as household bread winners explains why men were
responsible for those activities involving cash transactions in the dairy enterprise. Similarly, all
decision concerning labour activities of the enterprise were unilaterally made by the heads of
households the majority of whom were men. The contribution of children to running of dairy unit was
insignicant, less than 7% on average of total labour activities. Notably, children did not participate in
cutting forages, feeding and watering of the animals. The low contribution of children was primarily
because they attended school during week days and they were only available during week-ends and
holidays.
Nonetheless, the family labour was not sufcient to run the dairy unit and signicant labour was
126
sourced from outside particularly in Jinja. In Jinja, overall hired labour contributed more than half
of the total labour required in running of the dairy enterprises. This implies that external labour is
important for the success of dairy farming in the LVZ given the low levels of mechanization. This
scenario was also reported by Njarui et al., 2011 who found out that hired employees contributed
about 50% of the entire labour requirement of the dairy unit in the rural areas of semi-arid Kenya.
Conclusions and Recommendations
The conclusions drawn from this study are that lack of knowledge to make timely decisions on
available feed resources, limited value addition to highly perishable milk and lack of basic equipment
to reduce on hard work are major outstanding challenges pulling down dairy productivity. The
efciency of production and marketing of milk should be improved in order to enhance smallholder
dairy production in LVZ, Uganda. Therefore milk productivity can be enhanced through appropriate
engagement with the farmer to generate sustainable option to improve nutrient supply throughout
the year. Highly appreciated and utilized crop residues and agro-industrial by-products should be
identied, limitation to utilization evaluated and supplementary dairy cattle ration based on highly
abundant and agro-industrial by-product and crop residue be formulated. Appropriate on-farm
feed conservation practices that include biological processing of highly brous and lignied crop
residues, hay and silage making be promoted on farm. Furthermore, it is necessary to conduct on-
farm strategic studies in LVZ, Uganda to upgrade and enhance utilization of crop residues
and agro-industrial by-products identied by this study as alternative dairy cattle feeding strategy to
meet nutrient requirement during the dry seasons.
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128
7.5 Prioritization of agro-industrial by-products for improved productivity on smallholder
dairy farms in the Lake Victoria Crescent, Uganda
Andrew M. Atuhaire1,2,*, Swidiq Mugerwa1, Samuel Okello2, Kenneth Lapenga2, Fred Kabi3, George
Lukwago4
1 National Agricultural Research Institute (NARO), National Livestock Resources Research Institute,
P. O. Box 96, Tororo, Uganda
2 Department of Livestock and Industrial Resources, College of Veterinary Medicine, Animal Resources and
Bio-security, Makerere University, P. O. Box 7062, Kampala, Uganda
3 Department of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere
University, P. O. Box 7062, Kampala, Uganda
4 East African Agricultural Productivity Project: National Agricultural Research Organization,
P.O. Box 295, Entebbe, Uganda
Introduction
Shortages and uctuating quality and quantity of animal feed resources impose major constraints to
productivity on smallholder dairy farm in Uganda. However, from the production and processing
of plants for human food production, agro-industrial by-products are generated and are potentially
suitable for the feeding of dairy cattle (Kabi et al., 2013), Lukuyu et al., (2011) reported that agro-
industrial by-products play an important role on smallholder dairy farms in Sub-Saharan Africa for
supply of metabolisable energy (ME) and crude protein (CP) which are key components in feeding
dairy cattle for optimum productivity.
Smallholder dairy farming, where 1 to 5 head of cattle are reared on less than 0.5 to 5 acres of land,
is an integral part of livestock production systems that provides food, manure for crop production,
income and employment (Kabirizi et al., 2006)). In Uganda, development strategy and investment
plan (DSIP) clearly recognize the role of smallholder dairy farmer in economic growth and poverty
reduction (MAAIF, 2010). Under the Eastern Africa Agricultural Productivity Project (EAAPP) there
has been a deliberate effort aimed at increasing smallholder dairy productivity. However, smallholder
dairy farming system in Uganda often fails to attain maximum production limit of their potential,
because of inability to obtain adequate required amounts of ME and CP (Mubiru et al., 2007). It is
documented that smallholder dairy farmers in Uganda provide only 59% and 36% of the required
ME and CP, respectively (Mubiru et al., 2011). According to (Mugerwa et al., 2012), Uganda has
the potential to produce enough agro-industrial by-products for dairy cattle feeding, especially in
Lake Victoria Agro-ecological Zone (LVZ) to provide adequate nutrition to match the present trend.
Therefore, exploring the potential to prioritize agro-industrial by-products will lead
to economically feasible as well as socially acceptable feed management strategies for improved
sustainable productivity of smallholder dairy farm.
Despite the potential of agro-industrial by-products, their utilization in smallholder dairy farming
system is limited. Therefore understanding utilization, spatial and temporal variability, and limitation
to utilization will give an insight on prioritizing agro-industrial by-products. This will build coherent
principles required to develop appropriate feeding strategies for sustainable productivity on
smallholder dairy farms. The objective of the study was to establish use, variability and limitations to
utilization of agro-industrial by-products in smallholder dairy farming system.
129
Materials and Methods
Description of the Study Area
The study was conducted in the Lake Victoria Agro-ecological Zone (LVZ) of Uganda
which hosts the majority of smallholder dairy farmers (MAAIF, 2010). Three districts namely Buikwe
(0018’4.32 N and 3303’6.63 E), Jinja (0025’28 N and 33012’15 E) and Mayuge (0027’35 N and 33028’49
E) were selected for the study based on the intensity of smallholder dairy farms (Figure 7.5.1).
Figure 7.5.1: Map of Uganda
showing the location of Buikwe,
Jinja and Mayuge districts
The mean daily temperature ranged between 16-28°C, 18-28°C and 17-27°C for Buikwe, Jinja and
Mayuge Districts respectively. The mean annual rainfall ranged between 1279 to 1544 mm, 1200 to
1500 mm and 1100 to 1500 mm for Jinja, Mayuge and Buikwe, respectively. The districts experienced
tropical climate bimodal rainfall pattern characterized by two rainy seasons (March to May and
September to November) with dry spells (December to February and June to August). According to
the Population and Housing Census of 2002, the estimated mean population density was 256,
66, and 92.55 people’s km-2 for Buikwe, Jinja and Mayuge, respectively (UBOS, 2012). Agriculture is
the main economic activity in the zone, and the level of agricultural productivity at farm level greatly
inuences household’s social- economic status.
Dairy cattle are mainly raised under intensive and semi-intensive smallholder management systems
with the majority of farmers keeping between 1 to 5 head of cattle under stall feeding. Mean agricultural
area is 529, 601.1 and 603.3 km2 for districts of Buikwe, Jinja and Mayuge respectively.
Sampling Procedure, Sample Size, Data Collection and Analysis
A purposive multi-stage sampling design was employed in this study. In the rst stage, the country
was stratied into ten (10) strata (Agro-ecological Zones) on the basis of geographical demarcations.
In the second stage, one out of the ten agro-ecological zones was purposively selected. In the third
stage, three administrative districts were randomly selected as domain of analysis from the agro-
ecological zone. In the fourth stage, three sub-counties per district were randomly selected, in the
fth stage three parishes per sub-county were randomly selected and a list of smallholder dairy
farmers was developed per parish from respective extension ofcers in these three administrative
130
Table 7.5.1: Smallholder dairy farmers’ rankings of agro-industrial by-products utilization
in LVZ, Uganda
District Agro-industrial Bi-products Sum of ranks Mean of ranks Ranking Chi2
Buikwe
Cotton seed cake 1264.00 37.18a4
42.64
Maize bran 3800.00 88.37b3
Brewers spent grains 4031.00 93.74b2
Molasses 4271.00 99.33b1
Jinja
Cotton seed cake 537.00 29.83a4
29.50
Maize bran 1587.00 48.09a3
Molasses 2305.50 69.86b2
Brewers spent grains 2473.50 74.95b1
Mayuge
Cotton seed cake 2250.50 66.19a4
13.33
Maize bran 3502.00 77.82ab 3
Brewers spent grains 3933.50 89.40ab 2
Molasses 4849.00 103.17b1
ab means in the same row and same district without common letter are signicantly different p<0.05
districts. Finally, 7% of the farmers were randomly selected, 126 smallholder dairy households were
interviewed across the agro-ecological zone. Primary data were collected through structured and
semi- structured questionnaires administered by way of one-on-one direct interviews. Focus group
discussions (one per sub-county) were also held to corroborate the information gathered in direct
interviews. Secondary data were collected from document reviews at the district headquarters.
In order to establish differences among farmers’ ranking on utilization, variability and limitations
to utilization of agro-industrial by-products, farmers’ ranking were pooled and subjected to
nonparametric statistics analysis (Kruskal–Wallis one-way analysis of variance) using [9]. Using
multiple pair-wise comparisons, the computed mean of ranks were used to establish if there were
signicant differences in utilization levels, variability, availability and limitations to utilization of
agro-industrial by-products (Dunn, 1964), (XLSTAT, 2013) was used to generate descriptive statistics
for the variables.
Results
Utilization of Agro-industrial By-products
Farmers supplement their animals with various types of agro-industrial products (Table 7.5.1). Four
agro-industrial by-products were identied and ranked based on their utilization by farmers using a
scale of 1 to 4 with four being the most utilized agro-industrial by-product and l the least utilized. Chi-
square test at p < 0.01, df = 3 showed a signicant differences among farmers’ ranking on utilization
of agro-industrial by-products.
131
Table 7.5.2: Farmers’ rankings of factors that enhance use of agro-industrial by-products
unprocessed
District Agro-industrial Bi-products Sum of ranks Mean of ranks Ranking Chi2
Buikwe
Expensive supplementary
feeds
2817.00 93.9c1
47.64
Land shortage 2304.00 76.8bc2
Lack of basic equipment 2037.00 70.24bc 3
Marketing infrastructure 1052.50 47.84ab 4
Expensive labour 567.50 27.02a5
Jinja
Land shortage for fodder
production
1587.50 72.16b1
46.14
Expensive supplementary
feeds
1217.50 55.34b2
Expensive labour 1173.50 53.34b3
Marketing infrastructure 372.50 24.83a4
Lack of basic equipment 305.00 20.33c5
Mayuge
Marketing infrastructure 2659.00 91.69bc 1
45.56
Expensive supplementary
feeds
2114.50 72.89bc 2
Land shortage 1929.50 68.91bc 3
Lack of basic equipment 1019.00 46.34ab 4
Expensive labour 534.00 26.70a5
ab means in the same row and same district without common letter are signicantly different p<0.05
Factors Enhancing Utilization of Agro-industrial By-products in LVZ, Uganda
Factors enhancing utilization of agro-industrial by-products in LVZ were ranked by farmers
and analyzed. Chi-square test at p<0.01, df = 4 showed signicant differences among the farmers’
rankings (Table 7.5.2).
Spatial and Temporal Variability on Availability of Agro-industrial By-products
The variability of agro-industrial by-products were ranked by farmers basing on their memory
of past experience. There were signicant difference (p>0.05) in variability of agro-industrial by-
products generally in all the seasons throughout the year across LVZ, in Uganda (Table 7.4.3).
Smallholder Dairy Farmers’ Rankings of Limitations to Utilization of Agro-industrial By-products in
LVZ, Uganda
Limiting factors to utilization of agro-industrial by-products were identied and ranked by
smallholder dairy farmers as presented in Table 7.5.4. Five limiting factors were identied and ranked
using a scale of 1 to 5, with 5 being the most limiting factor affecting utilization of agro-industrial by-
product and 1 the least limiting factor. Chi-square test showed a signicant difference at p<0.01, df =
4 among farmers rankings across the LVZ.
132
Table 7.5.3. Farmers ranking of spatial and temporal variability on availability of agro-
industrial by-products in LVZ
District Season Variability Mean Rank P-value df
Buikwe
1st rain season (March to May
Low 21.70 0.81 1
Moderate 20.00
Jinja Low 21.27 0.79 1
Moderate 23.20
Mayuge Low 21.34 0.62 1
Moderate 22.70
Buikwe
2nd rain season (September to November)
Low 21.90 1.18 1
Moderate 19.50
Jinja Low 21.8 0.67 1
Moderate 20.00
Mayuge Low 21.5 0.43 1
Moderate 21.5
Buikwe
1st rain season (June to August)
Low 11.00
2
Moderate 25.50 4.88
Jinja High 22.06
Low 12.50
2
Moderate 26.08 4.02
Mayuge High 21.77
Low 11.00
1Moderate 26.50 6.59
High 21.88
Buikwe
2nd rain season (Dec to Feb)
Low 15.20 2.34 1
High 22.35
Jinja Low 16.70 1.38 1
High 22.15
Mayuge Low 18.90 1.2 1
High 21.85
133
Table 7.5.4. Smallholder dairy farmers’ rankings of limitation to utilizing of Agro-industrial
by-products
Table 7.5.5. Methods used by the farmers to store, process and preserve agro-industrial by-
products in LVZ, Uganda
District Limitations Sum of ranks Mean of ranks Ranking Chi-square
Buikwe
High input cost 6504.50 151.27c1
53.04
Inadequate knowledge 5609.00 130.44b2
Limited knowledge to preserve 4337.50 100.87b3
Poor market infrastructures 3191.50 77.84a4
Processing and storage 3148.50 73.22a5
Jinja
High input cost 3623.00 109.79b1
34.78
Inadequate knowledge on usability 3356.00 101.70b2
Limited knowledge to preserve 2586.50 80.83ab 3
Poor market infrastructures 2277.00 69.00a4
Processing and storage 1687.50 51.14a5
Mayuge
High input cost 9175.00 183.50d1
82.80
Inadequate knowledge on usability 7725.00 154.50c2
Limited knowledge to preserve 6375.00 127.50b3
Processing and storage 4475.00 89.50ab 4
Poor market infrastructures 3625.00 72.50b5
% of households undertaking the practice on
Methods BS M MB CSC
Storage Home heaps 53
Pits 23.4
None 12
Processing Additives to other feedstuff 15 61.1 100 100
Presentation Drying 21.2
Mult-nutrient block 2.4
BS = Brewers spent grain, M = Molasses, MB = Maize bran, CSC = Cotton seed cake
Methods practiced by smallholder dairy farmers to store, process and preserve agro-
industrial by-products
Table 7.5.5 shows the different methods used by the farmers to process and store agro-industrial by-
products.
While 23.4% of the farmers’ stored brewers spent grains in ground pits, 21% preserved it by drying
and 12% used it directly. It was also observed that 61.1 % of the farmers mixed molasses with
fodder especially in dry season to improve dry matter intake, while 2.4% used it in home-made
multi-nutrient block. Maize bran and cotton seed cake were utilized as additive to the basal feed.
134
Discussion
Utilization of Agro-industrial By-products
The possible explanation for signicant utilization of agro-industrial by-products in the study
area was because of geographic comparative advantage that made most of agricultural processing
industries such sugar factories, maize milling, brewery and oil manufacturing factories to be situated
in this area. For this reason, smallholder dairy farmers in the study area have access to most
of the agro-industrial by products. Use of agro-industrial by-products in LVZ is still limited to
only four by-products implying that there could be some other factors limiting their integration. On
the other hand, there is limited literature on utilization of agro-industrial by-products by farmers
in smallholder dairy farming system in the zone in particular and generally in Uganda, unlike in
other developing countries (Mugerwa et al., 2012). The current dairy cattle feeding regimen that
heavily depends on elephant grass as the major source of nutrients to dairy cattle conrms earlier
studies by (Kabirizi et al., 2006), which indicated that elephant grass is the most dominant and more
frequently used source of energy in Uganda. Such poor supplementary regime does not lend itself
into good husbandry for highly yielding dairy cattle, which probably explains the low productivity
in smallholder dairy farming system in LVZ, of Uganda. Although molasses was ranked protein, it
was not surprising to note that smallholder farmer whose animals depend mostly on natural pasture
were supplemented with molasses, brewers spent grain, dairy meal and home-made concentrates
to augment the protein and energy decient pastures. Limited use of agro-industrial by-products
to make home-made concentrates despite its high affordability by farmers was probably because
the farmers had limited expertise to formulate the concentrates suggesting a need for more farmers’
training. The ndings imply that in Mayuge district farmers urgently require immediate solutions
on how to process homemade concentrates for dairy cattle from agro-industrial by-products than
any other district. number one agro-industrial by-product utilized by smallholder dairy farmer in
the study area, it was reported to face stiff competition from alternative use in other cottage and
commercial industries like ethanol production, local brew production and thermal power generation
(Kabi et al., 2013). The potential of brewers spent grain to provide economical viable feed supplement
to dairy cattle in the study area remains credible since there was no signicant difference between
molasses and brewers spent grain across all districts (Table 7.5.1).
Factors Enhancing Utilization of Agro-industrial By-products in LVZ, Uganda
Most of the smallholder dairy farmers in the area of study own between 0.5 to 5 acres of land
which limits them in forage production. As such, the available forage is usually decient to meet
the nutritional requirements of their animals paving way for high levels of supplementation. The
smallholder farmers largely keep cross-breed animals whose response to supplementation with
high value protein is signicant compared to local breeds as earlier reported (Dhiman et al., 2003).
Given the fact that natural pastures are usually decient in protein, it was not surprising to note
that smallholder dairy farmer whose animals depend mostly on natural pastures and homemade
concentrates to augment the protein and energy decient pastures. Limited use of agro-industrial by-
products to make homemade concentrates despite its affordability by farmers was probably because
the farmers had limited expertise to formulate the concentrates suggesting a need for more farmers
training. The funding imply that in Mayuge District farmers urgently required solution on how to
process homemade concentrates for dairy cattle from agro-industrial by-products than any other
district.
135
Spatial and temporal variability of agro-industrial by-products
The spatial and temporal variability of agro-industrial by-products in area of study was not
signicant and indicated low levels of variability in utilization. Farmers in LVZ ranked utilization
of agro-industrial by-products as high in the dry seasons and slightly low in wet season. In a related
study, similar relationship between utilization levels and season was earlier reported by farmers in
Tanzanian western rangeland zone, Morogoro peri-urban area (Mlay et al., 2005). This is consistent
with (Ngongoni et al., 2006), who stated that peak agro-industrial by-product utilization occurs
during dry season. (Preston and Leng, 1987 ) noted that periods of intense utilization of agro-
industrial by-products reect the dynamics of dairy cattle nutrient requirements. During the dry
season, forages are low in essential nutrients such as nitrogen, energy, minerals and vitamins required
for optimal rumen microbial growth (Mlay et al., 2005). Thus it is very important to supplement with
agro-industrial by-products for supply of decient nutrients in poor quality forage during the dry
period.
During focus group discussions farmers reveled that supplementing dairy cattle during dry season
improves productivity in terms of milk yield and calving interval. This suggests that supplementing
during dry season meets the high physiological nutrient demands for lactating animals hence
improving on their productivity.
Limitation to utilization of agro-industrial by-products in LVZ, Uganda
The generally high cost of inputs ranked as the main limitation across all the districts (Table 7.5.1)
irrespective of season was attributed to scarcity of supplementary feeds due to limited knowledge
by farmers in value addition to the abundant agro industrial by-products. Similarly, poor marketing
infrastructures that limited value addition to the highly perishable milk were a bottle neck to farmers
to fetch reasonable prices. Therefore, in agreement with earlier observation [2], inadequate knowledge
usability, limited knowledge on preservation, unstable supply, inadequate processing and storage of
agro-industrial by-products were identied as very important limitations that need urgent attention if
challenges that limit dairy cattle productivity are to be eliminated. Furthermore, lack of infrastructural
development such as milk coolers in the area to preserve milk which is not immediately consumed
locally especially during the wet season coupled with lack of equipment to reduce on drudgery of
labour was reported to negatively impact on smallholder dairy productivity. It was evident in the
study that although to some extent farmers were aware of the nutritive attributes of agro-industrial
by-products to dairy cattle, they did not fully exploit the resource.
Storage, Processing and Preservation of Agro-industrial By-products
Based on storage, preservation and processing skills, farmers identied three methods of storage,
two methods of preservation and two methods of processing, which were remarkably consistent with
scientic methods. Such knowledge is worth documenting, promoted and where possible improved
on to facilitates communication between farmers, extension staff and scientists on agro-industrial by-
product utilization. The quantity and time period during which they are available, storage properties,
cost of transport, preparation, and preservation are determinants for their utilization (Lentes et al.,
2010b). In view of the reported shortages of conventional feeds for dairy cattle, there is a need to
develop technologies that are already known to farmers, using more social economic efcient scientic
strategies to obtained protein and energy supplements for improved productivity.
136
Conclusions
It was evident in the study that farmers are aware of the importance of agro-industrial by-products in
dairy cattle feeding. Although a number of factors were fronted to explain variations in dairy cattle
productivity, majority of smallholder dairy farmers attributed the challenges to social-economic
deterioration associated with inadequate knowledge to processes, preserve and store agro-industrial
by-products. Utilization of agro-industrial by-products was high during dry periods when natural
pastures and forages are low. Sustainable agro-industrial by-products management strategies on
smallholder dairy farm should not only target dry season, but also focus on ensuring sustainable
nutrient supply for optimum productivity. Prioritizing agro-industrial by-products management
strategies that enhance sustainable nutrient supply will help meet physiological nutrient demands by
productive animals and thus mitigate productivity surges. It is also necessary to conduct scientic
experimental investigations to establish appropriate economic inclusion levels of agro-industrial by-
products. Such information would assist to guide management decisions in an attempt to maintain
viable productivity equilibrium between nutrient supply and other farm input components. The
study has also provided some basic information about farmers’ knowledge of the utilization and
limitations of agro-industrial by-products that could aid the development and promotion of sustainable
and socially acceptable feeding strategies for smallholder dairy farming system. Smallholder dairy
farmers demonstrated knowledge of the importance, limitation, spatial and temporal distribution
of agro-industrial by-products. The study revealed that efforts aimed at prioritizing integration of
agro-industrial by-products into dairy cattle feeds in LVZ should focus on technologies of processing,
preservation and storage.
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138
7.6 Prioritization of crop residues for improving productivity on smallholder dairy
farming households in the Lake Victoria Crescent, Uganda
Andrew Mwebaze Atuhaire1, Swidiq Mugerwa1, Samuel Okello2*, Kenneth Okello Lapenga2, Fred Kabi3,
Jolly Mary Kabirizi1
1 National Agricultural Research Institute (NARO), National Livestock Resources Research Institute
(NaLIRRI), Tororo, Uganda
2 Department of Livestock and Industrial Resources, College of Veterinary Medicine, Animal Resources and
Bio-Security, Makerere University, Kampala, Uganda
3 Department of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere
University, Kampala, Uganda
Introduction
Because of its contribution to the socio-economic development of rural Uganda in both food security
and in- come generation, especially, among women and other disadvantaged groups, smallholder
dairy production sys- tem has received considerable support from the Government of Uganda as well
as non-government organizations (Kabirizi et al., 2006). Moreover, by functioning as a store of wealth
(Winrock International, 1992) and supplying manure for crop production (Kabi et al., 2007), dairy
cattle t very well in integrated crop-livestock systems. In Uganda, dairy cattle play a key role in the
nutrition, of most households with per capita milk consumption of about 58 litres (MAAIF, 2010)
against FAO requirement of 200 litres per person per year (FAO, 2012). While annual average milk
yield per cow per lactation per year of 305 days in developed countries can go above 8000 kg, less than
2000 kg is obtainable from pure dairy breeds, 1000 from cross breeds and 500 kg from indigenous
cows in Uganda (Bahiigwa et al., 2005). These statistics are obviously distressing in light of the rapidly
growing human population at a rate of 3.2% annually (UBOS, 2012). In Mugerwa (2012) it is singled out
that feed scarcity leads to poor nutrition which is a key constraint holding down production efciency
and health of the dairy cow on smallholder dairy farms in Lake Victoria Agro-ecological Zone (LVZ).
Poor nutrition of dairy cattle is exaggerated by drought induced feed scarcity attributed partly to
change in climate and demographics. As human population increases demand for milk also increases,
crop production expands, availability of land for forage production decreases contributing towards
dairy cattle feed scarcity. With projected increase in demand for milk, coupled with declining land
size for forage production due to demographic pressure, it seems inevitable for farmers to embrace
alternative feed resources. Utilization of crop residues therefore seems a logical alternative to address
the escalating levels of feed scarcity among smallholder dairy farming systems (Lentes et al., 2010).
Efcient utilization of crop residues however faces a number of intriguing challenges that include low
levels of metabolized energy and crude protein (Tesfaye et al., 2007) seasonal variability (Tsopito et
al., 2004), bulky (Walli et al., 2008) and poor keeping qualities (Anandan et al., 2010). These challenges
should be acknowledged for appropriate technological innovations that prioritize crop residues as
alternative feed to supply nutrients to dairy cattle for improved productivity on smallholder farm.
Crop residues have been used as livestock feeds since time immemorial and are readily available
feed re- sources (Njarui et al., 2011), however their nutritional value is poor and well documented
(Tesfaye et al., 2007) (Tsopito et al., 2003). Considerable research efforts have been devoted into
improving their nutritional value through crop management and breeding, physical, biological and
chemical treatments as well as supplementation with high protein oil cakes, green fodder, and tree
leaves (Mugerwa et al., 2012) (Preston et al., 1987). However, on-farm implementations of these
strategic innovations seem unsatisfactory. Further- more, in Uganda there is scanty of information
139
on crop residue utilization, temporal and spatial variability as well as limitations associated with
utilization on smallholder dairy farms unlike in other developing countries. Which make a basis
in identifying opportunities, to priorities feeds from crop residues for improved nutrition that
translate into enhanced productivity on smallholder dairy farming household. Thus this survey was
designed to assess crop residues variability, limitations and opportunities in LVZ for future research
on developing appropriate dairy feeding systems that utilize crop residues. These will in long run
secure smallholder dairy farming from demographic pressure and substance farming to improved
productivity and sustainable farming system.
Materials and Methods
Description of the Study Area
The study was conducted in the Lake Victoria Agro-ecological Zone of Uganda which hosts the
majority of smallholder dairy farmers. Three districts namely Buikwe (0˚18’4”N and 33˚3’6”E), Jinja
(0˚25’28”N and 33˚12’15”E) and Mayuge (0˚27’35”N and 33˚28’49”E) were selected for the study
based on the intensity of smallholder dairy farms (Figure 7.6.1). The mean daily temperature ranges
between 16˚C - 28˚C, 18˚C - 28˚C and 17˚C - 27˚C for Buikwe, Jinja and Mayuge Districts. The mean
annual rainfall ranges between 1279 to 1544 mm, 1200 to 1500 mm and 1100 to 1500 mm for Jinja,
Mayuge and Buikwe respectively. The districts experience a tropical climate bimodal rainfall pattern
characterized by two rainy seasons (March to May and September to November) with dry spells
(December to February and June to August). According to the Population and Housing census (2002),
the estimated mean population density was 256, 658 and 92.55 per person km-2 for Buikwe, Jinja and
Mayuge respectively. Agriculture is the main economic activity, prolonged droughts that lead to crop
failure and increased feed scarcity is the main constraints to agricultural production.
Dairy cattle are mainly raised under intensive and semi-intensive smallholder management systems
with majority of farmers keeping between 1 to 5 head of cattle under stall feeding with negligible
grazing and tethering. The mean agricultural area is 529, 601.1 and 603.3 km2 for districts of Buikwe,
Jinja and Mayuge respectively.
Figure 7.6.1. Map of Uganda showing the location of Buikwe, Jinja and Mayuge districts.
140
Table 7.6.1. Farmers ranking of crop residues.
District Crop residue Sum of ranks Mean ranks Chi2, p-value, df = 4
Mayuge
Sugar cane tops 2647.00 64.56a
X2= 54.40, p = 0.0001
G.nut haulms 3465.50 85.52ab
Banana peels 3954.50 96.45ab
Sweet potato vines 4810.00 117.32bc
Maize stover 6238.00 152.15c
Jinja
G.nut haulm 2790.00 69.75a
X2 = 25.83, p = 0.0001
Sugar cane tops 3468.00 86.7ab
Banana peels 4069.00 101.72bc
Sweet potato vines 4866.00 121.65abc
Maize stover 3616.00 122.67bc
Buikwe
Sugar cane tops 4020.00 80.37a
X2=54.71, p=0.0001
Banana peels 3616.00 89.33ab
G.nut haulms 4608.00 102.4ab
Sweet potato vines 5599.00 124.42b
Maize stover 7581.5 168.48c
abMeans in the same row and same district without common letter are signicantly different (p< 0.05).
Sampling Procedure, Sample Size, Data Collection and Analysis
The study was conducted in three districts (Buikwe, Mayuge and Jinja) which were purposively
selected based on the intensity of smallholder dairy farms. Three sub-counties were randomly
selected from each district. After consultations with the district extension staff and sub-county
extension ofcers and following all procedures of systematic random sampling selection, fourteen
respondents were selected from each sub-county totaling to forty two respondents per district. Data
was obtained using pre-tested structured and semi-structured questionnaires administered by way of
one-on-one direct interviews. Focus group discussions (one per sub-county) were held to corroborate
the information gathered in direct interviews. The questionnaires and focus group discussions were
intended to capture information on availability, variability and limitations to utilize crop residues on
smallholder dairy farms.
In order to establish if there were statistical signicance among farmers’ ranking of crop residues
utilization, variability and limitations in utilization of crop residues, farmers’ responses were pooled
and subjected to non- parametric statistics analysis (Kruskal-Wallis one-way analysis of variance)
using [16]. Five crop residues were ranked by farmers using a scale of 1 to 5 with ve being the most
important crop residue. Also, ve limiting factors were ranked by farmers using a scale of 1 to 5,
with 5 being the most important limitation in utilization of crop residue. The computed sum of ranks
and mean of ranks were compared using multiple pair-wise comparisons to establish if there were
signicant differences in utilization levels and limitations to utilization of crop residues. [16] was
used to generate summary statistics (frequencies, percentages and means) for the variables and later
tabulated.
Results
Farmers’ Ranking on Utilization of Crop Residues
Kruskal-Wallis test showed that there were signicant differences (p = 0.0001) maintained in all the
districts among farmers’ ranking of the different crop residues (Table 7.6.1).
141
Farmers’ ranking on utilization of maize stover was highest throughout the zone, in Buikwe, Jinja
and Mayuge with mean ranks of 168.48, 122.67 and 152.15 respectively. Farmers ranked maize stover
(mean of ranks = 152.15, 122.67 and 168.48) and sweet potato vines (mean of ranks = 117.32, 121.65
and 124.42) as the most important crop residue throughout Mayuge, Jinja and Buikwe districts
respectively. Sugar cane tops (mean of ranks = 64.56 and 80.37) were ranked as the least important
crop residue in Buikwe and Mayuge districts while in Jinja ground nuts haulms (mean of ranks =
69.75) was ranked as the least important crop residue. In Mayuge district, ground nut haulms (mean
of ranks = 84.52) were ranked second least important crop residue while in Jinja it was sugar cane tops
(mean of ranks = 86.7) and in Buikwe it was banana peels (mean of ranks = 89.33).
Farmers’ Ranking on Spatial and Temporal Variability of Crop Residues
Spatial and temporal variability of crop residues in the study area were assessed on monthly basis
by asking the respondents to classify abundance of crop residues as highest, moderate or lowest. The
orders were then converted to scores in such ways that score 3 was given to the highest in abundance,
score 2 moderate and score 1 lowest. Then the percentage score for each crop residue was calculated
as its total weighted score divided by the overall total scores. Calculated accordingly, the percent
score for variability of crop residues at given point in time by respondents are given in Figure 7.6.2
(UBOS, 2012), characterizes seasons based on amount of rain fall received, prevailing humidity and
temperature. LVZ has two dry seasons (December to February and June to August) and two wet
seasons (March to May and September to November) in a year. Generally farmers score indicated
that quantities of crop residues vary throughout the year. The highest in abundance was reported
to occur towards the beginning of dry season and least abundant levels were reported to be at the
end of dry season. Maize stover was scored highest in abundance in rst season, reduces slightly
in second season then attains peak abundance in third season and reduces progressively in fourth
season throughout the zone. The abundance levels of sweet potato vines were scored highest in rst
season reduces in second season, increases progressively to attain its peak abundance in third season,
in fourth season it moves down then starts increasing again towards the end of the season.
It was noted that most frequently utilized crop residues are highest in abundance in third season
and lowest in fourth season. Maize stovers were highest in abundance in Jinja district in rst season,
while the rest of the districts hit their peak abundance in third season. Ground nuts haulms were
moderately abundant in fourth season in Jinja district while in the rest of the districts it was lowest in
fourth season.
142
Figure 7.6.2. Spatial and temporal
variability of crop residues in the study
areas
3.3. Methods Applied by Farmers to Store, Process and Preserve Crop Residues
Table 2 shows different methods used by the farmers to store, process and preserve crop residues.
It was depicted that storage, processing and preservation had positive effect on improving crop
residues intake by the dairy cattle. Percentage of the respondents using different methods of storage,
processing and preservation are shown in Table 7.6.2. The majority of the farmers 52.7% stored
their maize stover by home heaps while 7.6% did not use any particular storage facilities. Physical
processing (chopping) of maize stover, ground nuts haulms and sweet potato vines practiced by
71.2%, 60.4% and 88.3% of the respondents respectively was the most common technology applied.
Farmers sprayed crop residues with additives that included molasses, salt, brewer’s spent grain and
yeast to improve on dry matter intake. The major preservation method of ground nuts haulms, sweet
potato vines and banana peels was by drying represented by 3.6%, 27.9% and 44.1% respectively.
Table 7.6.2. Methods applied by farmers to store, process and preserve crop residues
Practice Percentage score of the farmers undertaking the method
Method MS GNH SPV SCT BP
Storage
Field heap 22.3 24.1 2
Home heaps 52.7 36.3 45.2 38.5
Communal shade 17.4 27.7
None 7.6 25.1
Processing Physical processing 71.2 60.4 88.3
Spraying with additives* 81.1 21.6 2.7 5.8 27
Preservation
None 7.2 38.8 24.3 3.6 32.4
Drying 3.6 27.9 44.1
Multi-nutrient block 2.4 2.4
MS = maize stover, GNH = ground nuts haulms, SPV = sweet potato vines, SCT = sugar cane tops,
BP = banana peels, *With salt, molasses, and brewer’s grain/yeast.
143
Farmers’ Rankings of Limitations to Utilization of Crop Residues
The ranking of farmers on limitation to utilization of crop residues in smallholder dairy cattle feeds and
feeding system are presented in Table 7.6.3. Kruskal-Wallis test revealed a high signicant difference
among the farmers ranking. Buikwe district ranked lack of knowledge to preserve crop residue (mean
of ranks = 114.32) as the major limitation in utilization of crop residues. While in Jinja and Mayuge
district lack of knowledge to process crop residues (mean rank = 88.29, 121.24) was ranked as the
major limitation to utilization. Other limiting factors ranked in descending order of importance were:
limited land, transportation of crop residues from the eld and limited labour.
Table 7.6.3: Farmers ranking of limitation to utilization of crop residues
Practice Percentage score of the farmers undertaking the method
District Limitation Sum of ranks Mean of ranks (Chi2, df, p-value)
Mayuge
Limited labour 1748.50 52.98aX2 = 58.67, df = 4, p = 0.0001
Limited land 1829.50 55.44a
Transportation (Bulky) 2268.00 84ab
Lack of knowledge to preserve 4583.00 111.78bc
Lack of knowledge to process 4971.00 121.24c
Jinja
Limited labour 1572.50 58.24aX2 = 12.84, df = 4, p = 0.012
Limited land 1639.00 63.04ab
Transportation (Bulky) 1458.50 66.30ab
Lack of knowledge to
preserve
2764.50 83.77ab
Lack of knowledge to
process
3443.50 88.29b
Buikwe
Transportation (Bulky) 1858.00 59.94adf = 4, p = 0.0001 X2 = 33.0
Limited labour 2301.00 67.68a
Limited land 3262.50 95.96ab
Lack of knowledge to
process 4910.50 111.60b
Lack of knowledge to
preserve
4688.00 114.34b
aMeans in the same row and same district without common letter are different at p < 0.05.
144
Discussion
Crop residues are brous parts of crops that remain after those edible to human beings have been
removed. Through their digestive adaptations, primarily based on the degradation of brous
materials by microbes in the rumen (Preston et al., 1987), ruminant animals have the unique capacity
to utilize these otherwise useless by-products. This indicates that in dairy cattle feeding system,
crop residues can replace roughages in rations, reducing the competition on cereals between human
beings, monogastic and ruminant animals. Crop residues are readily available in LVZ, cheap feed
resource because the grain which is the main marketable product takes care of the production costs.
The major crop residues available in the study areas were established as maize stover, sweet potato
vines, sugar cane tops, ground nuts haulms and banana peels. Maize stover was ranked a major
crop residue available and utilizable in smallholder dairy farming system in LVZ of Uganda, the
study area. It was also established that with increased crop failures due to prolonged drought, as
has become more frequent even in the LVZ large acreages of maize crops would be available for
conversion into feed for smallholder dairy farms. Uganda currently ranks with the highest potential
of maize production for export among the countries in the East, Central and Southern African region
where maize is the staple food (Okaboi et al., 2011). If this potential is exploited, the massive quantities
of maize stover generated will be a major feed resource for smallholder dairy farmers. Furthermore,
rankings of spatial and temporal variability of crop residues indicate that rst season (December
to February) was the main harvest period, which explained the abundance of the crop residues in
second season (March to May). This is in line with studies by (Tsopito et al., 2013) who noted that
variations in availability of crop residues as major factors constraining their utilization. Furthermore,
suggesting that interventions to enhance utilization of crop residues in LVZ should prioritize maize
stover. However, its nutritive value is low (Njarui et al., 2011) (Akinfemi et al., 2009), research should
be directed towards enhancing its crude protein content, improving its digestibility and reduction on
its crude bre.
While there are prospects to improve the nutritive value of crop residues in LVZ through
supplementation, simple treatment, processing and preservation methods, maize stover and sweet
potato vain were fed without much attention to improve their nutritive values. The only method
undertaken by number of respondents (71.2% maize stover and 88.3% sweet potato vain) was
physical processing (Chopping). Feeding crop residues when they are unprocessed or untreated
limits their intake (Lukuyu et al., 2011). Integrating crop residues with forage legumes improves
rumen microbial degradation of crop residues by supplying nitrogen to the rumen microbes which in-
creases digestibility and intake of poor quality feed (Smith et al., 1993). Nitrogen supplementation in
the rumen environment decient of nitrogen leads to increased dry matter digestibility and voluntary
feed intake (Mlay et al., 2005). Furthermore, feeding small amounts of naturally occurring high
protein supplement such as brewers spent grain also improves the nutritive value of crop residues
(NRC, 2001). Biological treatment of maize stover utilizing mushroom fungi through fermentation,
is another alternative to convert maize straw into high nutritive value dairy cattle feed (Akinfemi et
al., 2009).
Maintaining access to sufcient quality and quantity of nutrition is vital for milk production in the
dairy cattle (Lukuyu et al., 2011). Although crop residues are important feed resources they are low
in nutritive value (Tsopito, et al., 2003) and poor storage methods (Table 7.6.2) practiced by farmers
predisposes them to rain and sunlight resulting into further deterioration in quality (Njarui et al.,
2011). Majority of the farmers (92.4%) interviewed stored maize stovers for future use in dairy cattle
feeding. Although the majority of the farmers understood very well the importance of storage and
tried to practice it but it was established that large proportion was left in the eld for the animals
145
to graze in situ hence resulting into inefcient utilization. Besides, where the crop residues were
stored, during feeding, it was thrown in the cattle boma. This resulted into trampling and wastage.
It was further observed that crop residues especially maize stovers are left to stand in the eld post-
harvest where they lose leaves prior to being harvested for storage. Even following harvesting and
stacking they tend to be stored outdoors in home heaps as reported by 52.7% of the respondents
resulting into further nutrient losses through leaching. These ndings are consistent with earlier
studies that mentioned low nutritive value of crop residues (Tsopito et al., 2003) and poor handling
of maize stovers (Akinfemi et al., 2009). Therefore, in order to improve utilization of maize stover,
the challenges on handling during harvesting, process and storage should be addressed. This is vital
in enhancing maize stover utilization and improving its intake and nutritive value for improved
smallholder dairy farm productivity.
Results of this study further reveals that inadequate knowledge to process and preserve crop residues
was major limitations in utilization of crop residues. Other limitations in descending order included;
difculty in transportation (bulkiness), seasonal variability, labour and storage facilitates. Similar
ndings were reported by (Anandan et al., 2010) who cited lack of knowledge and capital, (Dejene et
al., 2009) high labour cost, (Ngongoni et al., 2006) low nutritive value and (Walli et al., 2009) difculty
in transportation because crop residues are bulky. All these limitation directly inuence the stability
of the nutritive values of crop residues and hence there utilization. Earlier research interventions for
promoting smallholder dairy cattle productivity focused on fodder agronomy and seed production
(Mugerwa et al., 2012). However, with increased effects of climate change and reducing household
land holdings, emphasis must be shifted to utilization crop residues. But nutritional deciencies of
crop residues make them unable to support maintenance and production requirements of a milking
dairy cows (Mugerwa et al., 1987), pointing to the need for evaluation of strategic processing and
supplementation with locally available ingredients as a viable research interventions (Mubiru et al.,
2007). This calls for research innovations to improve on processing, preservation and storage of crop
residues, which should be appealing to smallholder dairy cattle farmers for sustainable productivity.
Conclusion and Recommendations
Maize stover and sweet potato vines were the major crop residues utilized in the study area. They
were not utilized at the optimum period thus compromising on their quality and variability. Lack of
knowledge, poor quality and transportation were the major limitations. Improving productivity in
dairy cattle production system in LVZ should therefore target qualitative improvement of nutritive
value of maize stover. Research thrust should be directed towards nutritive value improvement
techniques both on station and on farm to justify the economic feasibility. Biological processing of
maize stovers with mushroom fungi may provide a feasible research notion for improved utilization
of maize stover in order to improved smallholder dairy cattle productivity.
146
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148
7.7 Effect of supplementing lactating crossbred animals with Bentonite as a mineral
supplement on milk production
Mugerwa, S.; Zziwa, E. and Kabirizi, J.
National Livestock Resources Research Institute
Introduction
Aatoxins (AF) are a group of closely related, biological active mycotoxins (Mishra and Daradhiyar,
1991) that are highly toxic and carcinogenic fungal metabolites produced mainly by Aspergillus avus
and Aspergillus parasiticus. Almost any feed or grain for livestock and poultry is able to support
fungal growth and AF formation. AF B1, B2, G1, G2 and M1 are the most common forms but AFB1 is
considered to be the most toxic (Nilipour, 2002). They reduce growth and feed efciency, and cause
liver and kidney damage (Bintvihok, 2002). They also cause immuno-suppression and changes in
relative organs weight (Kubena et al., 1993), increased mortality (Huff et al., 1988) and enhanced
susceptibility to infectious diseases (Chang and Hamilton, 1991). According to the World Health
Organization and the Food and Drug Administration Department of the US, the recommended
maximum limit of aatoxin in foods for humans, poultry and young pigs is 20 ppb, but levels as high
as 1000 ppb have been reported in Uganda’s grain and animal feeds (Kaaya, 2005). The major way of
dealing with aatoxin contaminated grain has been condemning them to animal feeds, but animals
are squarely affected by aatoxins with reduced growth, egg and milk yield and animals also pass on
aatoxins to their products and affect humans.
Numerous strategies, such as physical separation, thermal inactivation, irradiation, microbial
degradation and treatment with a variety of chemicals have been used for the detoxication or
inactivation of mycotoxin-contaminated feedstuff. One strategy is to bind the aatoxin molecule to
a compound that cannot be absorbed from the animal’s digestive tract. The bound aatoxins are
then excreted in the faeces (Bintvihok, 2002). Bentonites have this capacity and have been utilized in
many countries to bind aatoxins. Bentonites are highly colloidal and plastic clay materials composed
largely, but not exclusively, of montmorillonite (a species of dioctahedral smectite) without reference
to a particular origin. The properties of bentonites can vary considerably depending on geological
origin and any post-extraction modication, and their individual characteristics have a marked
bearing on their economic use.
The discovery on Calcium Bentonite (CB) in Uganda coupled with the extra-ordinarily high level
contamination of animal feeds with aatoxins heightened the impetus to harness the clay in
detoxication of aatoxin infested feeds. Also, the Ugandan CB is rich in inorganic minerals containing
1.25, 1.35, 123.5, 35 and 0.2 ppm of Copper, Zinc, Iron, Manganse and Cromium respectively. It also
contains 0.11, 0.18, 0.013, 0.015 and 0.02% nitrogen, Phosphorus, Sodium, Potassium and Calcium.
Studies were therefore conducted to gain an understanding of the general effect of CB on animal
productivity as well as to set the ground for more focused studies intended at harnessing the clay
materials in animal nutrition. This paper presents preliminary ndings of short but scientically well
designed studies on the role of CB as a detoxier of atoxins as a mineral supplement in lactating
crossbred cattle.
149
Materials and Methods
The experiment was conducted in Jinja District with Jinja dairy farmers group. Twelve crossbred
lactating cows were blocked into three groups on the basis of stage of lactation, initial body
weight and the parity. Cows in their rst, second or third lactations were used for the trial. Three
experimental treatments including (1) Supplementation with concentrates containing bentonites, (2)
Supplementation with concentrates containing commercial mineral premix and (3) Supplementation
with concentrates containing neither premix nor bentonite (control) were allocated to the three groups
of animals. The quantity of the supplement per animal per day was 500 grams. The quantity and costs
of ingredients used in formulation of concentrates are presented in Table 7.7.1. The cows were feed
on a Napier basal diet that met their dry matter intake. A 14 day adaptation period was allowed
before data collection and then milk yields were recorded for the subsequent 7 days. The milk yield
from the individual animals were collected and recorded daily twice a day at 08:00 hrs and at 16:00
hrs. Animals were dewormed at the start of the experiment, sprayed and had constant access to clean
drinking water.
Table 7.7.1: Amount and cost of ingredients used in formulation of concentrates
Ingredient
CP (%) Inclusion
level (kg)
Unit cost
(Ushs)
Cost of
concentrate with
no bentonite/
premix
Cost of
Bentonite
concentrate
Cost of premix
concentrate
Maize stover 6 20 50 1,000 1,000 1,000
Maize bran 10 20 500 10,000 10,000 10,000
Molasses 5 30 330 9,900 9,900 9,900
Cotton seed 45.2 10 1400 14,000 14,000 14,000
Calliandra
hay
28.3 15 300 4,500 4,500 4,500
Bentonite - 5 1000 5,000
Premix - 1 5000 5,000
Cassava our - 4 1500 6,000
Total cost 39,400 44,400 50,400
Results and Discussion
During the 7 days of data collection on milk production, highest milk yields were recorded from
groups fed concentrates containing CB (Figure 7.7.1). Considering the price of a litre of milk to be
Ushs 1000, for every shs 197 used in control supplements, Ushs 500 were received in return. Where
concentrates containing bentonite were used, Ushs 2000 was obtained for every Ushs 222 while Ushs
1200 was obtained for every Ushs 252 used in premix concentrates. Bentonite clays have binding
properties, and when used, there is no need for use of other binders like cement and cassava our.
This therefore reduces the cost of bentonite concentrates as compared to premix based concentrates
and thus increases the returns per unit cost.
150
Figure 7.7.5: Variations in milk yield during the treatment
Because of its expanding properties, bentonite reduces the rate of feed passage through the
animal’s digestive system. The increased retention rate of digesta hence increases the amount of
nutrients absorbed into the animal’s body and contribute to increased milk yield as compared to
other concentrates where rate of digesta ow is not altered. The aatoxin and mycotoxin absorbing
properties of bentonite also help in reducing the negative impacts of aatoxin on feed utilization,
growth and milk yield of animals. As such, bentonite supplemented cows gave more milk than their
counterparts. Also note: Bentonite acts as pH regulators in the rumen, as they control pH, they enable
animals to increase dry matter intake.
Conclusion
It seems logical to conclude that CB has a potential to supply the required nutrients to lactating animals
to sustain high levels of milk production at even a much lower cost. It is recommended that more
studies are required to establish the appropriate levels of inclusion in lactating animals’ feed and
where possible develop a mineral premix for various animals including goats and sheep.
151
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aatoxin and T-2 toxin in broiler chickens. Poult. Sci. 67 (10), 1418–1423.
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152
7.8 Multiplication of Brachiaria hybrid cv. Mulato 1 planting materials for livestock
productivity enhancement (Short communication)
1Mwesigwa Robert ; 2Kabirizi Jolly Mary, 1Kajobe R.and 2Mugerwa Swidiq
1Rwebitaba Zonal Agricultural and Research Development Institute, P.O BOX 96 Fort-Portal
2National Livestock Resources Research Institute (NaLIRRI), P.O. Box 96, Tororo
Introduction
Brachiaria is a perennial grass native to East and Central Africa. A number of studies have shown that
the species is of high nutritive value (Frederiksen and Kategile, 1980) and therefore has the potential
to revolutionize grassland farming and animal production. This potential however, remains largely
unexploited by smallholder farming communities. This is because of the planting materials are scarce
which impedes there accessibility by the farming communities. As such, wider adoption of Brachiaria
as forage in the farming is limited and the positive impacts it brings to livestock improvement and
productivity is therefore felt by developed livestock farmers who have the purchasing power and
smallholders are left out as they cannot afford the cost of the planting materials. In Uganda, availing
improved pasture planting materials to smallholder farming communities has been a daunting
challenge mostly for the pasture species with very low seed viability like Brachiaria ssp. As such,
there multiplication has been mainly through getting Brachiaria stools, cutting it into smaller pieces
and planting them in multiplication gardens. At maturity, these are then dug out from the garden
and put into sacks for the farmers to multiply at their farms. Despite having worked for quite long in
improving pasture production and there animal production, this has been quite challenging practice.
As there has been slow progress in terms of availing planting materials to the farmers mostly due
to the high operational costs in terms labor for opening the multiplication area and its eventual
maintenance. Mugerwa et al. (2012) stated that efforts aimed at integration of introduced forages into
smallholder diary systems need to focus on high yielding forages as well as insuring availability of
adequate sources of planting materials. This can only be realized through innovative multiplication
path ways. In an attempt to realize this goal, multiplication of Brachiaria splits under nursery was
thought of and through this innovative approach, we have managed to raise thousands of seedlings
as illustrated below.
153
Procedure
Top loam soils, cow dung and sand are mixed in ratio of 10:5:3 wheel barrows respectively. The
mixture is then potted in polythene bags, Brachiaria cuttings with viable roots and buds are then cut
and put in the potted media under nursery shade (one small cutting per pot). These are then watered
twice in a day (morning and evening). Sprouting of the cutting starts within 3 weeks and in 10 weeks
time they are ready for planting in the main eld.
Advantages of multiplication under nursery
Thousands of Brachiaria splits can be raise in small space as shown in plates above and therefore
many farmers can be availed with the planting material in a short interval Management of the splits
under nursery is easy as compared to direct planting in the eld. Less labor is required to raise these
seedlings under shade compared to raising them directly in the eld.
Conclusion
Multiplication of improved Brachiaria splits under nursery comes at a point of rampant outcry for
improved pasture seed by livestock stock farmers. It is envisaged to bridge this gap and hence an
important step to revolutionize grassland farming and animal production not only in Uganda but
globally.
Acknowledgement
We acknowledge the nancial support from Eastern Africa Agriculture Productivity Project (EAAPP)
References
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smallholder dairy farmers in Uganda. International Journal of Bio sciences Volume 2. Page: 36-45
154
PUBLICATIONS
Journal publications
1. Atuhaire Andrew Mwebaze; Swidiq Mugerwa; Samuel Okello; Kenneth Okello Lapenga;
Fred Kabi and Jolly Kabirizi. 2014. Prioritization of crop residues for improving productivity
on smallholder dairy farming households in the Lake Victoria Crescent, Uganda. Open
Journal of Animal Science, 2014.103-114.
2. Atuhaire, Andrew M., Mugerwa, Swidiq., Kabirizi, Jolly., Okello, Samuel., Kabi, Fred.,
2014. Production Characteristics of Smallholder Dairy Farming in the Lake Victoria Agro-
ecological Zone, Uganda Frontiers in Science 2014, 4(1): 12-19 DOI: 10.5923/j.fs.20140401.03
3. Atuhaire, Andrew M., Mugerwa, Swidiq., Okello, Samuel., Lapenga, Kenneth., Kabi,
Fred., Lukwago, George 2014. Prioritization of Agro-industrial By-products for Improved
Productivity on Smallholder Dairy Farms in the Lake Victoria Crescent, Uganda Frontiers in
Science 2014, 4(1): 1-7 DOI: 10.5923/j.fs.20140401.01
4. Kabirizi, J.; Zziwa, E.; Mugerwa, S. and Namagembe. A. 2013. Dry season forages for
improving dairy cattle production in smallholder dairy systems. In: David L Michalk et. al.,
2013. Revitalising Grasslands to Sustain our Communities: Proceedings 22nd International
Grassland Congress, Sydney, Australia pp 812-814. Print ISBN: 978-1-74256-543-9
5. Kabirizi, J.; Ndikumana, J.; Zziwa, E.; Mugerwa, S. and Asuma, J. 2013. The potential of
Brachiaria hybrid cv. Mulato as a feed resource in smallholder dairy systems. rst Special
Issue IGC2013 with all papers belonging to the IGC 2013 session 1.2.1 (“Development and
Impact of Sown Tropical Species”);
http://tropicalgrasslands.info/index.php/tgft/issue/current/showToc.
6. Kabirizi, J.. 2015. Climate change forage technologies for improved livelihoods of
smallholder crop–livestock farmers in ECA. In: J. A. Francis. 2015. Agricultural innovations
for sustainable development. Contributions from the 3rd Africa-wide women and young
professionals in science competition. Synthesis report: lessons learned. Vol. 4: issue 3. pp. 75-
82.
7. Kawube, G.; Talwana, H.; Nicolaisen, M.; Alicai, T.; Otim, M.; Kabirizi, J.; Mukwaya, A.;
Steen Lykke Nielsen. 2014. Napier grass stunt disease prevalence, incidence, severity and
genetic variability of the associated phytoplasma in Uganda. Elsevier Crop Protection 75
(2015) 63-69.
8. Kawube, G.; Alicai, T.; Otim, M.;. Mukwaya, A.;. Kabirizi, J. and Talwana. H. 2014.
Resistance of napier grass clones to napier grass stunt disease. African Crop Science Journal,
Vol. 22, No. 3, pp. 229 – 235
9. Kawube, G.; Kabirizi, J.; and Namazzi, C. 2014. Genetic characterization of Alupe
napier grass accessions based on simple sequence repeat markers. American Journal of
Experimental Agric.. http://www.sciencedomain.org/articles-press.php (2015)
10. Mugerwa, S.; Zziwa, E. and Kabirizi. J. 2014. Effect of fortifying Aatoxin-contaminated
feeds with Ugandan bentonite on performance of broiler birds. App. Sci. Report.3 (1), 2013:
106-109.
11. Mwesigwa , R.; Kabirizi, J.M.; Kajobe, R.and Mugerwa. S. 2015. Multiplication of
improved Brachiaria planting materials for livestock productivity enhancement (Short
communication). Livestock Research for Rural Development 27 (2) 2015. http://www.lrrd.
org/public-lrrd/proofs/lrrd2702/mwes27025.html
155
12. Omayio D.O. SI Ajanga, JV Muoma DMW. Ochieno, FN Muyekho, B Mukoye and RK
Leitich (2014). Predicting Endophytes Contribution In vivo in Napier Grass Accessions’
tolerance against Ustilago kamerunensis Using In vitro Strategies. Journal of Agri-Food and
Applied Sciences (JAAS Journal.). Vol. 2(10), pp. 296-303, 31 October, 2014
13. Omayio DO, SI Ajanga, JV Muoma, DMW Ochieno, FN Muyekho, B Mukoye and RK Leitich
(2014). Predicting Endophytes Contribution In vivo in Napier Grass Accessions’ tolerance
against Ustilago kamerunensis Using In vitro Strategies. Journal of Agri-Food and Applied
Sciences (JAAS Journal.) Vol. 2(10), pp. 296-303, 31 October, 2014
14. Omayio DO, SI Ajanga, JV Muoma, FN Muyekho and I Kariuki (2014). Internal Transcribed
Spacer Primers Detect Better Ustilago kamerunensis; A Napier Grass Head Smut Pathogen
Constraining the dairy sector in Eastern Africa. Journal of Agri-Food and Applied Sciences
(JAAS Journal.) Vol. 2(9), pp. 265-274, 30 September, 2014
15. Swidiq Mugerwa, Emmanuel Zziwa and Jolly Kabirizi. 2014. Effect of fortifying Aatoxin-
contaminated feeds with Ugandan bentonite on performance of broiler birds. App. Sci.
Report.3 (1), 2013: 106-109.
Conference/workshop papers
1. Awalla B. J., Skilton R., Muyekho F.N., Were B., Mulaa M., Wanjala B. and Kawube G.
(2013). Genetic diversity of Napier grass using Simple Sequence Repeats (SSR) in Western
Kenya. In EAAPP Conference on enhancing regional specialization in Technology and
Dissemination for increased agricultural productivity. 12th to 13th November 2013. Book of
Abstract page 24 [Proceedings in preparation]
2. Baguma, Y. and Kabirizi, J. 2014 The role of Science, Technology and Innovations in
Improving Performance of Livestock Value Chains in Africa, Paper presented during
African Livestock Conference and Exhibition held at Speke Resort Hotel, Munyonyo, 20th to
24th June 2014
3. Kabirizi, J,; Zziwa, E.; Mugerwa, S. 2013. Participatory evaluation of improved feed
technologies in war affected smallholder dairy farming systems of Uganda. 10th African
Crop Science Society Conference, Imperial Botanical Gardens, Entebbe, 14th to 17th October
2013
4. Kabirizi, J,; Zziwa, E.; Mugerwa, S.; Ndikumana, J. and Lukwago, G. 2014. Climate Smart
Forage Technologies for Improving Dry Season Feeding in Smallholder Dairy Systems.
Proceedings of the Second Biennial National Agricultural Research Organization Scientic
Conference 3rd to 7th November 2014 held at Munyonyo Resort Hotel, Kampala, Uganda
5. Kabirizi, J. 2015.A review of forage research and development in Uganda. Paper presented
during the “Forages for Africa meeting held at the Institute of Biological, Environmental &
Rural Sciences (IBERS), Aberystwyth University, Aberystwyth, Ceredigion, SY23 3EE, UK,
26th to 29th February 2015
6. Kabirizi, J.; Mugerwa, S.; Lukwago, G.; Zziwa, E. 2014. Strategies to improve year-round
feed supply in smallholder dairy systems. Paper presented during the 16th International
Conference for Women Engineers and Scientists (ICWES16): 20th to 28th October 2014, Los
Angeles, California, USA.
7. Kabirizi, J.; Mugerwa, S.; Namazzi, C.; Kawube, G.;.Nampijja, Z
Lukwago, G. and Mulaa. M. 2013. Evaluation of Napier grass (Pennisetum Purpureum)
accessions for tolerance to Napier stunt disease. Proceedings of EAAPP Mini-Scientic
Conference Held at the Regional Dairy Centre of Excellence, 12th to 15thh November
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2013, Kenya Agricultural Research Institute, Naivasha. http://www.rdcoe.or.ke/disease_
challenges
8. Kabirizi, J.; Mugerwa, S.; Ziwa, E.; Lukwago, G.; Namazzi, C. 2012. Napier stunt disease
incidence, severity and management in Uganda. Proceeding of the Annual Scientic
Symposium of the Animal Production Society of Kenya, April 11th to 13th 2012.Green Hills
Hotel, Nyeri. Kenya. pp 30-35.
9. Kabirizi, J.; Ndikumana, J.; Zziwa, E.; Mugerwa, S. and Asuma, J. 2013. The potential of
Brachiaria hybrid cv. Mulato as a feed resource in smallholder dairy systems. Book of
Abstracts of the 2013 Annual Symposium and Annual General meeting (AGM) of the
Animal Production Society of Kenya, 11th to 12th April 2013. pp.24.
10. Kabirizi J.; Mugerwa, S.; Lukwago, G.; Ziwa, E. and Ndikumana, J. 2014. Strategies to
improve year-round feed supply in smallholder dairy cattle production systems in Eastern
Africa. Paper presented during the 16th International Conference for Women Engineers and
Scientists (ICWES16), Los Angeles, California, October 23-25, 2014
11. Kabirizi, J.; Zziwa, E.; Lukwago, G.; Namazzi, C.; Kigongo, J. 2014. Enhancing the
contribution of maize to food and fodder security in smallholder dairy production systems.
Paper presented during the African Livestock Conference and Exhibition, 18th to 20th June
2014, Speke Resort Hotel, Munyonyo
12. Kabirizi, J.; Mwesigwa, R. and Nvviri, G. 2015. Forage research and development in Uganda.
Paper presented during “Forages in Eastern and Central Africa” meeting held at Beca-ILRI,
Nairobi, Kenya (26th to 28th May 2015)
13. Khan, Z.R., P. Chiliswa, K. Ampong-Nyarko, L.E. Smart, A. Polaszek, J. Wandera, and M.A.
Mulaa. 1997. Utilisation of wild gramineous plants for management of cereal stemborers in
Africa. Insect Science and its Application 17: 143-150.
14. Kigongo, J.; Birthe K. P,; Zziwa E., Brigitte L. Maass, Kabirizi, J..2013. Evaluating drought
tolerant improved forage legumes for enhanced smallholder dairy productivity in Uganda.
Paper presented during Tropentag, September 17-19, 2013, Stuttgart-Hohenheim, Germany
“Agricultural development within the rural-urban continuum”
15. Mugerwa, S.; Kabirizi, J.; Ziwa, E.; Lukwago, G. 2012. Utilization of crop residues and agro-
industrial by-products in livestock feeds and feeding systems in Uganda. Proceeding of the
Annual Scientic Symposium of the Animal Production Society of Kenya, April 11th to 13th
2012.Green Hills Hotel, Nyeri. Kenya. pp 151-157.
16. Mugerwa, S.; Kabirizi, J.; Ziwa, E.; Lukwago, G. 2012. Utilization of crop residues and agro-
industrial by-products in livestock feeds and feeding systems in Uganda. Proceeding of the
Annual Scientic Symposium of the Animal Production Society of Kenya, April 11th to 13th
2012.Green Hills Hotel, Nyeri. Kenya. pp 151-157.
17. Munyasi J.W., E.O. Auma, L. Ngode L and F.N. Muyekho (2014). Effects of moisture regimes
and fertilizer levels on morphological characteristics and biomass yield of alternative fodder
grasses to Napier grass in western Kenya. Paper presented at the Egerton University Annual
conference [Proceedings in preparation]
18. Mwesigwa I. and Kabirizi, J. 2014. Engaging the youth in agricultural production for food
Security and income generation. Paper presented during the African Livestock Conference
and Exhibition, 18th to 20th June 2014, Speke Resort Hotel, Munyonyo
19. Mwisa P., F. Muyekho, M. Mulaa, D, Ndege and R. Gitonga. 2013. Effects of Napier
Accessions in the validation tissue culture protocol for mass production of diseases
free planting materials. In EAAPP Conference on enhancing regional specialization
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in Technology and Dissemination for increased agricultural productivity. 12th to 13th
November 2013. Book of Abstract page 29 [Proceedings in preparation]
20. Namazzi C.S, Hanson J, Proud J, 1Kabirizi.J, Mulaa M; Pallangyo B. 2011. Evaluations of
Napier grass clones for nutritive quality and the potential effect of stunt and smut diseases.
ASARECA Livestock And Fisheries Programme Scientic Conference held at Hotel Source
du Nil, Bujumbura, Burundi, 30thOctober to 4th November 2011
21. Nampijja, Z., Kabirizi, J, Zziwa E, Mugerwa, S, Namazzi, C..; Lukwago, G. Evaluation of
Napier grass clones for performance and tolerance to Napier stunt disease in Eastern and
Central Africa. Paper presented during the 2nd ASARECA General Assembly and Scientic
conference, 9th to 13th December 2013, Bujumbura
22. Nampijja, Z.; Kabirizi, J.; Mugerwa, S.; Lukwago, G.; Zziwa, E. 2014. Evaluation of Napier
grass clones for herbage biomass yield and tolerance to Napier stunt disease Paper
presented during the 16th International Conference for Women Engineers and Scientists
(ICWES16): 20th to 28th October 2014, Los Angeles, California, USA
23. Okitoi, L.O., M. Khasatsili, F.N. Muyekho, M. Mudeheri, J. Ojiem, T.A. Onyango and F.P.
Wandera (2013). Availability and utilization of crop residues in feeding dairy cattle in
western Kenya. In: EAAPP Conference on enhancing regional specialization in Technology
and Dissemination for increased agricultural productivity. 12th to 13th November 2013.
page 12 [Proceedings in preparation]
24. Okitoi, L.O., M. Khasatsili, F.N. Muyekho, M. Mudeheri, J. Ojiem, T.A. Onyango and
F.P. Wandera (2013). The potential of crop residue based compacted total mixed rations
to supply balanced feeds to dairy cattle. In EAAPP Conference on enhancing regional
specialization in Technology and Dissemination for increased agricultural productivity. 12th
to 13th November 2013. page 14 [Proceedings in preparation]
25. Omayio D.O., J.V. Muoma, F.N. Muyekho and S.I. Ajanga (2014). A Probable Case of
Quantitatively Controlled Antibiosis Strategy of Pathogen Resistance against Napier Grass’
Head Smut. Paper presented at the Egerton University Annual conference [[Proceedings in
preparation]
26. Omayio D.O., Muoma J.V., Muyekho F.N., Kariuki I. and S.I. Ajanga (2013). A novel
technique in estimating the magnitude of established quantitative resistance in selected
Pennisetum purpureum (Schum.) accessions against headsmut disease. In EAAPP
Conference on enhancing regional specialization in Technology and Dissemination for
increased agricultural productivity. 12th to 13th November 2013. Book of Abstract page 25
[Proceedings in preparation]
27. Omayio D.O., Muoma J.V., Muyekho F.N., Kariuki I. and S.I. Ajanga (2013). Ustilago
kamerunensis P. and H. Sydow, imposed resistance and its signicance to Napier grass
(Pennisetum purpureum Schum.) farmers in mitigating head smut disease challenges. In
EAAPP Conference on enhancing regional specialization in Technology and Dissemination
for increased agricultural productivity. 12th to 13th November 2013. page 27 [Proceedings in
preparation]
28. Wamalwa, N. E. Midega A.C., Ajanga S., Omukunda N. E., Ochieno D., Omayo D. Muyekho
F., Mulaa M. Z. Khan (2013). Napier grass accession 16789 tolerant to Napier stunt disease
(Phytoplasma 16SRXI) constraining dairy industry in Western Kenya/Eastern Africa. In
EAAPP Conference on enhancing regional specialization in Technology and Dissemination
for increased agricultural productivity. 12th to 13th November 2013. Pp. 26 [Proceedings in
preparation]
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29. Wanyama J.M., F.N. Muyekho, N.F. Lusweti, E. Omamo, K.N. Wairimu, N. Kariuki, and J.C.
Komen (2013). Household livelihood strategies in crop-livestock systems in North-West and
Western Kenya. In EAAPP Conference on enhancing regional specialization in Technology
and Dissemination for increased agricultural productivity. 12th to 13th November 2013.
page 43 [Proceedings in preparation]
Books
1. Kabirizi, J.M.; Mugerwa, S.; Kirunda, H.; Lukwago, G.; Oluka J.; Butungi, S.; Ssemabo,
D.K.K.; Mubiru, F.; Nakimbugwe, H. 2014. Feed resources management, genetic
improvement and disease control in smallholder dairy systems. ISBN 9789970926909
2. Kabirizi, J.; Muyekho, F.; Mulaa, M; Kawube, G.; Msangi, R.; Pallangyo, B.; Zziwa, E.;
Mugerwa, S.; Ajanga,S.; Lukwago, G.; Wamalwa N.I. E; Kariuki, I.; Mwesigwa, R.;
Nannyeenya-Ntege, W.; Atuhairwe, A.; Awalla, J.; Namazzi, C.; Nampijja, Z. 2015. Napier
grass feed resource: production, constraints and implications for smallholder farmers in
Eastern and Central Africa. ISBN: 978-9970-9269-1-6
Book chapter
Kabirizi, J. et al., 2015. Forage research and development activities in Uganda (1950-2015) In:
Ghimeri, S. et al. 2015. Forage research in Eastern and Central Africa. [In preparation]
Farming information materials, manuals, posters leaets and brochuress
1. Brachiaria hybrid cv mulato as an alternative forage for smallholder dairy farmers by
Kabirizi, J.; Mugerwa, S. and Lukwago, G.
2. EAAPP: Dairy research component manual by Kabirizi, J.; Kirunda, H. and Oluka, J. and
Lukwago, G.
3. Enhancing adoption of napier grass varieties tolerant to stunt disease for increased feed
availability in smallholder dairy systems in East and Central Africa: Achievements
(September 2011- February 2013) and Planned activities (2013-2014) Newsletter March 2013
by Kabirizi, J.
4. Enhancing Adoption of Napier Grass Varieties Tolerant to Stunt Disease for Increased
Feed Availability in Smallholder Dairy Systems in East and Central Africa: Achievements
(February 2013 by Kabirizi, J.
5. Establishment and Management of Chaloris gayana (Rhodes grass) fodder and seed crop by
Kabirizi, J.
6. Establishment and Management of Lablab purpureus (Lablab) fodder and seed crop by
Kabirizi, J.
7. Establishment and Management of Napier grass (Pennisetum purpureus) by Kabirizi, J.
8. Grow fodder sorghum for increased milk yield in Napier stunt and smut diseases affected
areas by Muyekho, F.N., M. Shisya, S. Ajanga, S. Mwendia, M. Masibili, J. Wamalwa, G.
Sudi, M. Mulaa and D.T. Cheruiyot (Published in 2013)
9. Grow giant setaria grass for increased milk production in napier stunt disease affected
areas by: Cheruiyoti, D.T., F.N. Muyekho, M. Masibili, S. Ajanga, M. Mulaa, M. Shisya, J.
Wamalwa, G. Sudi and S. Mwendia (Published 2013)
159
10. Grow Guatemala grass for increased milk yield in napier stunt disease affected areas by:
Muyekho, F.N., M. Masibili, S. Ajanga, M. Shisya, J. Wamalwa, G. Sudi M. Mulaa, S.
Mwendia and D.T. Cheruiyoti (Published in 2013)
11. Grow Mulato I and II grass for increased milk yield in Napier stunt disease affected areas
by Muyekho, F.N., M. Masibili, S. Ajanga, S. Mwendia, M. shisya, J. Wamalwa, G. Sudi, M.
Mulaa and D.T. Cheruiyoti (Published 2013)
12. Grow Panicum grass for increased milk yield in Napier stunt and smut diseases affected
areas by: Shisya, M., F.N. Muyekho, S. Ajanga, M. Masibili, J. Wamalwa, S. Mwendia, G.
Sudi, M. Mulaa and D.T. Cheruiyoti (published 2013)
13. Guidelines for production of disease-free Napier grass seed by Ajanga S., Muyekho F.N.,
Mulaa M., MwendiaS., Kariuki I., Masibili M., Shisya M., Wamalwa J., Cheruiyot D.T. and
Sudi G. (Published in 2013)
14. Improving nutritive quality and acceptability of grass hay and maize stover by Kabirizi, J.
15. Improving year-round feed supply: Feeding hay to dairy cows by Kabirizi, J.; Mugerwa, S.
and Lukwago, G.
16. Multiplication of Brachiaria planting materials: An innovative approach by Mwesigwa, R.;
Kabirizi, J. and Mugerwa, S.
17. Napier grass seed production guidelines to manage stunt and smut diseases by Ajanga,
S., F.N. Muyekho, M. Mulaa, S. Mwendia, J. Wamalwa, I. Kariuki, J., M. Masibili, S. M.
Shisya and G. Sudi. (Published 2013).
18. Napier stunt disease management by Kabirizi, J.
19. Napier stunt disease management strategies for increased feed availability in smallholder
farming systems in East and Central Africa by Kabirizi, J.
20. Nutrient feed block supplement for lactating goats and cattle by Kabirizi, J.
21. Silage making for small-scale dairy farmers by Kabirizi, J.; Mugerwa, S. and Lukwago, G.
22. Simple hay making method using a pit by: Sudi, G., F.N. Muyekho, M. Shisya, S. Ajanga, S.
Mwendia, M. Masibili, J. Wamalwa, G. Sudi, M. Mulaa and D.T. Cheruiyoti (Published 2013)
23. Smallholder silage making for dry season feeding by: Masibili, M., F.N. Muyekho, S. Ajanga,
S. Mwendi
24. Small-scale forage seed production by Kabirizi, J.; Mugerwa, S. and Lukwago, G.
25. Smut disease threatens napier grass production by: Wamalwa J., Muyekho, F.N., S. Ajanga,
M. Mulaa, M. Shisya, S. Mwendia, M. Masibili, G. Sudi, and D.T. Cheruiyoti (Published
2013)
26. Stop the spread of Napier stunt disease: by following recommended disease management
practices by Ajanga S., F.N. Muyekho, Mulaa, M., S. Mwendia, J. Wamalwa, I. Kariuki, M.
Masibili, M. Shisya and G. Sudi D.T. Cheruiyot (Published 2013).
27. Tips to a protable zero grazing dairy cattle enterprise by Kabirizi, J.; Mugerwa, S. and
Lukwago, G.
160
ISBN: 978-9970-9269-1-6
© The Eastern Africa Agricultural Producvity Project (EAAPP)
All rights reserved. The contents of this publicaon may be reproduced for non-
commercial purpose provided the Eastern African Agricultural Producvity Project
(EAAPP) and the Associaon for Strengthening Agricultural Research in Eastern and
Central Africa (ASARECA) are acknowledged.
Correct citaon: Kabirizi, J.; Muyekho, F.; Mulaa, M; Msangi, R.; Pallangyo, B.; Kawube, G.;
Zziwa, E.; Mugerwa, S.; Ajanga,S.; Lukwago, G.; Wamalwa N.I. E; Kariuki, I.; Mwesigwa,
R.; Nannyeenya-Ntege, W.; Atuhairwe, A.; Awalla, J.; Namazzi, C.; Nampijja, Z. 2015.
Napier grass feed resource: producon, constraints and implicaons for smallholder
farmers in Eastern and Central Africa.
ISBN: 978-9970-9269-1-6
NAPIER GRASS FEED RESOURCE:
PRODUCTION, CONSTRAINTS AND
IMPLICATIONS FOR SMALLHOLDER
FARMERS IN EASTERN AND CENTRAL
AFRICA
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