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ISSN No. 2319-3670
Journal
of
Rice Research
Volume 6, No. 2 December 2013
Society for
Advancement of
Rice Research
Journal of Rice Research
Volume 6: Issue No. 2 December 2013
CONTENTS
Page No.
Invited Paper
Site Suitability Analysis of SRI (System of Rice Intensification) Cultivation in
Potential Rice Cropped Areas of Andhra Pradesh: A Geospatial Approach
Anima Biswal, M.V.R. Sesha Sai, K.V. Ramana, S.V.C. Kameswar Rao and G. Sujatha
Contributed Papers
Variability and Association Studies for Yield Components and Quality Parameters
in Rice Genotypes
B. Krishna Veni, B. Vijaya Lakshmi and J.V. Ramana
Genetic Variability, Correlation and Path Analysis for Quantitative Characters in
Rainfed Upland Rice of Uttarakhand Hills
J. P. Aditya and Anuradha Bhartiya
Study on Grain and Water Productivity of Rice-Zero-Till Maize Cropping System
D. Sreelatha, M. Srinivasa Raju, M. Devender Reddy, G. Jayasree and D. Vishnu Vardhan Reddy
Influence of Long Term Fertilizer Application on Soil Phosphatase Enzyme
Activity and Nutrient Availability in Rice –Rice Cropping System
M. Srilatha, Palli Chandrasekhar Rao, S.H.K. Sharma and K. Bhanu Rekha
Relative Composition of Egg Parasitoids of Rice Yellow Stem Borer, Scirpophaga
incertulas (Walker) at Rajendranagar, Andhra Pradesh, India
N. Rama Gopala Varma, R. Jagadeeshwar and Chitra Shanker
Study on Bio-Efficacy of Certain Acaricides Alone and in Combination with
Propiconazole against Rice Panicle Mite, Stenotarsonemus Spinki Smiley
A. Venkat Reddy, R. Sunitha Devi, S. Dhurua and D. Vishnu Vardhan Reddy
Compatibility of Fungicides and Insecticides Targeting Sheath Blight and Major
Rice Pests
V. Bhuvaneswari and S. Krishnam Raju
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16
24
35
45
53
59
64
1 Journal of Rice Research 2013, Vol. 6 No. 2
Invited Paper
Site Suitability Analysis of SRI (System of Rice Intensification) Cultivation in
Potential Rice Cropped Areas of Andhra Pradesh: A Geospatial Approach
Anima Biswal*, M.V.R. Sesha Sai,,K.V. Ramana, S.V.C. Kameswar Rao and G. Sujatha
Agricultural Sciences Application Group,Soil & Land Resources Assessment Division,
National Remote Sensing Centre, ISRO, Hyderabad, Andhra Pradesh
Abstract
The study was undertaken to characterize
the soils of Andhra Pradesh, India, for
soil-suitability evaluation for SRI (System
of Rice Intensification) cultivation in
potential rice cropped areas using remote
sensing and geographic information
system based multi criteria evaluation.
The soil attributes selected for suitability
analysis for SRI rice are soil drainage, soil
depth, soil texture and soil salinity. The
study clearly brought out the spatial
distribution of rice crop derived from
remote sensing in conjunction with
evaluation of soil suitability for SRI
method of rice cultivation. The study
indicates that about 21.67 lakh ha. of
potential rice area is highly suitable for
SRI followed by 11.41 lakh ha. of
moderately suitable area. A marginal
area of 37,102.96 thousand ha. was
identified as slightly suitable for SRI
method of rice cultivation in Andhra
Pradesh.
*Corresponding author: anima.biswal@gmail.com
Key words: Site suitability, SRI, geospatial
approach, remote sensing, GIS.
The System of Rice Intensification (SRI) is
a method of rice cultivation that involves
efficient utilization of natural resources
along with judicious use of external inputs
to produce optimum rice yields. SRI is a
method of agronomic management of rice
cultivation for increasing the yield of rice
per unit area per unit time with reduced seed
and water requirement and modified soil
(field) ecosystem with special and
mechanical arrangements. This improved
method of rice cultivation was developed in
1983 in Madagascar by Fr. Henri de Lau
Lanie in association with a non government
organization –Association Tefy Saina
(ATS) and with many small farmers which
has later spread to many countries. SRI
cultivation is a system rather than a
technology and is based on the insights that
rice has the potential to produce more tillers
and grains than conventional method and
2 Journal of Rice Research 2013, Vol. 6 No. 2
that early transplanting and optimal growth
conditions, spacing, humidity, biologically
active and healthy soil and aerobic soil
conditions during vegetative growth can
fulfill this potential. Major SRI principles
include: (1) raising seedlings in well
managed nurseries (2) careful transplanting
of single and young (8–15 days old)
seedlings at wide plant spacing (starting at
25 x 25 cm, but going up to 50 x 50 cm) (3)
intermittent application of irrigation to avoid
permanent flooding during the vegetative
growth phase (4) addition of nutrients to the
soil, preferably organic manures and
amendments instead of chemical fertilizer
(5) intensive manual or mechanical weed
control without the use of herbicides.
Sridevi and Chellamuthu (2012) reported
that when all these principles are followed, it
profoundly enhanced the growth and
nutrient uptake which in turn improved the
yield attributes and yield. The enhancement
in the performance of rice was linearly
proportional to the number of SRI
components being practiced. As the SRI
components increase, the performance of
rice enhances. SRI that evolved in the 1980s
in Madagascar is also gaining popularity in
India. SRI saves not only the seed (a seed
rate of 5–7 kg/ha as against 25–30 kg/ha for
normal) but also saves water (35–40%) as
the fields are not inundated continuously
(Ghritlahre et al., 2012; Nay-Htoon et al.,
2013;Thakur et al., 2010). Rice is the major
crop under canal, tank, and tube well
irrigation systems in AP, with groundwater-
based systems now constituting 50% of the
gross irrigated area in the state. The normal
practices of rice cultivation include
transplanting seedlings about 25 days old,
with a seed rate of 60-75 kg ha-1, and
continuous inundation of water until the
grain filling stage. The large-scale shift from
canal and tank irrigation to reliance on wells
has placed stressful demands on the state’s
groundwater resources, with extraction
exceeding recharge rates in several parts of
Andhra Pradesh. The System of SRI was
diffused first to Tamil Nadu State in India
during the year 1999 (Johnson and
Vijayaragavan, 2011; followed by Andhra
Pradesh with systematic evaluation in on-
farm comparison trials across all districts of
the state. Although SRI has not spread
across the state on a large scale, experiences
in a number of areas can be assessed for its
potential adaptation. Andhra Pradesh (AP) is
among the several states considered as ‘SRI-
adopting’ and hence, its diffusion process is
of scientific interest. Ravindra and Laxmi,
(2011) evaluated the Potential of the system
of rice intensification for systemic
3 Journal of Rice Research 2013, Vol. 6 No. 2
improvement in rice production and water
use in Andhra Pradesh. Scientists from the
Directorate of Rice Research, Hyderabad
conducted field experiments from 2008 to
2010 and concluded that SRI practices
creates favourable conditions for soil
microbes to prosper, save irrigation water
and increase grain yield (Gopalakrishnan et
al., 2013). SRI can become a viable
alternative approach to the conventional
transplanting having advantage of both in
terms of higher yield and water productivity
especially, in the areas of limited water
situations (Kumar et al., 2011).
Suitability is a function of crop
requirements and land characteristics
(Mustafa et al., 2011). In order to explore
the potential areas suitable for SRI,
knowledge of soils, their properties, and
spatial distribution is indispensable as it
opens opportunities for a more rational
management of the soil resources.
Development of a GIS-based thematic
database on soils is vital in crop-suitability
analysis for optimal utilization of available
resources (Coleman and Galbraith, 2000).
Weighted overlay analysis is a component of
spatial modeling using spatial multi-criteria
evaluation. Weighted overlay analysis
assigns more importance to some criteria
over others (Hailegebriel, 2007; Zelalem,
2007). Multi-Criteria Evaluation (MCE)
approaches and GIS is useful because
various production variables can be
evaluated and each weighted according to
their relative importance on the optimal
growth conditions for crops (Perveen et al.,
2007). In the present study, multi-criterial
overlay analysis was carried out for soil site
suitability for SRI method of rice cultivation
in the potential rice growing area of Andhra
Pradesh using GIS and remote sensing
techniques.
Study area
Andhra Pradesh is selected for this study in
order to evaluate the soil suitability classes
for potential adaptation of SRI in the
existing rice area. The state has 13.83
million ha of gross cropped area out of
which 4.82 million ha is the net irrigated
area with an irrigation intensity of 1.39
(2008-2009). In Andhra Pradesh, rice is
grown in 22 districts, out of which 14
districts are falling under high productivity
group, that is, yield more than 2500 kg/ha.
More than 85 per cent of rice in the State is
grown under different sources of irrigation
under puddle condition whereas out of the
rest, 10 per cent rice area lies in the rain-fed
low land ecosystem and 5 per cent in the
rainfed system.
4 Journal of Rice Research 2013, Vol. 6 No. 2
Materials and Methods
For carrying out the soil suitability analysis,
a geo-referenced digital soil map with
attributes like drainage, texture, depth and
salinity, etc., is required that could be used
as a reference map. For this study,
NBSSLUP soil map of 1:250,000 scale is
used. The digital soil map of AP consists of
1249 polygons linked with an attribute table.
Lambert Conformal Conic projection and
Geographical coordinate system with WGS
84 datum was used in ARC GIS to generate
all the thematic layers. The attributes
selected for suitability analysis for SRI rice
are: (1) Soil drainage (2) Soil depth (3) Soil
texture (4) Soil salinity. The suitablity
criteria of these properties are evaluated
independently prior to jointly ranking them
followed by multi criteria overlay analysis in
GIS. The detailed methodology is presented
in Fig. 1.
Fig. 1 Flow chart showing the methodology
5 Journal of Rice Research 2013, Vol. 6 No. 2
Satellite DataAWiFS (Advanced Wide
Field Sensor)
Potential rice area mask was generated using
IRS-P6 (AWiFS) images. IRS-P6 (AWiFS)
has a spatial resolution of 56 m, four
spectral channels (green (0.52–0.59μm), red
(0.62–0.68μm), near infrared (NIR: 0.77–
0.86μm) and short-wave IR (SWIR: 1.55–
1.70μm)) and a temporal resolution of 5
days with a 740 km swath width. Time
series AWiFS images pertaining to the study
area were processed in ERDAS IMAGINE
software. AWIFS images were geo-
referenced with Survey of India (SOI)
topographic map (1:250,000). With ground
truthing, supervised classification was
carried out using maximum likelihood
algorithm. The accuracy of the classification
was evaluated using classification error
matrix. Potential rice area mask was
generated and overlaid on the soil suitability
map to derive the rice area suitability for
adaptation of SRI method in Andhra
Pradesh.
DEM (Digital Elevation Model)
Shuttle Radar Topography Mission (SRTM)
derived DEM of 90 m resolution was used to
generate the slope map of AP. The data were
taken from http://srtm.usgs.gov/data/
obtaining.html. The study area was clipped,
projected and then imported to the ArcGIS.
Based on the data the slope map was
generated.
Results and Discussion
Generation of thematic database in GIS
The rice growing soils in AP are varying in
properties such as texture, drainage, pH,
water holding capacity and nutritional status,
etc. These soils are in various topographical,
pedological and hydrological conditions in
various land-forms. The most useful
application of GIS in resource data analysis
is to overlay various thematic maps to derive
useful results. The factors which could
influence soil-suitability evaluation for SRI
have been defined and thematic layers on
soil drainage, depth, texture, salinity and
slope were generated. The present study has
utilized the analytical capabilities of GIS in
the evaluation of soil suitability for SRI
method of rice cultivation in Andhra
Pradesh.
Assigning weight and Multi Criteria
Evaluation (MCE)
The purpose of weighting is to express the
importance or preference of each factor
relative to the other factor on SRI method of
rice cultivation. Factors established in this
phase are not unique but they are most
relevant and expert opinion is very
6 Journal of Rice Research 2013, Vol. 6 No. 2
important in this phase. Suitability levels for
each of the above mentioned factors were
defined and ranks were attributed
accordingly. Once the composite layers and
their weights were obtained, the multi
criteria evaluation was carried out in GIS
environment to produce the soil suitability
maps for SRI method of rice cultivation in
Andhra Pradesh.
Soil drainage
The wetting and drying cycles are regarded
as critical to yield performance, with the
intermittent drying promoting root
development in a way that is not possible
under a ‘wet’ regime. Hence, soil drainage is
the most important physical attribute of soil
for SRI method. Soil drainage classes
derived from NBSSLUP soil map of
250,000 scale is shown in Fig. 2. Though
there are five drainage classes altogether, for
this study the soils of AP were categorized
into three drainage classes according to the
suitability for SRI method of rice
cultivation.
Fig. 2: Soil drainage classes in AP
7 Journal of Rice Research 2013, Vol. 6 No. 2
The poorly drained soils are sparsely
distributed particularly in the north eastern
and central part of AP. The well drained
soils are given lowest weight of 1 (most
suitable), the moderately well drained as
well as the imperfectly drained soils are
given a weight of 2 and lastly, poor and
excessive drainage classes are attributed the
highest weight of 3 (least suitable). When
the drainage map is overlaid on the potential
rice map, it was found that approximately
24.24 lakh ha of rice area is well drained and
best suitable for SRI, followed by
moderately well drained class of
approximately 6.82 lakh ha. and
approximately 2.38 lakh ha. of poorly
drained soil.
Soil depth
Soil depth is one of the most important soil
physical parameters for SRI method of rice
cultivation. Soil depth determines roots
growth as well as presence of volume of
water and air in the soil. In shallow soil, the
crops suffer sub optimal conditions in the
limited soil volume, which hinders growth
and yield of the crop. The depth limitations
also vary with the kind of clay mineral
present. According to the soil map of
250,000 scale, the soils of AP are
categorized into four classes as shown in the
Fig. 3. Maximum area of AP is covered by
deep soil. For studying the soil suitability for
SRI method of rice cultivation, the soils of
AP were categorized into two depth classes,
and it is observed that most of the rice area
in AP are deep or moderately deep. The
shallow and very deep soils are sparsely
distributed throughout AP. As intermittent
irrigation is practiced in SRI during
vegetative growth to keep the soil just
saturated or moist enough to avoid drought
stress, the deep/moderately deep soils are
given lowest weight of 1 (more suitable) and
shallow as well as very deep classes are
attributed the weight of 2 (less suitable). It
was observed that most part of potential rice
cropped area of approximately 30.836 lakh
ha. is more suitable to SRI method and
approximately 2.529 lakh ha. is less suitable
when soil depth is considered alone.
8 Journal of Rice Research 2013, Vol. 6 No. 2
Fig. 3: Soil depth classes in AP
Soil texture
Soil texture has a large influence on
irrigation water requirement due to much
higher percolation losses on coarser textured
soils. Hence, soil texture is an important
parameter for rice system. According to the
soil map of 250,000 scale, the soils of AP
are categorized into five textural classes as
shown in the Fig. 4. Clayey soil covers the
maximum area. As physical condition of soil
is very important criteria for SRI and well
drained soil is preferred, the soils of AP
categorized into three texture classes for this
study. It was observed that approximately
7.925 lakh ha. of rice area is covered with
best suitable soil texture (loamy and clay
skeletal) for SRI and the maximum rice area
of approximately 23.343 lakh ha. is
moderately suitable for SRI as far as soil
texture is concerned. Approximately 2.231
lakh ha. rice area is with poor soil texture
which might cause poor or excessive
drainage.
9 Journal of Rice Research 2013, Vol. 6 No. 2
Fig. 4: Soil texture classes in AP
Loamy and clayey skeletal texture classes
are attributed a weight of 1 as they are well
suited for SRI, clayey texture is given a
weight of 2 which is moderately suitable and
sandy, loamy skeletal texture classes are
attributed a weight of 3 which are least
suitable due to excessive drainage and low
water retention properties.
Soil salinity
As shown in Fig. 5, there are 6 salinity
classes in the NBSSLUP soil map of
250,000 scale and normal soil occupies most
of the area in AP. As high saline soils are
not suitable for SRI system, the soils of AP
categorized into two salinity classes for this
study. It is observed that entire rice area of
10 Journal of Rice Research 2013, Vol. 6 No. 2
approximately 33.091 lakh ha. is non saline
where as 21,487 thousand ha. rice area is
having moderate to strong salinity problem.
Fig. 5: Soil salinity classes in AP
Slope
Slope map was generated from the SRTM
derived DEM of 90m resolution for the state
of AP and presented in Fig. 6. It is observed
that most of the potential rice grown area in
the state is lying on the flat terrain with
slope less than 15 degree. As far as potential
rice grown area of AP and adaptation of SRI
based on soil criteria are concerned, the
slope effect is not significant.
11 Journal of Rice Research 2013, Vol. 6 No. 2
Fig. 6: Slope map of AP
Multi criteria Evaluation for soil
suitability analysis for SRI system
After preparing thematic maps and giving
weightage to the respective soil parameters
according to the soil suitability for SRI
method of rice cultivation, multi-criteria
evaluation was carried out in GIS to arrive at
suitability classes. Four soil criteria along
with their associated categories (3x3x2x2)
are considered resulting in 36 possible
combinations with total weightage ranging
from 4 to 9. As more suitable classes are
attributed lower weightage, the final
weightage of 4-5 are grouped into the highly
suitable class (S1) followed by moderately
suitable class (S2) with weightage 6-7; and
12 Journal of Rice Research 2013, Vol. 6 No. 2
slightly suitable (S3) with weight 8-9 (Table
1). It is to be noted that, as our analysis is
confined to the potential rice grown area in
the state, only the rice area with different
suitability classes for SRI is shown in the
map (Fig.8). The potential rice cropped area
derived from AWiFS images (Fig.7) was
overlaid on the soil suitability map and the
extent of each suitability class was
calculated. It is observed that most of the
rice area is best suitable for SRI followed by
moderately suitable class. A very small
fraction of rice area is found slightly suitable
for SRI method of rice cultivation.
Negligible area was classified as non
suitable class.
Fig. 7: Potential Rice area derived from AWiFS
13 Journal of Rice Research 2013, Vol. 6 No. 2
Fig. 8: Soil suitability classes for SRI in AP
14 Journal of Rice Research 2013, Vol. 6 No. 2
Conclusions
In this study, Remote Sensing (RS) and GIS
techniques were applied to identify suitable
areas for SRI cultivation of rice in Andhra
Pradesh, based on soil criteria. The results
obtained from this study confirm that RS,
GIS and multi-criteria evaluation techniques
proved to be effective tools for soil-site
suitability analysis studies. The study clearly
brought out the spatial distribution of rice
crop derived from remote sensing in
conjunction with evaluation of soil
suitability for SRI method of rice
cultivation. However, further studies are
suggested, for including more number of
soil parameters and other socio-economic
data like irrigation facility etc., that affect
the adaptation of SRI method of rice
cultivation in the state.
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Table 1: Potenital area suitable for SRI based on multi- criteria evaluation
Rank scored in multi-criteria
weight overlay analysis
Suitability for SRI system
Potential Rice Area of AP
4-5
S1;Highly Suitable
21.675 lakh ha.
6-7
S2; Moderately Suitable
11.410 lakh ha.
8-9
S3; Slightly Suitable
37,102.96 thousand ha.
16 Journal of Rice Research 2013, Vol. 6 No. 2
Variability and Association Studies for Yield Components and Quality
Parameters in Rice Genotypes
B. Krishna Veni*, B. Vijaya Lakshmi and J.V. Ramana
Rice Research Unit, ANGRAU, Bapatla, Guntur, Andhra Pradesh
Abstract
Direct selection based on crop yields is
often a paradox in breeding programmes
because yield is a complex polygenically
inherited character, influenced by its
component traits. Breeding programmes
should, therefore, take into consideration
character association of various
component traits with yield and among
themselves. In this study, seventy rice
(Oryza sativa L.) genotypes were assessed
for genetic variability and correlations
between yield and yield components and
quality parameters. A wider genetic
variability was observed among the
genotypes for most of the characters
studied. Days to 50 per cent flowering,
productive tillers per plant, panicle
length, Head Rice Recovery (HRR) and
volume expansion ratio manifested
significant positive association with grain
yield indicating that simultaneous
improvement of all the characters is
possible. Productive tillers, panicle length,
*Corresponding author: bkv_lam@yahoo.co.in
kernel breadth and L/B ratio manifested
positive direct effect on grain yield per
plant. The relative contribution of
characters towards variability and results
of correlation and path coefficient
indicated the importance of days to 50per
cent flowering, ear bearing tillers and
panicle length.
Key words: Rice, correlation, path analysis,
grain yield, quality parameters.
Rice (Oryza sativa L.) is the staple food for
about 3.0 billion world’s population which
may escalate to 4.6 billion by 2050. Rice
fulfills the nutritional requirements of half of
the world’s population. In India, rice is a
major food crop supplying 30% of the
calorie requirement to the Indian population
(Maclean, 2002). The estimation of
character association could identify the
relative importance of independent character
(s) that may be useful as indicator(s) for one
or more characters. Similarly, path
coefficient analysis partitions the genetic
17 Journal of Rice Research 2013, Vol. 6 No. 2
correlation between yield and its
components into direct and indirect effects.
The present study is an attempt for assessing
rice genetic variability, and association of
various physico-chemical quality characters
with yield components and grain yield to
provide basis for selection and yield
improvement.
Materials and Methods
Seventy genotypes collected from various
research stations were evaluated in a
randomized block design with two
replications during kharif 2010 at Rice
Research Unit, Bapatla. Each genotype was
raised in two rows of five meter length with
a spacing of 20x15cm between and within
the rows respectively. Observations were
recorded on five randomly selected plants
from each replication for six yield
components viz., days to 50 per cent
flowering, plant height, productive tillers,
panicle length, test weight and grain yield
per plant. The quality parameters viz., head
rice recovery, kernel length, kernel breadth,
L/B ratio, kernel length after cooking,
elongation ratio, water uptake, volume
expansion ratio and amylose content were
estimated replication-wise on plot basis as
per the standard procedures delineated by
Murthy and Govinda Swamy (1967), Juliano
(1971) and Little et al., (1958). The mean
values were utilized for the estimation of
genetic parameters and genotypic
correlations as per the standard statistical
procedures. The correlations were
partitioned into direct and indirect effects by
path coefficient analysis using the technique
outlined by Dewey and Lu (1959).
Results and Discussion
The analysis of variance revealed significant
difference among the genotypes for all the
characters studied indicating the existence of
variation among genotypes for traits under
study. Coefficient of variation truly provides
a relative measure of variance among the
different traits. GCV (Table 1) was found to
be highest for water uptake (26.28) followed
by grain yield per plant (26.18) and test
weight (20.35). As suggested by
Subramanian and Menon (1973) the
remaining characters were categorized into
low and moderate groups with a range of
3.42 (panicle length) to 16.96 (productive
tillers/plant). Similar trend was observed for
PCV also. Close relationship between GCV
and PCV was found in all the characters and
PCV values were slightly greater than GCV,
revealing very little influence of
environment for their expression. Similar
results were obtained by Sharma and
18 Journal of Rice Research 2013, Vol. 6 No. 2
Sharma (2007) and Binse et al. (2006).
Except water uptake, all the quality traits
recorded low to moderate variability
estimates which corroborate with the results
of Kumar et al. (2006) and Prasad et al.
(2009).
Heritability and genetic advance
Heritability plays a vital role in deciding the
suitability and adopting breeding strategy
for improvement of a particular character.
As per Johnson et al. (1955) classification,
all the fifteen characters under study
exhibited high values for broad sense
heritability ranging from 97.8% (days to
50% flowering) to 62.8% (volume
expansion ratio) except panicle length
(34.3%) and amylose content (56.1%) which
recorded low values. Although, the presence
of high heritability values indicates the
effectiveness of selection on the basis of
phenotypic performance, it does not show
any indication to the amount of genetic
progress for selecting the best individuals
which is possible by using the estimates of
genetic advance. The estimates of genetic
advance as per cent of mean was high for
grain yield (52.23) followed by water uptake
(49.12) and test weight (41.14) while the
remaining characters manifested low to
moderate values. Similar results were
earlier reported by Sharma and Sharma
(2007), Bhavana (2003) and Veni et al.
(2006). High heritability coupled with high
genetic advance and high GCV were
observed for grain yield per plant, water
uptake followed by test weight and
productive tillers per plant indicating the
preponderance of additive gene action and
such characters could be improved through
selection. The characters, panicle length and
amylose content recorded low estimates for
all variability parameters studied suggesting
the role of non-additive gene action.
Association analysis
Complete knowledge on interrelationship of
plant character like grain yield with other
characters is of paramount importance to the
breeder for making improvement in complex
quantitative character like grain yield for
which direct selection is not much effective.
Hence, association analysis was undertaken
to determine the direction of selection and
number of characters to be considered in
improving grain yield. Days to 50 per cent
flowering, productive tillers per plant,
panicle length, head rice recovery and
volume expansion ratio manifested
significant positive association with grain
yield (Table 2) indicating that simultaneous
improvement of all the characters is
19 Journal of Rice Research 2013, Vol. 6 No. 2
possible. Sharma and Sharma (2007),
Krishna et al. (2008) also reported similar
findings. Days to 50 per cent flowering also
exhibited a significant positive correlation
with plant height (0.2709) and ear bearing
tillers per plant (0.4728) while its
association with L/B ratio is significantly
negative. Plant height and productive tillers
manifested positive and significant
correlation with panicle length. The results
are in corroboration with the findings of
Kumar and Kannan Bapu (2005) and
Krishna et al. (2009). Ear bearing tillers and
panicle length exhibited significant positive
association with head rice recovery. Kernel
length (-0.2944), kernel breadth (-0.3755)
and elongation ratio (0.3026) manifested
significant negative association with grain
yield/plant. Among quality traits, kernel
length manifested significant positive
association with L/B ratio (0.6244) and
kernel length after cooking (0.6514) while
kernel breadth exhibited significant negative
correlation with L/B ratio. Significant
positive correlation was observed between
L/B ratio and kernel length after cooking
and between kernel length after cooking and
elongation ratio. Similar results were
previously reported by Veni et al. (2006).
Significant positive correlation was
observed between elongation ratio and
volume expansion ratio while significant
negative relationship was manifested
between volume expansion ratio and
amylose content.
Path-coefficient analysis using
grain yield as dependent variable and other
characters as independent variables is
presented in Table 3. Productive tillers
(0.5687) manifested the maximum direct
effect (0.5687) on grain yield /plant
followed by kernel breadth (0.2809), L/B
ratio (0.2689), KLAC (0.2286) and panicle
length (0.1428). Test weight (-0.3035) and
kernel length (-0.3285) exhibited negative
direct effect on grain yield per plant. The
results were in agreement with the previous
findings of Krishna et al. (2008), Veni et al.
(2003).Productive tillers manifested positive
indirect effect on grain yield/plant through
days to 50 per cent flowering (0.2689),
panicle length (0.3147), head rice recovery
(0.2353) and volume expansion ratio
(0.2635). Panicle length and test weight
expressed positive indirect effects through
days to 50 per cent flowering, plant height
and Productive tillers. Among quality traits,
kernel length exhibited negative indirect
effects through test weight, L/B ratio and
kernel length after cooking and its
correlation with grain yield/plant is also
negative. The association of kernel breadth
20 Journal of Rice Research 2013, Vol. 6 No. 2
with grain yield is significantly negative but
its direct effect is positive, under such
conditions restricted simultaneous selection
is advocated for utilization of their positive
indirect effects.
The genetic architecture of grain
yield is based on the balance or overall net
effect produced by various yield
components interacting with one another.
Based on the studies on genetic variability
and correlation analysis, it may be
concluded that productive tillers, panicle
length and days to 50 per cent flowering
exhibited positive direct effect on grain yield
per plant coupled with significant positive
association with grain yield per plant.
Hence, utmost importance should be given
to these characters during selection for
single plant yield improvement. Selection of
plants on the basis of these traits would
certainly lead to improvement in grain yield.
References
Bhavana, P. 2003. Genetic divergence of rice
genotypes with regard to seed, growth and yield
characters, MSc.(Ag) Thesis. Acharya N.G.
RangaAgril. University, Hyderabad.
Binse, R, Motiramani, N.K. and Sarawgi. 2006.
Association analysis and variability analysis in
rice. Mysore Journal of Agricultural Sciences
40(3):375-380.
Dewey, D.R. and Lu, K.H. 1959. A correlation and
path coefficient analysis of components of
crested wheat grass seed production. Agronomy
journal 51 (9):515-518.
Johnson, H.W, Robinson, H.F. and Comstock, R.E.
1955. Estimates of genetic and environmental
variability in soybean. Agronomy Journal 47 (7):
314-318.
Juliano, B.O. 1971. A simplified assay for milled rice
amylose. Cereal Science Today.16:334- 339.
Krishna, D.M., Reddy, D.M, Reddy, K.H.P. and
Sudhakar, P. 2009. Character association and
interrelationship of yield and quality attributes in
rice (Oryza sativa L.). The Andhra Agricultural
Journal 56 (3): 298-301.
Krishna, L, Raju, Ch.D. and Raju, Ch.S. 2008.
Genetic variability and correlation in yield and
grain quality characters of rice germplasm. The
Andhra Agril. Journal 55 (30): 276-279.
Kumar, S, Gautam, A.S. and Chandel, S. 2006.
Estimates of genetic parameters for quality traits
in rice (Oryza sativa L.) in mid hills of Himachal
Pradesh. Crop Research 32(2):206-208.
Kumar, S.P. and Kannan Bapu, J.R. 2005. Character
association in inter sub-specific rice hybrids
involving wide compatible gene. Crop Research
30(2): 208-210.
Little, R.R, Hilder, G.B. and Dawson, E.H. 1958.
Differential effect of dilute alkali on 25 varieties
of milled rice. Cereal Chemistry 35:111-126.
Maclean, J.L. 2002. Rice Almanac. Los Banos:
International Rice Research Institute, Bouake;
Ivory Coast: West Africa Rice Development
Association; Cali: International Center for
Tropical Agriculture; Rome: Food and
Agriculture Organization.
Murthy, P.S.N. and Govindaswamy. 1967.
Inheritance of grain size and it’s correlation with
the hulling and cooking qualities. Oryza 4(1):
12-21.
Prasad, R., Prasad, L.C. and Agarwal, R.K. 2009.
Genetic diversity in Indian germplasm of
aromatic rice Oryza. 46(3): 197-201.
Sharma, A.K. and Sharma, R.N. 2007. Genetic
variability and character association in early
maturing rice. Oryza 44(4):300-303.
Subramanian, P.S. and Menon, P.M. 1973. Genotypic
and phenotypic variability in rice. Madras
Agricultural Journal 60: 103-109.
Veni, K.B, Rani, N.S, Prasad, A.S.R. and Prasad,
G.S.V. 2003. Character association and path
analysis studies for quality traits in aromatic rice.
The Andhra Agric. Journal 50 (1& 2): 20-23.
Veni, K.B, Rani, N.S. and Prasad, A.S.R. 2006.
Genetic parameters for quality characteristics in
aromatic rice Oryza 43(3):234-237.
21 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1: Mean, range and variability parameters for 15 yield components and
quality parameters in 70 genotypes of rice
Significant at 5% level Significant at 1% level
DFF: Days to 50% Flowering; PH: Plant Height; EBT: Ear Bearing Tillers; PL: Panicle Length;TW: Test Weight; HRR:Head Rice Recovery; KL: Kernel
Length; KB: Kernel Breadth;L/B: Length/Breadth Ratio; KLAC: Kernel Length after Cooking; ER: Elongation Ratio; WU: Water Uptake; VER: Volume
Expansion Ratio; AC: Amylose Content
Character
Mean
Range
PCV
GCV
Heritability
Genetic
advance as %
of mean
DFF (days)
106.95
89-133
11.98
11.84
97.8
24.12
PH (cm)
96.88
74.5-148.0
11.33
11.12
96.3
22.48
EBT
10.42
6.75-15.52
20.02
16.96
71.7
29.59
PL (cm)
22.82
19.2-24.5
5.85
3.42
34.3
4.13
TW (g)
19.71
13.41-32.29
20.73
20.35
96.3
41.14
HRR (%)
59.72
50.3-67.1
7.11
6.31
78.7
11.52
KL (mm)
5.62
3.72-6.97
11.80
11.21
90.3
21.96
KB (mm)
1.99
1.57-2.66
12.59
11.03
76.8
19.91
L/B
2.83
1.99-3.64
13.02
11.41
76.8
20.59
KLAC (mm)
8.88
5.65-12.18
15.54
13.99
81.1
25.95
ER
1.62
1.21-2.06
12.39
10.32
69.4
17.70
WU (ml)
199.26
90.0-347.5
28.97
26.28
82.3
49.12
VER
4.19
2.90-4.80
15.92
12.62
62.8
20.61
AC (%)
24.19
19.36-26.65
7.53
5.64
56.1
8.69
Grain yield/plant (g)
17.85
8.96-28.27
27.04
26.18
93.8
52.23
22 Journal of Rice Research 2013, Vol. 6 No. 2
Table 2: Genotypic correlation coefficients of grain yield with yield components and quality parameters in rice
Character
DFF
PH
EBT
PL
TW
HRR
KL
KB
L/B
KLAC
ER
WU
VER
AC
GY
DFF
1.000
0.2709*
0.473*
*
0.132
-
0.0530
0.1361
-
0.4191*
*
-0.0008
-
0.4086*
*
-0.2110
0.1704
0.1970
0.0055
0.2273
0.3254*
PH
1.000
-0.118
0.299*
-
0.0569
-
0.3114*
-0.2144
0.0558*
*
-0.2396
-
0.2495*
-0.1243
0.0918
0.0552
-0.0518
-0.0953
EBT
1.000
0.553*
*
-
0.2926
*
0.4137*
*
-
0.3185*
-
0.4009*
*
-0.0101
-0.2036
0.1566
0.0481
0.4633*
*
-0.0823
0.7970*
*
PL
1.000
-
0.1369
0.5146*
*
-
0.3886*
*
-0.1113
-
0.3012*
-0.2106
0.0242
0.2662
*
0.0777
-
0.5109*
*
0.4679*
*
TW
1.000
-0.1687
0.5181*
*
0.6785*
*
-0.0599
0.4634*
*
-0.0097
0.1216
-0.1729
0.4305*
*
-
0.3540*
HRR
1.000
-
0.2601*
-0.2338
-0.1020
0.1522
0.4933*
*
0.1333
0.3340*
*
-0.1090
0.5195*
*
KL
1.000
-
0.4090*
*
0.6224*
*
0.6514*
*
-0.1765
0.1025
-0.1331
0.0862
-
0.2944*
KB
1.000
-
0.4582*
*
0.3297*
*
-0.0380
0.1824
-
0.3805*
*
0.3854*
*
-
0.3755*
*
L/B
1.000
0.3319*
*
0.1648
-
0.0313
0.1666
-
0.2619*
-0.0093
KLAC
1.000
0.5117*
*
0.1484
0.2273
0.0035
-0.0272
ER
1.000
0.0264
*
0.5217*
*
-0.0697
0.3026*
WU
1.000
0.0082
0.2246
0.2253
VER
1.000
-
0.4775*
*
0.4991*
*
AC
1.000
-0.1852
* Significant at 5% level ** Significant at 1% level
DFF: Days to 50% Flowering; PH: Plant Height; EBT: Ear Bearing Tillers; PL: Panicle Length; TW: Test Weight; HRR:Head Rice Recovery; KL: Kernel
Length; KB: Kernel Breadth; L/B: Length/Breadth ratio; KLAC: Kernel Length After Cooking; ER: Elongation Ratio; WU: Water Uptake; VER: Volume
Expansion Ratio; AC: Amylose Content
23 Journal of Rice Research 2013, Vol. 6 No. 2
Table 3: Path coefficient analysis of grain yield with yield components and quality parameters in rice genotypes
Character
DFF
PH
EBT
PL
TW
HRR
KL
KB
L/B
KLAC
ER
WU
VER
AC
DFF
0.0023
0.0006
0.0011
0.0003
-0.0001
0.0003
0.0010
0.000
-0.0010
-0.0005
-0.0004
0.0005
0.0000
0.0005
PH
-0.0144
-0.0533
0.0063
-0.0159
0.0030
0.0166
0.0114
-0.0030
0.0128
0.0133
0.0066
-0.0049
-0.0029
0.0028
EBT
0.2689
-0.0669
0.5687
0.3147
-0.1664
0.2353
-0.1811
-0.2280
-0.0057
-0.1158
0.0891
0.0274
0.2635
-0.0468
PL
0.0188
0.0426
0.0790
0.1428
-0.0195
0.0735
-0.0555
-0.0159
-0.0430
-0.0301
0.0035
0.0380
0.0111
-0.0729
TW
0.0161
0.0173
0.0888
0.0416
-0.3035
0.0512
-0.1573
-0.2060
0.0182
-0.1407
0.0029
-0.0369
0.0525
-0.1307
HRR
0.0095
-0.0216
0.0288
0.0358
-0.0117
0.0695
-0.0181
-0.0163
-0.0071
0.0106
0.0343
0.0093
0.0232
-0.0076
KL
0.1377
0.0704
0.1046
0.1277
-0.1702
0.0854
-0.3285
-0.1343
-0.2044
-0.2140
0.0580
-0.0337
0.0437
-0.0283
KB
-0.0002
0.0157
-0.1126
-0.0313
0.1906
-0.0657
0.1149
0.2809
-0.1287
0.0926
-0.0107
0.0512
-0.1069
0.1083
L/B
-0.1099
-0.0644
-0.0027
-0.0810
-0.0161
-0.0274
0.1674
-0.1232
0.2689
0.0893
-0.0443
-0.0084
0.0448
-0.0704
KLAC
-0.0482
-0.0570
-0.0465
-0.0481
0.1059
0.0348
0.1489
0.0754
0.0759
0.2286
0.1170
0.0339
0.0519
0.0008
ER
-0.0081
0.0059
-0.0075
-0.0012
0.0005
-0.0236
0.0084
0.0018
0.0079
-0.0244
-0.0477
0.0013
-0.0249
0.0033
WU
0.0232
0.0108
0.0057
0.0313
0.0143
0.0157
0.0121
0.0215
-0.0037
0.0175
-0.0031
0.1177
0.0010
0.0264
VER
0.0011
0.0112
0.0937
0.0157
-0.0350
0.0676
-0.0269
-0.0770
0.0337
0.0460
0.1055
0.0017
0.2023
-0.0966
AC
0.0287
-0.0065
-0.0101
-0.0644
0.0543
-0.0137
0.0109
0.0486
-0.0330
0.0004
-0.0088
0.0283
-0.0602
0.1260
DFF: Days to 50% Flowering; PH: Plant Height; EBT: Ear Bearing Tillers; PL: Panicle Length;TW: Test Weight; HRR:Head Rice Recovery; KL: Kernel
Length; KB: Kernel Breadth;L/B: Length/Breadth Ratio;KLAC: Kernel Length After Cooking; ER: Elongation Ratio; WU: Water Uptake; VER: Volume
Expansion Ratio; AC: Amylose Content.
The values in bold and diagnolly represented are direct effects and all others are indirect effects.
24 Journal of Rice Research 2013, Vol. 6 No. 2
Genetic variability, Correlation and Path Analysis for Quantitative
Characters in Rainfed Upland Rice of Uttarakhand Hills
J. P. Aditya* and Anuradha Bhartiya
Crop Improvement Division, Vivekananda Parvatiya Krishi Anusandhan Sansthan (ICAR),
Almora 263 601 Uttarakhand.
Abstract
Genetic parameter, correlation
coefficients among yield and yield
components, direct and indirect effect of
yield components on yield were studied in
eighteen rice genotypes under rainfed
ecosystem for fifteen quantitative traits.
The analysis of variance revealed that
there were highly significant differences
for all the characters among the
genotypes. The estimate of GCV and PCV
was found to be highest for grain yield
per plot followed by fertile grains per
panicle and grains per panicle. The broad
sense heritability was highest for plant
height and fertile grains per panicle
(98.14%) followed by grains per panicle
(97.74%), days to 50 per cent flowering
(95.18) and days to maturity (94.71). The
estimate of genetic advance was found to
be highest for grains per panicle and
fertile grains per panicle. The number of
grains per panicle and fertile grains per
*Corresponding author : jayprakashaditya@gmail.com
panicle had high heritability as well as
high genetic advance. The phenotypic
correlation coefficient among fifteen traits
showed that grain yield was significantly
and positively correlated with plant
height, days to 50 per cent flowering, days
to maturity, flag leaf length, flag leaf
width, panicle length, grains per panicle,
fertile grains per panicle, kernel length
and L/B ratio. The estimates of direct and
indirect effect revealed that L/B ratio had
the highest positive direct effect on grain
yield followed by kernel width, grains per
panicle, and tillers per plant.
Key Words: Rainfed upland rice, genetic
parameters, correlation, path analysis, yield
components
Rice (Oryza sativa L.) is the staple food of
more than three billion people in the world.
Nearly, hundred million people depend on
the upland rice as their daily staple food.
Almost two third of the upland rice area is in
Asia. In India, the total area under upland
25 Journal of Rice Research 2013, Vol. 6 No. 2
rice is 6 m. ha. which accounts 13 per cent
of the total area under rice crop in the
country. Upland rice is generally grown
under rainfed conditions and crop growth is
entirely depends on the monsoon. Upland
rice ecology is much harsh environment for
rice production in which intermittent
drought is the major constraint (Hanamaratti
et al., 2005) and cause a yield penalty from
12 to 46 per cent (Oak et al., 2006). Rainfed
upland rice is an important component of
cropping system in Uttarakhand hills.
Rainfed upland rice cultivation in hills is
suffering from the problem of poor
productivity mainly due to erratic rainfall,
poor soil fertility as well as lack of improved
varieties. Poor yield potential of traditional
rice cultivars necessitates the development
of the high yielding cultivars for rainfed
upland condition of hills. Development of
high yielding varieties requires a thorough
understanding of existing genetic variability
as well as magnitude and direction of
genetic association among the yield
contributing characters. Knowledge of
association direct and indirect effect
between grain yield and other characters can
be helpful in efficient selection of suitable
cultivars of rice for rainfed upland
condition. Therefore, the present study
aimed to determine the extent of genetic
variability,genetic parameters with
correlation and path coefficient to select
superior rice genotypes adapted to rainfed
upland ecosystem of Uttarakhand hills.
Materials and Methods
The experimental material consisted of
eighteen rainfed upland rice genotypes
(Table 1). These genotypes were evaluated
in a completely randomized block design
with three replications during kharif season
at experimental farm of Vivekananda
Parvatiya Krishi Anusandhan Sansthan
(ICAR), Almora. The crop was direct seeded
under the rainfed condition. Each plot
consisted of five rows plot of 3.5m length
with spacing of 20cm between rows. Ten
plants from middle row of each entry in each
replication were randomly selected for
recording observations on quantitative traits
viz., plant height, tillers per plant, flag leaf
length, flag leaf width, panicles per plant,
panicle length, grains per panicle, fertile
grain per panicle, thousand grain weight,
kernel length, kernel width and L/B ratio.
Whereas, days to 50 per cent flowering,
days to maturity and grain yield were
recorded on whole plot basis. The mean
value was used as the replicated data and
was subjected to statistical analysis using
INDOSTAT software package. Analysis of
26 Journal of Rice Research 2013, Vol. 6 No. 2
variance was estimated following Panse and
Sukhatme (1985). The phenotypic and
genotypic coefficient of variability,
heritability in broad sense, genetic advance
at 5 per cent selection intensity were
computed as suggested by Johnson et al.
(1955). The phenotypic correlation
coefficients among all the traits under study
were calculated following Al-Jobouri et al.
(1958) and the path analysis was carried out
as per method of Dewey and Lu (1959).
Results and Discussion
Analysis of variance indicated the existence
of highly significant differences among the
genotypes for all the characters studied
except tillers per plant. This suggested that
there is an inherent genetic difference
among the genotypes (Table 2). The range,
mean, standard error of mean, genotypic
coefficient of variation, phenotypic
coefficient of variation, heritability, genetic
advance at 5 per cent selection intensity for
different characters are given in Table-3.
Among rainfed upland rice genotypes, the
average grain yield per plot ranged from
0.23 kg to 0.95 kg and crop duration varied
from 114 to 131 days. Five genotypes viz.,
VL 8204 (0.95 kg/plot), VL 8302 (0.82
kg/plot), VL 8185 (0.80 kg/plot), VL 31402
(0.75 kg/plot) and VL 8292 (0.70 kg/plot)
were found significantly superior for grain
yield. A wide range of variability was
observed for grains per panicle (76-150)
followed by fertile grain per panicle (65-
137). The range of variation obtained for
kernel width (2.22-2.63) and flag leaf width
(1.39-1.95) was least when compared to all
other characters. The estimate of GCV and
PCV was found to be highest for yield per
plot followed by fertile grains per panicle
and grains per panicle. Padmaja et al. (2008)
also recorded similar observation for grains
per panicle and single plant yield. Low GCV
and PCV estimates were noticed for plant
height, days to 50 per cent flowering, days
to maturity, tillers per plant, panicle length,
thousand grain weight, kernel length, kernel
width and LB ratio. These results are in
conformity with Padmaja et al. (2008) for
days to 50 per cent flowering and panicle
length. The estimates of PCV were slightly
higher than the corresponding GCV
estimates for plant height, days to 50 per
cent flowering, days to maturity, grains per
panicle and fertile grains per panicle
indicating that the characters were less
influenced by the environment. Therefore,
selection on the basis of phenotype alone
can be effective for the improvement of
these traits. In general, the magnitude of
PCV was found to be higher than the
27 Journal of Rice Research 2013, Vol. 6 No. 2
corresponding GCV for all the characters
suggesting the influence of environment on
the expression of the traits. However, the
differences between PCV and GCV were
very small for most of the characters
indicating the lesser contribution of
environmental variation towards the
expression of these traits. Similar
observations were also recorded by (Karad
and Pol 2008; Ubarhande et al., 2009) in
rice genotypes.
The broad sense heritability was
highest for plant height and fertile grains per
panicle (98.14%) followed by grains per
panicle (97.74%), days to 50 per cent
flowering (95.18) and days to maturity
(94.71). Sharma and Sharma (2007) also
reported similar finding for these traits. The
estimate of heritability alone is not very
much useful because it includes the effect of
both additive and non additive gene. The
genetic advance is a useful indicator of the
progress that can be expected as a result of
exercising selection on the pertinent
population. The estimate of genetic advance
was found to be highest for grains per
panicle and fertile grains per panicle
(Sharma and Sharma, 2007). The number of
grains per panicle and fertile grains per
panicle had high heritability as well as high
genetic advance. It is suggested that these
characters were predominantly controlled by
additive gene action. Hence genetic
improvement through selection for these
traits may be effective. Heritability estimates
along with genetic advance are more helpful
in predicting gain under selection than
heritability estimate alone (Sinha et al.,
2004; Johnson et al., 1955).
The phenotypic correlation coefficient
among 15 traits including grain yield in the
present investigation is presented in Table-4.
Grain yield was observed to be positively
and significantly correlated with plant
height, days to 50 per cent flowering, days
to maturity, flag leaf length, flag leaf width,
panicle length, grains per panicle, fertile
grains per panicle, kernel length and L/B
ratio. Among the component traits plant
height was significantly positively
correlation with days to 50 per cent
flowering, days to maturity, flag leaf length,
flag leaf width, panicle length, grains per
panicle and fertile grains per panicle.
Sharma and Sharma (2009); Subudhi and
Dikshit (2009) reported significant positive
correlation between plant height and grains
per panicle and panicle length. Days to 50
per cent flowering showed significant
positive correlation with days to maturity,
flag leaf length, flag leaf width, panicle
length, grains per panicle and fertile grains
28 Journal of Rice Research 2013, Vol. 6 No. 2
per panicle. Chandra et al. (2006) reported
significant positive correlation of days to 50
per cent flowering with panicle length. Days
to maturity was found to be significantly
positively correlated with flag leaf length,
flag leaf width, panicle length, grains per
panicle and fertile grains per panicle. Tillers
per plant exhibited significant positive
correlation with panicles per plant while it
was negatively correlated with panicle
length. Flag leaf length, flag leaf width,
panicle length, grains per panicle and fertile
grains per panicle were mutually correlated
with each other. L/B ratio showed
significant positive correlation with grains
per panicle, thousand grain weight, kernel
length and kernel width.
The above inter se association
amongst the traits indicated that although
tillers per plant, panicles per plant, thousand
grain weight, and kernel width did not
exhibit positive significant association with
grain yield, their role in contributing
towards grain yield could not be overlooked
as these component traits exhibited
positively significant association with
important yield attributes. Thus, these traits
may be assumed to indirectly contribute via
other traits in governing grain yield. In this
regard it is important to partition out the
observed phenotypic association into direct
and indirect effects of the component traits
towards grain yield.
A character contributing to grain
yield may contribute directly or indirectly. It
is essential to conduct the path analysis. The
estimates of direct and indirect effect are
presented in Table-5. In the present
investigation, L/B ratio had the highest
positive direct effect on grain yield followed
by kernel width, grains per panicle, and
tillers per plant. Highest positive but indirect
effect was observed for kernel length via
L/B ratio followed by thousand grain weight
via L/B ratio. Plant height, days to 50 per
cent flowering, days to maturity, tillers per
plant, flag leaf length, panicles per plant,
thousand grains weigh and kernel length
grains per panicle were observed to
contribute positively to an appreciable
extent via L/B ratio.Direct and indirect
effect of yield component traits on grain
yield have also been reported earlier
(Shivani and Reddy, 2000; Kavitha and
Reddi, 2001; Biao et. al., 2002; Shanthala et
al., 2004 and Shashidhar et al., 2005).
References
Al Jibouri, H.A., Miller, R.A. and Robinson, H.F.
1958. Genetic environmental variances and
covariances in an upland cotton cross
interspecific origin. Agronomy Journal 50: 633-
636.
Biao, G.L., Lijun, L., Zhong, X.Y., Yipin, W., Wei,
M.H., Qian, Q. and Cunshan, Y. 2002. Path
analysis for yield and its component characters in
rice. Chinese Rice Research Newsletter 10: 5-6.
29 Journal of Rice Research 2013, Vol. 6 No. 2
Chandra, R., Pradhan. S.K., Singh, S., Bose, L.K. and
Singh, O.N. 2006. Agro-morphological traits as
selection parameters for improvement of upland
rice. Indian Journal of Plant Genetic Resources
19 (2): 184-187.
Dewey, D.R. and Lu, K.H. 1959. A correlation and
path coefficient analysis of components of
crested wheat grass seed populations. Agronomy
Journal 51:515-518.
Hanamaratti, N.G., Prashanthi, S.K., Angadi, V.V.
and Salimath, P.M. 2005. Rice research in rain-
fed drill sown rice in Karnataka. In : Five
Decades of Rice Research in Karnataka,
Directorate of Research, University of
Agricultural Sciences, GKVK, Bengaluru, pp.
55-68.
Johnson, H.N., Robinson, H.F. and Comstock, R.E.
1955. Estimate of genetic and environmental
variability in soybean. Agronomy Journal 27:
314-318.
Karad, S.R. and Pol, K.M. 2008. Character
association, genetic variability and path
coefficient analysis in rice (Oryza sativa L.).
International Journal of Agricultural Sciences 4
(2): 663-666.
Kavitha, S. and Reddi, N.S.R. 2001. Correlation and
path coefficient analysis of yield component in
rice (Oryza sativa L.) The Andra Agricultural
Journal 48:311-314.
Oak, M.B., Tsubo, J., Fukai, M., Fisher, S., Cooper,
K.S. and Nesbitt, M. 2006. Use of drought
response index for identification of drought
tolerant genotypes in rainfed lowland rice. Crop
Science Research 99(1):48-58.
Padmaja, D., Radhika, K., Subba Rao, L.V. and
Padma, V. 2008. Studies on variability,
heritability and genetic advance for quantitative
characters in rice (Oryza sativa L.) Indian
Journal of Plant Genetic Resources 21(3): 196-
198.
Panse, V.G. and Sukhatme, P.V. 1985. Statistical
methods for agricultural workers. Indian Council
of Agricultural research, New Delhi.
Shanthala, J., Latha, J. and Hittalmani. 2004. Path
coefficient analysis for grain yields and in
component characters in hybrid rice.
Environment and Ecology 22: 734-736.
Sharma, A.K. and Sharma, R.N. 2007. Genetic
variability and character association in early
maturing rice. Oryza 44 (4): 300-303.
Sharma, M.K. and Sharma, A.K. 2009. Character
association and path analysis of yield and its
component in direct seeded upland rice (Oryza
sativa L.). Progressive Agriculture 9 (1): 117-
120.
Shashidhar, H.E., Pasha, F., Janamatti, M., Vinod,
M.S., and Kanbar, A. 2005. Correlation and path
coefficient analysis in traditional cultivars and
double haploid lines of rainfed low land rice.
Oryza 42: 156-159.
Shivani, D. and Reddy, N.S.R. 2000. Correlation and
path analysis in rice (Oryza sativa L.) hybrids.
Oryza 37: 183-186.
Sinha, S.K., Tripathi, A.K. and Bisen, U.K. 2004.
Study of genetic variability and correlation
coefficient analysis in midland land races of rice.
Annals of Agricultural Research 25 (1):1-3.
Subudhi, H.N. and Dikshit, N. 2009. Variability and
character association of yield components in
rainfed lowland rice. Indian Journal of Plant
Genetic Resources 22 (1): 31-35.
Ubarhande, V.A., Prasad, R., Singh, R.P., Singh, S.P.
and Agrawal, R.K. 2009. Variability and
diversity studies in rainfed rice (Oryza sativa L.)
Indian Journal of Plant Genetic Resources 22
(2): 134-137.
30 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1. List of rainfed upland rice genotypes under study and their pedigree
Genotypes
Pedigree
VL 8257
Pant Dhan 6 x Barakat
VL 8201
VR 539-2 x VLD 81
VL 8204
VR 539-2 x VLD 81
VL 8302
VL 9588 x A-57
VL 8292
VL 9588 x A-57
VL 8214
VLD 81 x VR 539-2
VL 8188
VR 539-2 x IR 63872-93-2-37
VL 8185
VR 539-2 x IR 63872-93-2-37
VL 8369
VL 9588 x VR 539-2
VL 31384
China 4 x BG 367-4
VL 31402
SRSN 38 x VL 6394
VL 31430
Pant Dhan 6 x VL 3288
VL 31590
VL 3861 x IR 59656-5- K-1
VL 31567
Vivek Dhan 82 x WAB 337-B-B-13-1-1-3
VL 31440
VHC 1253 x Thapachini
VL 31419
Vivek Dhan 82 x VLD 206
Vivek Dhan 154
VL Dhan 221 x VL- 24
VLD 221
IR 2053-521-1-1-1 x Ch- 1039
31 Journal of Rice Research 2013, Vol. 6 No. 2
Table 2: Analysis of variance for various yield contributing characters
Source of
variance
d.f
Plant
height
Days to
50%
flowering
Days to
maturity
Tillers
per
plant
Flag
leaf
length
Flag
leaf
width
Panicles
per
plant
Panicle
length
Grains per
panicle
Fertile
grains per
panicle
1000grain
weight
Grain
yield
per
plot
Kernel
length
Kernel
width
L/B
ratio
Replication
2
18.91
0.91
4.24
0.91
1.27
0.01
1.46
1.04
16.07
4.46
1.13
0.009
0.07
0.006
0.0004
Treatments
17
281.62**
74.73**
70.01**
0.90
40.50**
0.08**
1.09*
5.39**
1898.27**
1589.33**
17.68**
0.12**
0.47**
0.04**
0.61**
Error
34
1.77
1.24
1.28
0.71
1.91
0.008
0.54
0.60
14.54
9.95
1.32
0.004
0.03
0.004
0.01
*, ** Significant at 5% and 1% level of probability respectively.
32 Journal of Rice Research 2013, Vol. 6 No. 2
Table 3: Range, mean and genetic parameters of 15 yield attributing characters in rainfed upland rice
Characters
Range
GM
CV %
CD at 5%
SEm
GCV
(%)
PCV
(%)
h2
(%)
GA at 5%
GA as %
mean
Plant height
(cm)
104-142
121.52
1.09
2.21
1.08
7.95
8.02
98.14
19.71
16.22
Days to 50%
flowering (days)
82-99
91.74
1.21
1.85
0.91
5.39
5.53
95.18
9.95
10.84
Days to maturity
(days)
114-131
122.81
0.92
1.88
0.92
3.90
4.00
94.71
9.60
7.81
Tillers per plant
(number)
5-8
6.30
13.39
1.40
0.69
3.96
13.96
8.03
0.14
2.31
Flag leaf length
(cm)
21.29-34.31
28.85
4.78
2.29
1.13
12.43
13.32
87.09
6.90
23.90
Flag leaf width
(cm)
1.39-1.95
1.66
5.44
0.15
0.07
9.00
10.51
73.21
0.26
15.86
Panicles per plant
(number)
5-7
5.96
12.34
1.22
0.60
7.20
14.28
25.38
0.45
7.47
Panicle length
(cm)
20.98-26.13
22.98
3.37
1.29
0.63
5.49
6.45
72.61
2.22
9.65
Grains per panicle
(number)
76-150
118.43
3.22
6.33
3.11
21.16
21.40
97.74
51.03
43.09
Fertile grains per
panicle (number)
65-137
103.76
3.04
5.23
2.58
22.10
22.31
98.14
46.80
45.10
1000grain weight
(g)
22.53-31.22
27.64
4.16
1.91
0.94
8.45
9.42
80.52
4.32
15.62
Grain yield per plot
(Kg)
0.23-0.95
0.55
12.07
0.11
0.05
35.72
37.70
89.74
0.38
69.70
Kernel length
(cm)
5.88-7.35
6.68
2.37
0.26
0.13
5.74
6.21
85.48
0.73
10.94
Kernel width
(cm)
2.22-2.63
2.47
2.63
0.11
0.05
4.44
5.16
74.03
0.19
7.86
L/B ratio
2.40-3.24
2.72
3.74
0.17
0.08
9.41
10.13
86.35
0.49
18.01
33 Journal of Rice Research 2013, Vol. 6 No. 2
Table 4: Phenotypic correlation coefficients among grain yield and component traits in rainfed upland rice
Characters
Plant
height
Days to
50%
flowering
Days to
maturity
Tillers
per
plant
Flag leaf
length
Flag leaf
width
Panicles
per plant
Panicle
length
Grains
per
panicle
Fertile
grains
per
panicle
1000grain
weight
Grain
yield
per plot
Kernel
length
Kernel
width
L/B ratio
Plant
height
1.000
0.645**
0.691**
-
0.241
0.708 **
0.418**
-0.126
0.499**
0.308 *
0.335*
0.164
0.471**
0.109
-0.118
0.134
Days to
50%
flowering
1.000
0.980**
-
0.154
0.4453**
0.477**
-0.083
0.408**
0.315 *
0.306*
0.162
0.284*
0.033
-0.139
0.107
Days to
maturity
1.000
-
0.171
0.459**
0.499**
-0.084
0.436**
0.313*
0.303*
0.139
0.307*
0.023
-0.126
0.095
Tillers per
plant
1.00
-0.105
-0.0918
0.849**
-0.317 *
-0.226
-0.240
0.006
0.053
0.147
-0.164
0.181
Flag leaf
length
1.000
0.663**
-0.027
0.4170**
0.583**
0.602**
0.313*
0.602**
0.202
-0.036
0.133
Flag leaf
width
1.000
-0.039
0.369 **
0.535**
0.515**
0.057
0.383**
-0.134
0.157
-0.186
Panicles
per plant
1.000
0.394**
-0.256
0.279*
0.112
-0.042
0.238
-0.206
0.259
Panicle
length
1.000
0.543**
0.545**
-0.057
0.369**
-0.254
0.163
-0.251
Grains per
panicle
1.000
0.982**
0.122
0.485**
-0.156
0.329*
0.289*
Fertile
grains per
panicle
1.000
0.133
0.502**
-0.099
0.294*
-0.236
1000grain
weight
1.000
0.184
0.688**
0.089
0.390 **
Grain yield
per plot
1.000
0.306*
-0.256
0.319 *
Kernel
length
1.000
0.479**
0.884**
Kernel
width
1.000
0.832**
L/B ratio
1.000
34 Journal of Rice Research 2013, Vol. 6 No. 2
Table 5: Phenotypic path coefficient analysis among the quantitative characters in rainfed upland rice
Characters
Plant
height
Days to
50%
flowering
Days to
maturity
Tillers
per
plant
Flag
leaf
length
Flag
leaf
width
Panicles
per
plant
Panicle
length
Grains
per
panicle
Fertile
grains
per
panicle
1000grain
weight
Kernel
length
Kernel
width
L/B
ratio
Grain
yield
per
plot
Plant height
0.330
0.213
0.228
-0.080
0.234
0.138
-0.042
0.164
0.101
0.110
0.054
0.036
-0.039
0.044
0.471
Days to
50%
flowering
-0.295
-0.457
-0.448
0.071
-0.203
-0.218
0.038
-0.186
-0.144
-0.140
-0.074
-0.015
0.064
-0.049
0.284
Days to
maturity
0.130
0.184
0.188
-0.032
0.086
0.094
-0.016
0.082
0.059
0.057
0.026
0.004
-0.024
0.018
0.307
Tillers per
plant
-0.129
-0.082
-0.091
0.532
-0.056
-0.049
0.452
-0.169
-0.120
-0.128
0.003
0.078
-0.087
0.096
0.053
Flag leaf
length
0.039
0.025
0.026
-0.006
0.056
0.037
-0.002
0.023
0.032
0.033
0.017
0.011
-0.002
0.007
0.602
Flag leaf
width
0.092
0.105
0.110
-0.020
0.146
0.220
-0.009
0.081
0.118
0.113
0.013
-0.029
0.034
-0.041
0.383
Panicles
per plant
0.058
0.038
0.038
-0.389
0.012
0.018
-0.458
0.180
0.117
0.128
-0.051
-0.109
0.094
-0.119
-0.042
Panicle
length
0.041
0.033
0.036
-0.026
0.034
0.030
-0.032
0.082
0.044
0.045
-0.005
-0.021
0.013
-0.021
0.369
Grains per
panicle
0.253
0.258
0.257
-0.185
0.478
0.439
-0.210
0.446
0.821
0.806
0.100
-0.128
0.270
-0.237
0.485
Fertile
grains per
panicle
-0.114
-0.104
-0.103
0.082
-0.205
-0.175
0.095
-0.186
-0.334
-0.341
-0.045
0.034
-0.100
0.080
0.502
1000grain
weight
-0.015
-0.015
-0.013
-0.001
-0.029
-0.005
-0.010
0.005
-0.011
-0.012
-0.093
-0.064
-0.008
-0.036
0.184
Kernel
length
-0.141
-0.043
-0.030
-0.189
-0.261
0.173
-0.306
0.327
0.202
0.128
-0.888
-1.290
0.618
-1.140
0.306
Kernel
width
-0.130
-0.153
-0.139
-0.180
-0.040
0.173
-0.227
0.180
0.362
0.323
0.099
-0.528
1.102
-0.917
-0.256
L/B ratio
0.353
0.283
0.249
0.475
0.350
-0.490
0.684
-0.661
-0.762
-0.620
1.028
2.327
-2.191
2.633
0.319
Residual effect= 0.591
35 Journal of Rice Research 2013, Vol. 6 No. 2
Study on Grain and Water Productivity of Rice-Zero-Till Maize Cropping
System
D. Sreelatha*, M. Srinivasa Raju, M. Devender Reddy, G. Jayasree and
D. Vishnu Vardhan Reddy
Acharya N.G.Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh
Abstract
The effect of two rice crop establishment
methods (transplanted and aerobic), two
irrigation (IW: CPE ratio of 0.8 and 1.0)
and four phosphorus levels (0, 30, 60 and
90 kg P2O5ha-1) on rice-zero-tillage maize
cropping system is studied during 2007-08
and 2008-09 at a field experiment station
at Hyderabad. Transplanted rice on an
average gave 1.02 t ha-1 higher yield than
aerobic rice (4.49 t ha-1). However,
succeeding maize grown as zero-tilled
crop after aerobic rice has 0.34 t ha-1
more yields than that after transplanted
rice (6.34 t ha-1). The higher water
productivity of aerobic rice (0.395 kg m-3)
and succeeding zero-tilled maize (1.17) as
compared to transplanted rice and
succeeding maize (0.37 and 1.095 kg m-3)
together brought higher water
productivity (0.64 kg m-3) in aerobic rice-
maize system in comparison to
transplanted rice-maize (0.54 kg m-3).
With increase in level of irrigation from
0.8 to 1.0 IW: CPE ratio and increase in P
*Corresponding author: lathadogga@gmail.com
dose, the consumptive use of water by
maize increased during both the years of
study.
Key words: Rice, zero-till maize, grain
yield, consumptive use, water productivity
Rice (Oryza sativa L.)-Maize (Zea mays L.)
is one of the pre-dominant cropping system
of both command and non-command areas
of Andhra Pradesh. Shortage of irrigation
water and increased cost of transplanting in
rice made several researchers to study the
possibility of rice cultivation under irrigated
dry conditions (aerobic). The early crop
maturity (7-10 days) and ease of
establishment of succeeding crop after
aerobic rice cultivation are additional
benefits. The concept of zero-tillage is
gaining momentum in traditional areas
under rice-maize sequence.This technique
aids in overcoming planting difficulties in
rice fallow, reduces weeds and improves
fertilizers and water use efficiency and
reduce cost of cultivation (DMR Technical
Bulletin, 2009).
36 Journal of Rice Research 2013, Vol. 6 No. 2
Irrigation as well as nutritional
requirements, particularly, the phosphorus
(P) of zero-till maize is different from
conventionally sown maize because of
alteration of physico-chemical properties of
soil under rice-based situations. Maize uses
water efficiently in terms of total dry matter
production among the cereals. Frequency
and depth of irrigation has pronounced
effect on grain yield of maize. Positive
relationship between irrigation and ‘P’
response in many field crops particularly in
maize have been indicated mainly due to the
fact that ‘P’ availability of both soil and
applied increases due to adequacy of soil
water. Keeping above aspects in view, a
study was under taken to assess zero-tillage
maize performance under different irrigation
and P fertilization following a aerobic and
transplanted crop.
Material and Methods
The field study was conducted during rainy
and winter seasons of 2007-08 and 2008-09
at Water Technology Centre, Agricultural
College Farm, Rajendranagar (78023 E and
1701 N and 524.6 m above MSL),
Hyderabad, Andhra Pradesh. The location
with semi arid tropical climate is
characterized by hot summer and cold
winters. The mean maximum and minimum
temperatures ranges from 31.20C and 15.60C
in 2007-08 and 32.10C and17.00C in 2008-
09 had annual rainfall of 398.5 mm and
1095.6 in 2007-08 and 2008-09 which was
received in 38 and 39 rainy days. The
experimental soil was sandy clay loam with
pH 7.4, low in organic carbon (0.51%) and
available nitrogen (240.6 kg ha-1), medium
in available phosphorus (15.39 kg ha-1) and
high in available potassium (631.6 kg ha-1).
The experiment was conducted in split-plot
design with four replications. During rainy
season, two methods of rice crop
establishment (transplanted and aerobic)
were evaluated whereas in winter season
zero-tilled maize was grown in sequence to
rice while considering the two previous rice
crop establishment methods as main-plot
and combination of two levels of irrigation
(1.0 and 0.8 Irrigation Water (IW):
Cumulative Pan Evaporation (CPE) and four
levels of phosphorus (0, 30, 60 and 90 kg
P2O5ha-1) as sub-plot treatments. During
rainy season semi dwarf rice variety (MTU
1010) was transplanted at a spacing of 20 x
15 cm in a puddled field. Whereas under
aerobic method, direct seeding of dry seed
was done in solid rows at row spacing of 20
cm. Nursery sowing was done for
transplanted rice on the same day as of
Aerobic Rice (AR) sowing. A fertilizer dose
of 120-60-40 kg, N-P2O5- K2O ha-1 in the
37 Journal of Rice Research 2013, Vol. 6 No. 2
form of urea, Single Super Phosphate (SSP)
and Muriate Of Potash (MOP) was applied.
In AR, weeds were controlled by spraying
pendimethalin 35 EC @ 1.0 kg ha-1 in 500 l
of water after 24 hours of seeding followed
by push hoeing at 25 and 45 days after
sowing. In transplanted rice, butachlor 50
EC @1.25 kg ha-1 mixed with sand was
applied at 2 Days After Transplanting
(DAT) maintaining thin film of water
followed by one hand weeding at 30 DAT.
Two sprays of 0.2% ferrous ammonium
sulphate solution were also given at weekly
interval for AR to correct the iron
deficiency.
For transplanted rice, 2 cm standing
water was maintained upto panicle initiation
stage and later 5 cm of level was
maintained. In AR a soaking irrigation was
given initially later on from 7 days onwards
irrigations (5 cm) were given when the soil
moisture reached to 28% corresponding to -
20 Kpa tension that was measured with theta
probe soil moisture sensor ML2. The
amount of water applied was measured
through water meter and was directly
delivered to plot. During winter season,
paraquat 50 EC @ 1.25 kg ha-1 was sprayed
immediately after rice harvest to control the
existing weeds as well as to arrest the re
growth of rice stubbles. Maize hybrid ‘DHM
117’ seeds were dibbled at a spacing of 60 x
20 cm under zero-tillage and a day later
atrazine @1.0 kg ha-1 was sprayed for weed
control. A uniform fertilizer dose of120-40
kg N-K2O ha-1 fertilizers along with P
fertilizer as per the treatment was applied.
The entire P and K was applied as basal in
the form of SSP and MOP and N was
applied in three equal splits (basal, knee
high and tasseling & silking) in the form of
urea. Pests and disease control were adopted
as per the recommendations for the region.
One pre-sowing irrigation followed by one
common irrigation each of 2.5 cm
immediately after sowing of the crop was
given to ensure uniform germination.
Subsequent irrigations were scheduled based
on IW: CPE ratio. In IW: CPE approach, 5
cm depth of irrigation water was applied
uniformly when CPE reached 6.25 and 5.0
cm in order to get a ratio of 0.8 and 1.0. CPE
values were obtained from standard USWB
Class A pan. The soil moisture depletion
method was employed to determine the
Consumptive Use (CU). Consumptive use
was calculated from change in the soil
moisture content in successive samples
Sankara Reddi and Yellamanda Reddy,
1995).
n
U= ∑ (Mxi - Mzi)
38 Journal of Rice Research 2013, Vol. 6 No. 2
i=1 --------------------- x BDi x Di
100
Where, U = Consumptive use or actual
moisture used from the root zone within one
irrigation cycle (mm)
n = Number of soil layers sampled in the root
zone depth D
Mxi = Soil moisture percentage at the time of
first sampling in the ith layer
Mzi = Soil moisture percentage at the time of
second sampling in the ithlayer
BDi =Bulk density of the soil of ith layer (g cm-3)
Di = Depth of ith layer of the soil (mm)
CU = ∑ U
The seasonal CU was obtained by
adding CU values for each sampling
interval. Soil moisture extraction was
worked out for different soil depths for the
period of sampling interval during the crop
growth. Then, the total moisture extracted
(SMDt) from the root zone depth (0-60 cm)
was calculated using the expression
SMDt = SMD 1 + SMD2 + SMD3 + SMD4
where, SMDt = Soil moisture depleted from
0-60 cm
SMD1,2,3,4 = Soil moisture depleted from
0-15,15-30, 30-45 and 45-60 cm
Moisture depletion from each part
of the soil depth was then expressed as
percentage of total moisture depletion from
the part of soil depth. A comprehensive
analysis of water productivity (kg m-3)was
done. Crop water productivity was estimated
as ratio of maize yield (kg) to that of CU
(m3) of the crop and field water productivity
(kg m-3) was calculated as ratio of yield (kg)
to that of water applied to the crop including
rainfall (m3) in the season.
Results and Discussion
Crop establishment methods and yield
Transplanted rice rerecorded 1.09 tonne higher
yield than aerobic crop (4.63 and 4.35 tonne ha-1
in 2007 and 2008). The higher grain yield might
be due to efficient utilization of water and
nutrients by puddle transplanted rice
resulting in yield attributes. The low yields
in aerobic rice may be due to excessive
vegetative growth and more panicle density
that caused tiller mortality and spike let
sterility as compared to transplanted rice.
Similar results are also reported by Gill et
al. (2006).
Winter maize productivity grown under
zero-tilled conditions after aerobic rice was
higher than that after transplanted rice (Table 1)
on account of greater values of yield attributes
(cob number ha-1, cob weight, cob length,
cob girth, number of grains cob-1 and
shelling percentage). The favorable
39 Journal of Rice Research 2013, Vol. 6 No. 2
conditions under AR cultivation might have
improved the plant growth and dry matter
and also crop with optimum source-sink
ratio facilitate proper portioning of photo
synthetates and thus resulted in better filling
of grains. In case of transplanted method of
establishment, due to puddling soil structural
changes along with formation of hard pan
development in sub-soil might have
restricted the root growth which in turn
reduced shoot growth. Whereas in, aerobic
rice the dry land preparation was done and
good pulverized soil condition facilitated for
better root development and good crop
performance. These results are supported by
Gangwar et al. (2008). The interaction
between methods of crop establishment and
irrigation level indicated that maize grain
yield with 1.0 IW: CPE ratio irrigation was
significantly higher than 0.8 IW:CPE ratio
after both the methods of crop
establishment. Maximum benefit from
irrigation was realized under aerobic method
of cultivation in both years (Table 1). The
interaction between irrigation and P level
also attained level of significance.
Application of 30 kg P2O5ha-1 at irrigation
of 1.0 IW:CPE ratio resulted in comparable
grain yield of maize as that of 90 kg P2O5
ha-1 at irrigation level of 0.8 IW:CPE ratio.
The beneficial effect of P application was
more pronounced at IW: CPE ratio of 1.0
than 0.8 at all P levels (Table 2).
Crop establishment methods - water use
and water productivity
In the present study, transplanted method
recorded the highest field water use
compared to AR. It was observed that on an
average AR recorded a saving of 35.7% and
29.2% of field water compared to
transplanted rice in 2007 and 2008 (Table
3). LavBhushan et al. (2007) observed 23%
saving of irrigation water with direct seeded
rice over transplanted rice. The effective
rainfall during 2008 (5795 m3ha-1) was
much higher than that in 2007 (2238 m3
ha-1) and thus the water applied through
irrigation during 2008 was comparatively
lower than 2007. Therefore, the total water
use was higher during 2008 than 2007.
Field water productivity was lower in 2008
irrespective of establishment method
because of lower grain yield. In AR the field
water use was low as compared to
transplanted rice because of dry land
preparation which led to reduction in
irrigation water and total water requirement.
Similar findings were also reported by
Cabangon et al. (2000) and Tabbal et al.
(2000). Lower water consumption by AR
has resulted in higher water productivity
(0.40 and 0.34 kg m3in 2007 and 2008) as
40 Journal of Rice Research 2013, Vol. 6 No. 2
compared to the transplanted method of
cultivation (0.44 and 0.35 kg m3in 2007 and
2008 respectively) (Table 3). In AR, seepage
and percolation and evaporation losses are
greatly reduced and also increased effective
utilization of rain water which helped in
enhancing the water productivity (Singh and
Vishwanathan, 2006; Bouman et al., 2005;
Gill et al., 2006).
In zero-tillage maize, both the
methods of rice establishment utilized more
or less same field water under different
irrigation schedules during two years of
study (Table 4). Irrigation scheduled at 1.0
IW : CPE ratio has recorded more field
water use due to more number of irrigations
than 0.8 ratio. The field water productivity
was higher in the latter irrigation schedule
than that in the former. The CU of maize
after transplanted rice was less (343.8 and
362.5 mm) as compared to AR (382.8 and
396.2 mm) in both years and water
productivity of maize was found to be more
when grown after transplanted rice than after
over aerobic rice. In maize grown after
puddle rice, the leaching losses are minimum
where as after aerobic rice relatively leaching
of irrigation water is more due to un-puddled
condition.With increase in level of irrigation
from 0.8 to 1.0 IW : CPE ratio there was an
increase in CU of water by maize during
both the years of study. During 2008-09,
maximum CU was recorded due to more
number of irrigations provided to the maize
crop. Similar results of maximum water
requirement (58.86 cm) was recorded under
IW:CPE of 1.2 and minimum water
requirement (44.98 cm) was observed with
0.6 IW:CPE ratio was reported by Bharathi
et al.(2007).The system water use was
lowest in aerobic rice-maize system and thus
system water productivity was higher as
compared to transplanted rice-maize during
the years of study (Table 4).
Increase in level of P application
resulted in increase in CU (Table 5). With
each level of P increase from 0 to 90 kg
P2O5ha-1 the CU use increased
considerably. The difference in CU between
control and 90 kg P2O5ha-1 was 68.8 and
74.6 mm during 2007-08 and 2008-09
respectively.
The influence of irrigation
frequencies are more pronounced on CU use
rather than on water productivity. The
luxuriant crop growth at 1.0 IW: CPE which
utilized more irrigation water to meet the
higher crop demand and realized higher
productivity. The water productivity was
higher in maize grown after transplanted
than aerobic rice. Irrigation at IW:CPE ratio
of 0.8 recorded higher water productivity
41 Journal of Rice Research 2013, Vol. 6 No. 2
than irrigation at IW : CPE ratio of 1.0.
Increase in the level of P increased
the water productivity. The increase in water
productivity with increase in level of P was
noticed up to 30 kg P2O5ha-1 during 2007-
08 and upto 60 kg P2O5ha-1 during 2008-09.
Soil moisture extraction pattern
Based on the CU of water, soil moisture
extraction pattern was maximum from the
top 0-15 cm soil and decreased with each
successive soil layers irrespective of
preceding rice establishment methods, levels
of irrigation and phosphorus. Lowest
extraction was observed from 45-60 cm soil
depth (Table 6). Slightly more soil moisture
was extracted from deeper layers
(30-45 cm and 45-60 cm) in transplanted
rice as compared to aerobic rice during
second year. IW:CPE ratio of 1.0 resulted in
slightly more soil moisture extraction from
30-45 cm and 45-60 cm soil layers during
both the years. Increase in phosphorus level
increased the soil moisture extraction from
30-45 cm soil depth compared to control.
From the present study, it can be
concluded that in the irrigated command
areas the aerobic rice establishment method
would be a viable option in terms of water
saving and also aerobic rice-maize system
will be more productive and profitable and
results in higher system water productivity
indicating sustainability of aerobic rice-
maize system compared to the transplanted
rice-maize system.
References
Bharathi, V., Nandan, R., Kumar, V. and Pandy, I.B.
2007. Effect of irrigation levels on yield, water
use efficiency and economics of winter maize
(Zea mays) based intercropping systems. Indian
Journal of Agronomy 52 (1): 71-72.
Bouman, B.A.M., Yang, V., Wang, H., Wang, Z.,
Zhao, J. and Chen, B. 2005. Performance of
aerobic rice varieties under irrigated conditions
in North China. Field Crops Research 97:53-65.
Cabangon, R.J., Tuong, T.P., Tiak, E.B. and Bin, A.
2000. Increasing water productivity in rice
cultivation: impact of the large scale adoption of
direct seeding in muda irrigation system.
Proceeding of workshop 25-28 January
Bangkok, Thailand.
DMR 2009. Technical bulletin of Directorate of
Maize Research Centre, ICAR, New Delhi
2009/5: 10-11.
Gangwar, K.S., Tomar, O.K. and Panday, D.K. 2008.
Productivity and economics of transplanted and
direct seeded rice (Oryza sativa) based cropping
systems in Indo-Gangetic plains. Indian Journal
of Agricultural Sciences 78(8):655-658.
Gill, M.S., Kumar, A. and Kumar, P. 2006. Growth
and yield of rice (Oryza sativa) cultivars under
various methods and times of sowing. Indian
Journal of Agronomy 51(2):123-127.
LavBhushan., Jagdish, K., Ladha., Rajk Gupta.,
Singh S., Tirol A.P, Saharawat Y.S., Gathaia, M.
and Pathak, H. 2007. Saving of water and Labor
in Rice wheat system with no tillage and direct
seeding technology. Agronomy Journal
99:1288-1296.
Shankara Reddi, G.H. and Reddy, Y.T. 1995
Efficient use of irrigation water. Kalyani
Publishers pp 110-111.
Singh, A.K. and Vishwanathan, C. 2006. Aerobic rice
prospects for enhancing water productivity.
Indian Farming (December): 58-61.
Tabbal D.F., Bhuiyan, S.I. and Sibayan, E.B. 2000.
The dry seeding technique for saving water in
irrigation rice production systems. Proceedings
of International workshop on direct seeding in
Asian Rice System.
42 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1: Interaction effect of rice crop establishment method and irrigation
level on maize grain yield (kg ha-1)
IW:CPE ratio(I)
Rice crop establishment method (M)
2007-08
2008-09
Transplanted
Aerobic
Mean
Transplanted
Aerobic
Mean
0.8
5798
6462
6130
6258
6536
6396
1.0
6381
6728
6554
6808
7072
6940
Mean
6139
6545
6533
6803
SEm ±
CD(P=0.05
)
SEm ±
CD(P=0.05)
I
107
217
89
180
M
68
156
62
199
I at same or
different M
152
307
126
255
M at same or
different I
114
245
109
262
Table 2: Interaction effect of Irrigation and Phosphorus level on maize grain yield (kg ha-1)
P level( kg P2O5
ha-1)
Irrigation levels ( IW: CPE ratio)
2007-08
2008-09
0.8
1.0
Mean
0.8
1.0
Mean
0
4751
5125
4938
4938
5734
5340
30
5756
6333
6045
6506
6865
6686
60
6934
7350
7142
7058
7478
7268
90
7079
7408
7244
7084
7674
7379
Mean
6130
6554
6396
6940
SEm ±
CD(P=0.05)
SEm ±
CD(P=0.05)
P
132
292
116
225
I
107
217
89
180
Pat same or
different I
155
311
179
359
I at same or
different P
149
218
179
359
43 Journal of Rice Research 2013, Vol. 6 No. 2
Table 3: Influence of crop establishment method of rice on field water use (m3ha-1)
and field water productivity (kg m-3)
2007
2008
Transplanted
Aerobic
Transplanted
Aerobic
Number of irrigations
33
24
27
16
Irrigation water applied
12200
8400
10100
6500
Effective rainfall during crop period
2238
2238
5795
5795
Quantity of field water used
14438
10638
15895
12295
Field Water Productivity
0.40
0.44
0.34
0.35
Table 4: Influence of rice crop establishment methods and irrigation levels on field water
use (m3ha-1) and field water productivity (kg m-3 grain) in zero-tillage maize and rice-
maize system
2007-08
2008-09
Maize after Transplanted
rice
Maize after aerobic
rice
Maize after
Transplanted rice
Maize after
aerobic rice
IW: CPE ratio
0.8
1.0
0.8
1.0
0.8
1.0
0.8
1.0
Maize
Number of irrigations
Quantity of irrigation water
applied
8
4500
10
5500
8
4500
10
5500
10
5500
13
7000
10
5500
12
6500
Effective rainfall
339
339
534
534
365
365
--
--
Total quantity of water used
4839
5839
5034
6034
5865
7865
5500
6500
Field Water Productivity
1.33
1.18
1.31
1.16
1.07
0.80
1.17
1.04
Rice-maize system
Total quantity of water used
21071
16172
22839
18295
Water productivity
0.56
0.68
0.52
0.60
44 Journal of Rice Research 2013, Vol. 6 No. 2
Table 5: Consumptive use and crop water productivity of maize as influenced of rice crop
establishment method, irrigation and phosphorus level
Treatments
Consumptive use
(mm)
Crop water productivity
(kg m-3 )
2007-08
2008-09
2007-08
2008-09
Mean
Crop establishment methods (M)
Transplanting rice
343.75
362.46
1.83
1.82
1.83
Aerobic rice
382.79
396.20
1.78
1.76
1.77
Irrigation level (IW:CPE ratio)
0.8
376.95
404.62
1.68
1.62
1.65
1.0
421.10
458.14
1.69
1.53
1.61
Phosphorus levels (kg P2O5ha-1)
0
292.58
327.56
1.67
1.56
1.62
30
320.85
375.90
2.04
1.82
1.93
60
349.72
396.10
2.03
1.87
1.95
90
361.39
405.20
2.01
1.84
1.93
Data not analyzed statistically
Table 6: Soil moisture extraction pattern (mm) in zero-tillage maize as influenced by crop
establishment method irrigation and phosphorus level
Treatments
Soil depth (cm)
2007-08
2008-09
0-15
15-30
30-45
45-60
Total
0-15
15-30
30-45
45-60
Total
Crop establishment method
Transplanted rice
137.5
103.12
67.24
35.89
343.75
138.98
100.72
80.16
42.60
362.46
Aerobic rice
158.05
118.79
71.52
34.43
382.79
161.86
116.12
76.24
42.08
396.20
Irrigation level (IW:CPE ratio)
0.8
142.54
108.26
82.76
43.39
376.95
162.85
122.39
78.92
40.46
404.62
1.0
160.44
124.33
84.24
32.09
401.10
174.06
140.04
94.03
50.01
458.14
Phosphorus level (kg P2O5ha-1)
0
121.03
89.7
53.52
28.26
292.58
129.02
95.27
64.12
39.15
327.56
30
131.34
98.26
61.17
30.08
320.85
150.36
106.77
71.18
47.59
375.90
60
137.89
102.92
75.94
32.97
349.72
159.44
120.83
71.22
44.61
396.10
90
141.09
100.16
82.24
37.90
361.39
162.12
122.83
76.24
44.02
405.20
45 Journal of Rice Research 2013, Vol. 6 No. 2
Influence of Long Term Fertilizer Application on Soil Phosphatase Enzyme
Activity and Nutrient Availability in Rice –Rice Cropping System
M. Srilatha*, Palli Chandrasekhar Rao, S.H.K. Sharma and K. Bhanu Rekha
Regional Agricultural Research Station, Acharya N.G.Ranga Agricultural University, Jagtial.
Abstract
Build up of phosphorous in soil was
observed under long term fertilizer
experiments which were initiated in
kharif 2000-01 on clay soil at Regional
Agricultural Research Station, Acharya
N.G. Ranga Agricultural University,
Jagtial under All India Coordinated
Research Project (AICRP) in a
randomised block design for growing rice
–rice cropping system involving various
doses of N, NP, NPK, NPK with FYM, Zn
and S. The data generated during rabi
2010-11 (11th crop cycle) was used to
report the results. In the present study,
the activities of acid phosphatase and
alkaline phosphatase in soil were
determined during crop growth of rice.
Soil samples collected after harvest of rice
were analysed for organic carbon,
available N, P and K. The activity of acid
and alkaline phosphatase in soil at
different growth stages of rice revealed
that there was an increase in enzyme
activity up to active growth stages of crop
and later showed decrease. The activities
*Corresponding author: sriluss02@gmail.com
of acid and alkaline phosphatase were
significantly higher with application of
150% NPK followed by the treatment
100% NPK +FYM @ 10 t ha-1.
Phosphatase activity was at its peak at 60
days after transplanting stage.
Key words: Long term, phosphatase
activity, rice, fertilizers, FYM.
Usage of imbalanced fertilizers badly
influences production potential and soil
health. Integrated nutrient management will
not only sustain the crop production but also
be effective in improving soil health and
enhancing nutrient use efficiency. Enzyme
activities are considered as an index of
microbiological activity. A better
understanding of the role of these soil
enzymes in the ecosystem could provide a
unique opportunity for an integrated
biological assessment of soils due to their
crucial role in several soil biological
activities, their ease of measurement, and
their rapid response to the changes in soil
management.
46 Journal of Rice Research 2013, Vol. 6 No. 2
Enzyme levels in soil systems vary
in amounts primarily due to the fact that
each soil type has different amounts of
organic matter, composition and activity of
living organisms and intensity of the
biological processes. Since rice grows in the
interactive ecosystem involving soil –
microorganism –rice and atmosphere, rice
development consequentially affect soil
microorganisms and soil enzymatic
activities.
Among the various enzymes,
phosphatase speeds up soil organic
phosphorus decomposition and improves
soil phosphorous concentration, which is an
important index to assess soil phosphorus
bio –availability. Phosphatases are capable
of catalysing hydrolysis of esters and
hydrides of phosphoric acid. In soil
ecosystem, these enzymes are believed to
play critical roles in ‘P’ cycle as evidence
shows that they are correlated to ‘P’ stress
and plant growth. Apart from being good
indicators of soil fertility, phosphatase
enzymes play key role in the soil system
(Dick and Tadatabai, 1992). Acid
phosphatase provides a potential index of
mineralisation of soil organic P. Keeping
this in view, a study on the effect of
continuous application of fertilizers on soil
phosphatase enzyme activity at different
growth stages of rice was taken up.
Materials and Methods
The present investigation was carried out in
the on-going AICRP on Long Term
Fertilizer Experiments initiated in kharif
2000-01 at the experimental farm of
Regional Agricultural Research Station,
Acharya N.G. Ranga Agricultural
University, Jagtial. The experimental site is
situated at Longitude 78o45’ E to 79o0 E,
Latitude 18o45’ N to 19o0 N. The
experimental soil at the initiation of the
experiment was clayey (Inceptisol) in
texture with a soil pH 8.2 (1:2 soil: water
ratio), Electrical Conductivity 0.47 dSm-1
(1:2 soil: water ratio), organic carbon 0.79 %
and 107.6, 19.6 and 364 kg ha-1 of available
N, P and K. The mean annual total rainfall
of the area is 900–1500 mm.
Based on the soil test values for
available NPK, 120-60-40 kg N-P2O5-K2O
ha-1 was fixed as cent per cent optimum
recommended dose. The experiment was
laid out on permanent basis, the fertilizer
and manure doses were then fixed as per
treatments. Twelve (11+1) treatments with
four replications in a randomised block
design (unit plot size 12mx9m) are as
follows:
47 Journal of Rice Research 2013, Vol. 6 No. 2
T1–50%NPK ,
T2–100%NPK,
T3–150%NPK,
T4–100% NPK +HW,
T5–100% NPK+ZnSO4@ 10 kg ha-1(in
kharif),
T6–100% NP, T7–100% N alone,
T8–100% NPK+FYM@ 10 t ha-1(in each
kharif),
T9–100% NPK-S,
T10 –FYM @ 10 t ha-1( in each kharif and
rabi),
T11 –Control (No fertilizers, No manures),
T12 –Fallow (No crop , No fertilizers).
The nutrients were applied through
urea, single super phosphate, muriate of
potash and zinc sulphate, where as DAP was
used as a source of ‘P’ in T9. Recommended
chemical control and hand weeding
measures were adopted in all the treatments
except T4where fertilizers and only hand
weeding was practiced. The crop was
harvested at maturity manually. Soil samples
were collected at 30, 60, 90 days after
transplanting and at harvest. Acid and
alkaline phosphatase activities were assayed
by quantifying the amount of p-nitrophenol
released and expressed as µg of p-
nitrophenol released g-1 soil h-1as described
by Tabatabai and Bremner (1969).
Soil samples collected after harvest
of rice were air dried, ground to pass
through 2 mm sieve and then subjected to
chemical analysis. For soil organic carbon,
soil samples were sieved to pass through a
0.5 mm sieve. Soil organic carbon was
determined by the Walkley and Black
method (1934), available N by Subbaiah and
Asija (1956), P by Olsen method (Olsen et
al. 1954) and K by ammonium acetate
method (Black 1965).
Results and Discussion
The results obtained on the effect of long
term fertilizer application on acid
phosphatase activity are presented in Table.1
Phosphatase activity (expressed as µg of p-
nitrophenol released g-1 soil- h-1) in soils
collected from different treatments varied
significantly during all growth stages of
crop. Enzyme activity in soil increased with
age of the crop up to 60 days after
transplanting. These results are in
conformity with those of Vandana et al.
(2012). Acid phosphatase increase ranged
from 64.3 to 90.3, 77.3 to 127.9, 67.6 to
121.3 and 48.8 to 78.1during kharif and 72.7
to 120.6, 169.8 to 206.1, 86.1 to 138.7 and
65.6 to 100.5 µg of p-nitrophenol released g-
1soil- h-1 at 30, 60, 90 DAT and harvest
respectively during rabi .
48 Journal of Rice Research 2013, Vol. 6 No. 2
Soil enzyme activities increased with
increasing rate of NPK application. The
highest acid phosphatase activity recorded in
150% NPK treated plot (90.3 and 120.6 µg
of p-nitrophenol released g-1 soil- h-1 in
kharif and rabi respectively) was on par with
the application of 100% NPK along with
FYM @10 t ha-1 (85.1 and 110.5 µg of p-
nitrophenol released g-1 soil- h-1 in kharif
and rabi respectively), compared to other
treatments. The acid phosphatase activity
was lowest in 100% N alone (64.3 and 72.7
µg of p-nitrophenol released g-1 soil h-1 in
kharif and rabi respectively), indicating that
balanced nutrition of crop is responsible for
better proliferation of root and for maximum
activity of enzymes.
The increase in activity with
integrated application of organic manures
along with chemical fertilizer may be
attributed to the increasing population of
microorganisms like bacteria, etc., due to
increased availability of substrate through
organic manure there by resulting in high
microbial activity and release of these
enzymes in to the soil. Mishra et al, (2008)
reported that application of 100% NPK
along with FYM @ 10 t ha-1 to maize
resulted in increase in phosphatase activity.
Alkaline phosphatase activity ranged
from 73.5 to 94.8, 81.8 to 135.2, 70.2 to
125.9, 52.8 to 92.6 in kharif and 81.7 to
126.1, 127.9 to 177.4, 85.6 to 151.4 and 69.1
to 109.4 µg of p-nitrophenol released g-1 soil
h-1 at 30, 60, 90 DAT and harvest
respectively in rabi. The activity of alkaline
phosphatase was considerably higher (Fig.1
and 2) than that of acid phosphatase
irrespective of treatments. Alkaline
phosphatase activity increased sharply up to
60 DAT and there after declined gradually to
30 DAT level in all the treatments. The
highest alkaline phosphatase activity was fo
und in150% NPK treatment followed by the
application of 100% NPK +FYM. In general
these enzymes activities were found to be
high in rabi than kharif season.
Effect on available nutrients
Long term application of variable amounts
of nutrient levels either alone or in
combination, and along with organic
manures had profound influence on soil
fertility (Table.3). After 11th crop cycle soil
organic carbon status increased in all the
treatments, highest values were recorded
with application of organic manure alone
(FYM@10 t ha-1) and along with chemical
fertilizers (100% NPK+FYM). 150% NPK
Jrecorded highest soil available N (213 kg
ha-1), P (42.1 kg ha-1 and K (349 kg ha-1)
100% NPK +FYM treatment with 210, 43.2
and 326 kg ha-1 respectively indicating that
49 Journal of Rice Research 2013, Vol. 6 No. 2
integrated nutrient application improves the
soil fertility status equivalent to 150% NPK.
Data on available phosphorous indicates that
(Table. 5) available ‘P’ in treatment 100%
NP was 25.8 kg ha-1 whereas in treatment
receiving 100% N, it was 18.6 kg ha-1. Use
of 100% NP over 100% N significantly
improved the available P status of the soil. A
significant reduction in ‘P’ was observed
under N alone (3.6% depletion from the
initial) due to removal of ‘P’ by the crop in
the absence of external source of ‘P’ (Verma
et al., 2012).
Conclusions
From the study, it can be concluded that acid
phosphatase and alkaline phosphatase
activities in soil were significantly increased
with application of increased rate of
nutrients from 50% recommended dose to
150% of recommended dose of fertilizers.
Activity of alkaline phosphatase was higher
than acid phosphatase. Enzyme activity
increased sharply up to 60 DAT and
thereafter decreased gradually to 30 DAT
level. Continuous application of fertilizers
resulted in build up of available ‘P’ in soil
under long term fertilizer experiments.
References
Black, C.A. (1965) Methods of Soil Analysis. Part I.
American Society of Agronomy, Madison,
Wisconsin, USA.
Dick, W.A., Tabatabai, M.A., 1992. Potential uses of
soil enzymes. In: Metting Jr., F.B. (Ed.), Soil
Microbial Ecology: Applications in Agricultural
And Environmental Management . Marcel
Dekker, New York, pp. 95-127.
Jackson, M.L. 1967. Soil Chemical Analysis Prentis
Hall of India Pvt. Ltd., New Delhi. 111 –203.
Olsen, S.R., Cole, C.V., Watanabe, F.S. and Dean,
L.A.(1964) Estimation of available phosphorus
in soils by extraction with sodium bicarbonate.
United States Department of Agriculture
Circular 939.
Rai, T.N. and Yadav, J. 2011. Influence of inorganic
and organic nutrient sources on soil enzyme
activities. Journal of the Indian society of Soil
Science 59 (1): 54 –59.
Sridevi, S., Venkataramana, M. and Swaruparani.
2011. Soil enzyme activity and nutrient
availability as influenced by different nutrient
management practices in maize –onion cropping
system. Journal of Research ANGRAU 39(3):32
–37.
Subbaiah, B.V. and Asija, G.L. 1956. A rapid
procedure for the determination of available
nitrogen in soils. Current Science 25: 259-260.
Tabatabai, M.A. and Bremner, J.M. 1969. Use of P-
nitrophenyl phosphate for assay of soil
phosphatase activity. Soil Biology and
Biochemistry 1: 301-307.
Vandana, L.J., Rao, P.C. and Padmaja, G. 2012.
Effect of crop cover on soil enzyme activity.
Journal of Reseacrh ANGRAU. 40 (4): 1 -5.
Verma, A, Nepalia, V and Kanthaliya, P.C. 2005.
Effect of continuous cropping and fertilization on
crop yields and nutrient status of a Typic
Haplustept. Journal of the Indian Society of Soil
Science 53 (3): 365 –368.
Walkley, A. and Black, C.A. 1934. Estimation of
organic carbon by chromic acid titration method.
Soil Science 37: 29-38.
50 Journal of Rice Research 2013, Vol. 6 No. 2
Fig.1 Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1) at
various growth stages of rice (rabi).
Fig.2 Changes in soil alkaline phosphatase activity (µg p-nitrophenol released
g-1soil h-1) at various growth stages of rice (rabi).
Table 1: Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1)
at various growth stages of rice during kharif
Treatments
Days after transplanting (kharif)
30
60
90
Harvest
50% NPK
74.6
92.2
88.2
52.1
100%NPK
80.8
110.4
101.3
67.0
150% NPK
90.3
127.9
121.3
78.1
100%NPK + HW
82.5
110.5
100.7
65.5
100%NPK + Zn
83.2
107.6
99.9
64.2
100%NP
65.6
80.7
74.1
55.5
100%N
64.3
77.3
67.6
48.8
100%NPK + FYM
85.1
116.7
112.5
75.5
100%NPK - S
81.9
100.8
103.6
62.3
FYM
87.4
104.2
100.6
74.5
Control
73.1
89.1
80.8
61.1
50 Journal of Rice Research 2013, Vol. 6 No. 2
Fig.1 Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1) at
various growth stages of rice (rabi).
Fig.2 Changes in soil alkaline phosphatase activity (µg p-nitrophenol released
g-1soil h-1) at various growth stages of rice (rabi).
Table 1: Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1)
at various growth stages of rice during kharif
Treatments
Days after transplanting (kharif)
30
60
90
Harvest
50% NPK
74.6
92.2
88.2
52.1
100%NPK
80.8
110.4
101.3
67.0
150% NPK
90.3
127.9
121.3
78.1
100%NPK + HW
82.5
110.5
100.7
65.5
100%NPK + Zn
83.2
107.6
99.9
64.2
100%NP
65.6
80.7
74.1
55.5
100%N
64.3
77.3
67.6
48.8
100%NPK + FYM
85.1
116.7
112.5
75.5
100%NPK - S
81.9
100.8
103.6
62.3
FYM
87.4
104.2
100.6
74.5
Control
73.1
89.1
80.8
61.1
50 Journal of Rice Research 2013, Vol. 6 No. 2
Fig.1 Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1) at
various growth stages of rice (rabi).
Fig.2 Changes in soil alkaline phosphatase activity (µg p-nitrophenol released
g-1soil h-1) at various growth stages of rice (rabi).
Table 1: Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1)
at various growth stages of rice during kharif
Treatments
Days after transplanting (kharif)
30
60
90
Harvest
50% NPK
74.6
92.2
88.2
52.1
100%NPK
80.8
110.4
101.3
67.0
150% NPK
90.3
127.9
121.3
78.1
100%NPK + HW
82.5
110.5
100.7
65.5
100%NPK + Zn
83.2
107.6
99.9
64.2
100%NP
65.6
80.7
74.1
55.5
100%N
64.3
77.3
67.6
48.8
100%NPK + FYM
85.1
116.7
112.5
75.5
100%NPK - S
81.9
100.8
103.6
62.3
FYM
87.4
104.2
100.6
74.5
Control
73.1
89.1
80.8
61.1
51 Journal of Rice Research 2013, Vol. 6 No. 2
Fallow
82.9
100.9
98.0
76.8
S.Em+
4.0
7.2
5.5
4.6
CD (0.05)
8.2
14.7
11.2
9.5
CV (%)
7.2
10.1
8.1
10.2
Table 2: Changes in soil acid phosphatase activity (µg p-nitrophenol released g-1 soil h-1)
at various growth stages of rice during rabi
Treatments
Days after transplanting (rabi)
30
60
90
Harvest
50% NPK
88.1
187.9
106.7
77.8
100%NPK
102.2
192.0
122.9
87.4
150% NPK
120.6
206.1
138.7
100.5
100%NPK + HW
102.1
191.5
126.7
91.2
100%NPK + Zn
105.3
194.2
126.9
89.6
100%NP
78.5
177.0
91.5
70.1
100%N
72.7
169.8
86.1
65.6
100%NPK + FYM
110.5
201.1
155.6
95.4
100%NPK - S
101.3
194.0
129.4
89.6
FYM
107.9
198.2
140.2
92.0
Control
83.8
181.9
93.5
74.5
Fallow
100.1
191.5
138.1
95.7
S.Em+
4.4
6.6
6
4.6
CD (0.05)
8.9
13.5
12.2
9.3
CV (%)
6.3
4.9
7.1
7.6
Table 3: Changes in soil alkaline phosphatase activity (µg p-nitrophenol released g-1 soil
h-1) at various growth stages of rice during kharif
Treatments
Days after transplanting(kharif)
30
60
90
Harvest
50% NPK
82.2
86.1
94.0
78.6
100%NPK
87.9
97.6
100.0
82.3
150% NPK
94.8
135.2
125.9
92.6
100%NPK + HW
83.1
97.1
99.0
78.9
100%NPK + Zn
82.6
94.1
99.1
86.1
100%NP
79.9
85.9
79.8
59.2
100%N
73.5
81.8
70.2
52.8
100%NPK + FYM
91.9
123.4
105.1
88.7
100%NPK - S
85.2
99.5
102.0
82.4
FYM
82.2
102.7
104.8
88.5
Control
83.7
85.5
87.5
62.2
Fallow
89.3
110.3
105.3
85.4
S.Em+
3.9
4.4
4.9
3.5
CD (0.05)
7.9
8.9
10.1
7.1
CV (%)
6.5
6.2
7.2
6.3
52 Journal of Rice Research 2013, Vol. 6 No. 2
Table 4: Changes in soil alkaline phosphatase activity (µg p-nitrophenol released g-1
soil h-1) at various growth stages of rice during rabi
Treatments
Days after transplanting(rabi)
30
60
90
Harvest
50% NPK
94.2
142.0
109.1
83.9
100%NPK
103.8
152.0
125.2
94.9
150% NPK
126.1
177.4
151.4
109.4
100%NPK + HW
102.0
153.6
121.9
96.8
100%NPK + Zn
103.7
149.8
123.1
93.9
100%NP
85.6
132.0
96.7
76.9
100%N
81.7
127.9
85.6
69.1
100%NPK + FYM
114.7
167.0
140.1
109.3
100%NPK - S
100.9
151.6
123.7
94.6
FYM
118.5
156.1
137.0
100.6
Control
87.6
136.6
97.0
86.4
Fallow
114.8
157.8
131.6
103.2
S.Em+
3.3
3.9
3.3
2.4
CD (0.05)
6.7
7.9
6.8
4.9
CV (%)
4.5
3.6
3.9
3.6
Table 5: Soil fertility status after harvest of rice (After 11th crop cycle)
Treatments
Organic carbon
(%)
Available Nitrogen
(kg ha-1)
Available Phosphorous
(kg ha-1)
Available
Potassium
(kg ha-1)
50% NPK
0.81
204
29.5
320
100%NPK
0.8
185
31.1
322
150% NPK
0.81
213
42.1
349
100%NPK + FYM
1.01
210
43.2
326
FYM
1.04
247
38.2
316
Control
0.8
191
20.3
309
CD (0.05)
0.16
NS
6.7
NS
53 Journal of Rice Research 2013, Vol. 6 No. 2
Relative Composition of Egg Parasitoids of Rice Yellow Stem Borer,
Scirpophaga incertulas (Walker)
N. Rama Gopala Varma*, R. Jagadeeshwar and Chitra Shanker
Rice Section, Acharya N.G. Ranga Agricultural University, Agricultural Research Institute,
Rajendranagar and Directorate of Rice Research, Rajendranagar, Hyderabad
Abstract
Studies on the extent of parasitization of
yellow stem borer (YSB), Scirpophaga
incertulas (Wlk.) egg masses for four
consecutive years (2009-2012) was
assessed in insecticide free paddy field
at Rajendranagar, Hyderabad, Andhra
Pradesh. The hymenopteran
parasitoids, Telenomus dignus (Gahan),
(Scelionidae), Tetrastichus schoenobii
Ferriere (Eulophidae) and
Trichogramma japonicum Ashmead
(Trichogrammatidae) were the three
important YSB egg parasitoids recorded
from this area which played a pivotal
role in population regulation of YSB.
The peak parasitization ranging from
75.29 to 97.56% was observed during
kharif, particularly in October. The
parasitization during rabi varied from
42.60% to 69.79%. In kharif,
parasitization by Trichogramma was
more prevalent during September, while
that of Telenomus and Tetrastichus was
more during October.
__________________________________
*Corresponding author: varmanrg@gmail.com
Keywords: Scirpophaga incertulas, egg
parasitoids, egg parasitization,
Trichogramma, Telenomus, Tetrastichus
Rice is one of the most important food
crops, with its production crossing 100
million tonnes in 2011-12, accounting for
22.81 per cent of global production. In
Andhra Pradesh, rice is cultivated in about
38 lakh hectares with a production of
72.12 lakh metric tonnes and productivity
of 2900 kg/ha. Among the various insect
pests of rice inflicting yield loss, yellow
stem borer, Scirpophaga incertulas
(Walker) is considered one of the major
insect pest of rice, having a potential to
cause yield losses ranging from 3%-95%
in India (Ghose et al., 1960) while Prasad
et al. (2007) reported yield losses ranging
from 38%-50%. In terms of grain
production loss over ecosystems, 1% dead
heart, or white ear head, or both phases of
stem borer damage would be 108 kg/ha,
174 kg/ha and 278 kg/ha, respectively
(Muralidharan and Pasalu, 2006).
Host plant resistance to yellow
stem borer is ambiguous. The most
54 Journal of Rice Research 2013, Vol. 6 No. 2
commonly used method of control is
insecticides, but less effective due to the
concealed habit of the larvae. Biological
control offers an eco-friendly option for
management of this pest. Several workers
have reported on egg parasitsation of YSB
from different parts of the country.
Chandramohan and Chellaiah (1984)
identified several parasites of S. incertulas
from Coimbatore. Hikim (1988) reported
that parasitoid activity showed periodical
fluctuation coinciding with emergence of
YSB moths. Chakraborty (2012) recorded
egg parasitoids of YSB from West Bengal.
The present study was contemplated to
document the extent of parasitism by egg
parasitoids against rice yellow stem borer
at Rajendranagar, Hyderabad.
Materials and Methods
Field study was conducted at the Rice
Section of Agricultural Research Institute,
Rajendranagar, Hyderabad, during four
consecutive crop years (2009-2012) with
variety Sumati during kharif and var.
Tellahamsa during rabi. The observation
plot (1000 m2) was kept pesticide free and
the planting time was adjusted to facilitate
incidence of rice yellow stem borer and its
natural enemies. The entire plot was
divided into 4 blocks of equal size,
demarcated with bunds and channels. The
stem borer egg masses were collected from
these unsprayed blocks twice or thrice in a
crop season depending upon the
availability of egg masses. A minimum
of 8-10 egg masses were collected from
each block accounting for 30-40 egg
masses per observation date.
The collected egg masses were
placed individually in separate plastic vials
(15 cm long and 2.5 cm wide) and
observed periodically for emergence of
adult parasitoids. After the emergence, the
adult parasitoids were observed under a
stereo-zoom microscope (Magnus MSZ
with a zoom ratio of 1:7), to identify the
respective species and number.
The per cent egg parasitism was
computed based on number of live larvae
and parasitoid emergence. The species
identification of egg parasitoids was done
at Directorate of Rice Research,
Rajendranagar, Hyderabad.
Results and Discussion
The egg parasitoids of the yellow stem
borer, S. incertulas prevalent in
Rajendranagar were identified as the
hymenopterans Trichogramma japonicum
(Ashm.) (Trichogrammatidae), Telenomus
dignus (Gahan) (Scelionidae) and
Tetrastichus schoenobii (Ferr.)
(Eulophidae). Perusal of kharif 2009 data
(Table 1) revealed that 24 per cent of the
eggs were parasitized during 2nd week of
55 Journal of Rice Research 2013, Vol. 6 No. 2
October, while maximum parasitization
was observed during October 1st (75.29)
and 3rd weeks (82.23%). Lakshmi et al.
(2010) reported 95 per cent egg mass
parasitization. The composition of
Tetrastichus, Telenomus and
Trichogramma was 43.13 per cent, 25.90
per cent and 6.26 per cent, respectively
during 1st week of October, 6.74, 6.99 and
10.30 per cent during October 2nd week
and 35.88, 39.77 and 6.38%, during
October 3rd week. Chakraborty (2012)
reported parasitization by Trichogramma
sp.,Telenomus spp., and Tetrastichus spp.
to be 6.12 per cent, 9.53 per cent and 48.44
per cent, respectively.
During kharif 2010, total
parasitization increased gradually from
September 1st week to October 4th week
ranging from 39.34% to 97.56%, except
during fourth week of September where in
only 33.33% eggs were parasitized (Table
1). Trichogramma was the predominant
egg parasitoid during September, while it
was overtaken by Tetrastichus schoenobii
and Telenomus dignus during October 4th
week.
Lakshmi et al. (2010) reported that T.
schoenobii was prevalent from September
to November and Trichogramma and
Telenomus from September to October,
but the activity of egg parasitoids
decreased during November. Similar
observations were made in the present
study. During kharif 2011, the egg mass
parasitization of Tetrastichus,Telenomus
and Trichogramma was 20.8 per cent, 28.0
per cent and 13.2 per cent during October
1st week and 42.5, 6.2 and 22.0 during 2nd
week, respectively. The parasitization was
relatively low during kharif 2012 with
37.96 per cent, 68.97 per cent and 29.45
per cent parasitization, respectively during
3rd week of September, 3rd week of
October and 1st week of November.
Similarly during kharif 2012
Trichogramma was the predominant egg
parasitoid during September, while
Telenomus and Tetrastichus have become
dominant during October.
The total parasitization during rabi
2009-10 varied from 51.78% during 4th
week of March to 42.60% in 3rd week of
April (Table 2). During rabi 2009-10
Telenomus was the predominant egg
parasitoid followed by Trichogramma and
meager incidence of Tetrastichus was
noticed.
During rabi 2010-11 maximum
parasitization (69.79%) was recorded
during April 3rd week with Trichogramma
being the predominant egg parasitoid.
Contrastingly, Tetrastichus parasitization
was more during April 3rd and 4th weeks,
while Telenomus parasitization was
negligible during rabi 2010-11. Gupta et
56 Journal of Rice Research 2013, Vol. 6 No. 2
al. (1985) reported egg parasitization of
30.6% and 23.7% respectively during
kharif and rabi by T. schoenobii while in
the present study the parasitization by T.
schoenobii ranged from 2.19%
to 48.61% during kharif and 4.35% to
19.14% during rabi.
Even though all the three egg
parasitoids were observed, Trichogramma
was more predominant during September,
while the other two egg parasitoids viz.,
Telenomus and Tetrastichus dominated
during October. At Navsari, Gujarat, T.
dignus and T.schoenobii were most
abundant parasitoids of YSB eggs (Pandya
et al., 1995) and T. schoenobii was
reported to be second important parasitoid
during winter (Hikim, 1988). Senapati et
al. (1999) reported that the extent of
parasitism in different parts of India ranges
from 4.0% to 97.2%.
Further, it was observed that there
was larval survival in egg masses
parasitized by Trichogramma but very
rarely live larvae were recorded from egg
masses parasitized by Telenomus and
Tetrastichus. The extent of parasitization
was more during kharif than during rabi.
It was observed that mostly the egg masses
were parasitized either by single or two
parasitoid species. Occasionally all the
three parasitoid species were observed in a
single egg mass. Chakraborty (2012) also
reported parasitization of YSB egg mass
by more than one species viz.,
Trichogramma spp + Telenomus spp
(3.46%), Telenomus + Tetrastichus
(21.06%) and Trichogramma +
Tetrastichus (2.35%).
The study on composition of egg
parasitoids of rice yellow stem borer, S.
incertulas revealed that Trichogramma
japonicum, Telenomus dignus and
Tetrastichus schoenobii are predominant
egg parasitoids of this region.
Considerable variations in egg parasitoid
composition were observed across the
seasons and in different months within the
season. Looking at the predominance of
egg parasitoids in kharif than in rabi there
is a greater scope of conserving these
parasitoids and augmenting with
Trichogramma releases, particularly
during September and October months, so
that the surviving larval population after
natural parasitization can be taken care of
at the egg stage, through inundation,
whereby pesticide usage can be
minimized. During rabi natural
parasitization is relatively low
necessitating more inundative releases for
effective management of yellow stem
borer.
References
57 Journal of Rice Research 2013, Vol. 6 No. 2
Chakraborty, K. 2012. Relative composition of egg
parasitoid species of yellow stem borer,
Scirpophaga incertulas Wlk. in paddy field at
Uttar Dinajpur, West Bengal, India. Current
Biotica 6 (1):42- 52.
Chandramohan, N. and Chellaiah, S. 1984. Parasite
complex of yellow stem borer (YSB).
International Rice Research Newsletter 9
(6):21.
Ghose, R.L.M., Ghatge, M. B. and Subramanyan,
V. 1960. Rice in India. Revised Edition. Indian
Council of Agricultural Research, New Delhi
pp 74.
Gupta, M., Chaugule, R.A., Pawar, A.D. 1985.
Role of Tetrastichus schoenobii Ferrierre in
controlling yellow rice borer, Scirpophaga
incertulas Wlk. Plant Protection Bulletin of
India 37 (2):7-12.
Hikim, I.S. 1988. Seasonal parasitism by egg
parasites of yellow stem borer, Scirpophaga
incertulas (Lepidoptera: Pyralidae).
Entomologia 33(1):115-124.
Lakshmi, V.J., Surekha, K. and Pasalu, I.C. 2010.
Parasitization of rice yellow stem borer,
Scirpophaga incertulas (Walker) egg masses.
Annals of Plant Protection Sciences 18 (2):
366-369.
Muralidharan K. and Pasalu, I.C. 2006.
Assessments of crop losses in rice ecosystems
due to stem borer damage (Lepidoptera:
Pyralidae). Crop Protection 25: 409–417.
Pandya, H.V., Sah, A.H., Patel, C.B., Purohit, M.S.
and Rai, A.B. 1995. Study of egg parasitism of
rice yellow stem borer in Gujarat. Gujarat
Agricultural University Research Journal 21
(1):197-199.
Prasad, S.S., Gupta, P.K. and Kanaujia, B.L. 2007.
Simulation study on yield loss due to
Scirpophaga incertulas on semi deep water
rice. Annals of Plant Protection Sciences 15:
491-492.
Senapati, B. and Panda, S.K. 1999. Rice stem
borers. In: Insects of cereals and their
management. Applied Zoologist Research
Association, Cuttack. pp169.
58 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1: Relative composition of egg parasitoids of rice yellow stem borer in kharif
season at Rajendranagar
Year
Trichogramma
japonicum
Telenomus
dignus
Tetrastichus
schoenobii
Total **
2009
% Egg Parasitization*
October (1st week)
6.26
25.90
43.13
75.29
October (2nd week)
10.30
6.99
6.74
24.00
October (3rd week)
6.38
39.97
35.88
82.23
2010
September (1st week)
39.34
0.00
0.00
39.34
September (2nd week)
28.70
14.29
0.00
42.99
September (3rd week)
39.40
10.34
6.90
56.64
September (4th week)
16.68
14.46
2.19
33.33
October (4th week)
7.54
41.41
48.61
97.56
2011
October (1st week)
13.20
28.00
20.8
54.00
October (2nd week)
22.00
6.20
42.5
70.70
2012
September (3rd week)
24.52
13.44
0.00
37.96
October (3rd week)
11.86
35.91
21.20
68.97
November (1st week)
15.34
11.17
2.94
29.45
* Each value is a mean of 30 to 40 egg masses
** The total indicates the extent of parasitization observed in the specified week
Table 2: Relative composition of egg parasitoids of rice yellow stem borer in rabi season
at Rajendranagar
Year
Trichogramma
japonicum
Telenomus
dignus
Tetrastichus
schoenobii
Total**
2009-10
% Egg Parasitization*
March
(4th week)
19.74
26.33
5.71
51.78
April
(3rd week)
8.57
34.03
0.00
42.60
2010-11
April
(1st week)
34.10
8.70
4.35
47.15
April
(2nd week)
52.40
0.31
17.38
69.79
April
(4th week)
32.20
0.57
19.14
51.96
* Each value is a mean of 30 to 40 egg masses
** The total indicates the extent of parasitization observed in the specified week
59 Journal of Rice Research 2013, Vol. 6 No. 2
Study on Bio-Efficacy of Certain Acaricides Alone and in Combination
with Propiconazole against Rice Panicle Mite, Stenotarsonemus Spinki
Smiley
A. Venkat Reddy*, R. Sunitha Devi, S. Dhurua and D. Vishnu Vardhan Reddy
Regional Agricultural Research Station, Mulugu Road, Warangal-506007, Andhra Pradesh
Abstract
Four acaricides (Diafenthiuron,
Propargite, Dicofol and Profenophos)
and in combination with fungicide
(Propiconazole) were evaluated for their
efficacy against rice panicle mite for the
management of grain damage during
field trials conducted at Regional
Agricultural Research Station, Acharya
N.G. Ranga Agricultural University,
Warangal, A.P for three consecutive
kharif seasons of 2010, 2011 and 2012.
Among all the treatments, Dicofol 18.5
EC + Propiconazole 25 EC @ 5 ml+1
ml/l was found to be the most effective
treatment followed by Diafenthiuron 50
WP + Propiconazole @ 1.5 g + 1 ml/l
and Profenophos 50 EC + Propiconazole
25 EC @ 2 ml+1ml/l. Among all the
treatments, acaricides in combination
with fungicide gave higher efficacy
when compared to acaricides alone.
Key words: Rice, panicle mite, acaricide,
fungicide, bio-efficacy.
_____________________________________
* Corresponding author: adrrars_wgl@yahoo.co.in
Rice, the staple food of nearly half of the
humanity is mainly grown and consumed
in Asian countries. India is number one in
area and it ranks second in rice production,
but per hectare yield or productivity is
low.
Traditionally insect pests, diseases
and weeds are the triple evils responsible
for lower yields of rice in India. Of late,
mites are assuming major status in rice
crop in India as well as in Andhra Pradesh.
Among different species of mites
associated with rice crop, the rice panicle
mite or sheath mite is most important. The
rice panicle mite or sheath mite,
(Stenotarsonemus spinki) alone and in
association with sheath rot fungus,
(Acrocylindrium oryzae) causes grain
discoloration, ill-filled, chaffy grains and
often cause heavy losses. It has been
reported that this mite caused yield losses
ranging from 4.9% to 23.7% (Natalie et
al., 2009). Several studies were conducted
to test the efficacy of insecticides alone
against panicle mite (Bhanu et al., 2006;
Laxmi et al., 2008). However, adequate
60 Journal of Rice Research 2013, Vol. 6 No. 2
information is not available on the efficacy
of acaricides alone and in combination
with fungicides. Therefore, the present
study was conducted to evaluate the
efficacy of different acaricides alone and
in combination with fungicide,
propiconazole against rice panicle mite
under field conditions.
Materials and Methods
Field trials were conducted at Regional
Agricultural Research Station, Warangal,
Andhra Pradesh for three years i.e., 2010,
2011 and 2012 Kharif seasons to evaluate
the efficacy of certain acaricides alone and
in combination with fungicide-
Propiconazole against panicle mite. The
trials were laid in a Randomized Block
Design (RBD) with nine treatments and
three replications with a plot size of 20 m2.
The popular rice variety, BPT-5204 which
is susceptible to panicle mite was chosen.
All the recommended package of practices
were implemented in all the treatments
except treatment sprayings. Three
sprayings of chemicals were given at
panicle initiation stage, boot leaf stage and
at 50 per cent panicle emergence using
knapsack sprayer with a spray fluid
volume of 500 l/ha. Observations were
recorded on number of healthy grains,
number of discolored grains, number of
chaffy grains per panicle, grain yield per
plot and the data was expressed as per cent
discolored grains+ chaffy grains and per
cent reduction of discolored grains +
chaffy grains over control and grain yield
per hectare.
Results and Discussion
The pooled data for three years in respect
of per cent discolored grains + chaffy
grains, per cent reduction over control and
grain yield/ha is depicted in Table 1. The
results indicated that among all the
treatments, Dicofol 18.5 EC +
Propiconazole 25 EC @ 5 ml + 1 ml/l was
significantly highly effective , where in the
per cent grain discoloration + chaffy grains
was the lowest (8.3%) and per cent
reduction of grain discoloration + chaffy
grains was the highest (60.8%) with
highest grain yield of 7049 kg/ha. The
next best treatments were: Diafenthiuron
50 WP + Propiconazole 25 EC @ 1.5 g + 1
ml/l (9.8%, 53.8% respectively) and
Profenophos 50 EC + Propiconazole 25
EC @ 2 ml + 1 ml/l (10.1%, 52.4%
respectively) and were found to be on par
with each other in efficacy and grain yield
(6768 and 6698 kg/ha respectively). The
lowest efficacy was recorded with
Propargite 57 EC + Propiconazole 25 EC
@ 1.5 ml + 1 ml/t where in, the per cent
grain discoloration + chaffy grain was the
highest (13.8%) and the per cent reduction
61 Journal of Rice Research 2013, Vol. 6 No. 2
over control was lowest (33.8%). Among
the treatments, all the acaricide treatments
alone have shown significantly lower
efficacy by showing highest grain
discoloration + chaffiness and lowest per
cent reduction over control compared to
combination of acaricides with
propiconazole. Among all the treatments,
significantly lowest efficacy was noticed
with Progargite 57 EC @ 1.5 ml/l (15.3%
and 27.8% respectively) followed by
Diafenthiuron 50 WP @ 1.5 g/l (14.3%,
32.5%, respectively) and Dicofol 18.5 EC
@ 5 ml (13.9%, 34.4%, respectively)
which were found on par with each other.
Among the acaricides alone treatments,
Profenophos 50 EC @ 2 ml/lt was found
to be the best treatment by showing
relatively lower percent grain discoloration
+ grain chaffiness (12.2%) and relatively
higher percent reduction (34.4%) over
control.
With respect to grain yield,
significantly highest yield was observed
with Dicofol 18.5 EC + Propiconazole 25
EC @ 5 ml + 1 ml/l (7049 kg/ha) followed
by Diafenthiuron 50 WP + Propiconazole
25 EC @ 1.5 g + 1 ml (6768 kg/ha). The
lowest grain yield was recorded in
Propargite 57 EC @ 1.5 ml/l (6358 kg/ha)
but significantly superior over untreated
control (5667 kg/ha).
The present finding on superior
efficacy of acaricides in combination with
fungicides compared to acaricides alone
was in conformity with findings of Suresh
et al. (2013). Bhanu et al. (2006) and Loet
al.(1981) also reported superior efficacy
of acaricides like Dicofol and Profenophos
against panicle mite in rice. In India,
grains infested with S.spinki were
described as being discolored and
pathogenic fungi were isolated from mite
(Rao and Prakash, 2003). Chen et al,
(1979) found that S.spinki carried spores of
Acrocylindrium Oryzae on their body and
attributed the plant symptoms to a
combination of S.spinki damage and
disease. Miticides that have been tested
under laboratory conditions reported to
cause more than 95 per cent mortality of
adult S.spinki. Field trials conducted in
India reported up to 90 per cent mortality
following treatments with certain
acaricides (Bhanu et al., 2006 and Ghosh
et al., 1998). The present findings clearly
indicate that apart from panicle mite,
several pathogens especially sheath rot
fungus, Acrocylindrium oryzae was
responsible for grain damage. Hence,
invariably an effective fungicide in
combination with effective acaricide may
be recommended to the farmers for
reducing grain damage associated with
panicle mite and pathogens. Based on
overall performance, Dicofol 18.5 EC +
62 Journal of Rice Research 2013, Vol. 6 No. 2
Propiconazole 25 EC @ 5 ml + 1 ml/l
followed by Diafenthiuron 50 WP +
Propiconazole 25 EC 1.5 g + 1 ml and
Profenophos 50 EC + Propiconazole 25
EC @ 2 ml + 1 ml/l may be suggested to
the farmers for managing grain damage
due to panicle mite in association with
pathogens.
References
Bhanu, V., Reddy, S.P. and Zaheeruddin, S.M.
2006. Evaluation of some acaricides against
leaf mite and sheath mite in rice. Indian
Journal of Plant Protection 34: 132-133.
Chen, C.N., Cheng,C.C. and Hsiano,K.C.1979.
Bionomics of Stenotarsonemus spinki
attacking rice plants in Taiwan. Plant
Protection Bulletin 22(1): 31-39.
Ghosh, S.K., Prakash, A. and Rao, J.1998. Efficacy
of some chemical pesticides against rice
tarsonemid mite Stenotarsonemus spinki
Smiley. (Acari: Tarsonemidae) under
controlled conditions. Environmental Ecology
16:913-915.
Laxmi, V.J., Krishnaiah, N.V., Pasalu, I.C. and
Katti, G. 2008. Bio-ecology and management
of rice mites. A review. Agricultural Reviews
29(1): 31-39.
Lo, K.C., Ho, C.C and Lin, K.C. 1984. Screening
of chemicals for the control of rice tarsonemid
mite, Stenotarsonemus spinki.Journal of
Agricultural Research, China 30(3): 303-307.
Natalie, A. Hummel., Boris A. Castro., Eric M. Mc
Donald., Miguel A.Pellerano and Ronald
Ochoa. 2009. The panicle rice mite,
Stenotarsonemus Spinki Smiley, a re-
discovered pest of rice in the United States.
Crop Protection 1-14.
Rao, J. and Prakash, A. 2003. Panicle mites causing
sterility in farmers’fields in India. Journal of
Applied Zoology Research 14:212-217.
Suresh, D., Bhushan, V.S., Ramgopal Varma, N
and Ramesh, B. 2013. Efficacy of Acaricides
alone and in combination with propiconazole
against rice panicle mite / sheath mite,
Stenotarsonemus spinki.Journal of
Agricultural Science and Technology B 36:
107-110.
63 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1. Efficacy of acaricides alone and in combination with fungicide in the management of grain damage due to rice panicle
mite
Treatments
Dose/l
% discolored grains + Chaffy
grains
% Reduction of discolored
grains + chaffy grains over
control
Grain yield (kg/ha)
2010
2011
2012
Pooled
2010
2011
2012
Pooled
2010
2011
2012
Pooled
Diafenthiuron 50 WP +
Propiconazole 25 EC
1.5g+1.0ml
11.3
10.7
7.5
9.8
19.3
64.0
62.1
53.8
7855
7575
4875
6768
Propargite 57 EC +
Propiconazole 25 EC
1.5ml+1.0ml
11.3
17.0
13.1
13.8
19.3
42.8
33.8
34.9
7315
7426
4650
6500
Dicofol 18.5 EC+
Propiconazole 25 EC
5.0ml+1.0ml
8.0
9.9
6.9
8.3
42.9
66.7
65.2
60.8
7950
8182
5015
7049
Profenephos 50 EC+
Propiconazole 25 EC
2.0ml+1.0ml
12.3
12.8
5.3
10.1
12.1
56.9
73.2
52.4
7710
7236
5150
6698
Diafenthiuron 50 WP
1.5g
13.7
16.1
13.0
14.3
2.1
45.8
34.3
32.5
7470
7055
4580
6368
Propargite 57 EC
1.5ml
12.7
15.9
15.6
15.3
9.3
46.5
21.2
27.8
7475
7135
4465
6358
Dicofol 18.5 EC
5.0ml
15.0
14.5
12.1
13.9
7.1
51.2
38.8
34.4
7590
6575
4715
6793
Profenephos 50 EC
2.0ml
11.0
15.2
10.5
12.2
21.4
48.8
47.0
42.5
7530
7435
4890
6618
Untreated control
-
14.0
29.7
19.8
21.2
-
-
-
-
6375
6507
4120
5667
CD (0.05%)
3.2
2.5
2.7
2.8
2.5
5.1
4.8
4.5
355.0
215.7
175.5
248.9
SEm±
1.5
1.2
1.3
1.3
1.2
2.4
2.3
2.1
159.0
103.2
82.8
115.0
64 Journal of Rice Research 2013, Vol. 6 No. 2
Compatibility of Fungicides and Insecticides Targeting Sheath Blight and
Major Rice Pests
V. Bhuvaneswari* and S. Krishnam Raju
Department of Plant Pathology, Andhra Pradesh Rice Research Institute & Regional
Agricultural Research Station, Maruteru,, Acharya N.G. Ranga Agricultural University,
Andhra Pradesh
Abstract
Three fungicides and six insecticides at
recommended concentrations were
evaluated as tank mix in various
fungicide and insecticide combinations
for their efficacy against sheath blight,
brown plant-hopper and leaf folder and
to investigate their compatibility as tank
mix application for the purpose of
reducing the application cost in the
event of simultaneous occurrence of
both diseases and pests during crop
growth period. Among the different
combinations tested, pymetrozine @ 0.5
g/l in combination with hexaconazole @
2 ml/l recorded less sheath blight
incidence (9.1%) severity (14.8%) and
also lesser number of plant-hoppers
(0.5/hill) followed by pymetrozine @ 0.5
g/l + validamycin @ 2 ml/l (9.6%, 15.0%
and 0.7/hill) and combination product of
imidacloprid + ethiprole @ 0.8 g/l +
hexaconazole @ 2 ml/l (9.2%, 18.2%
and 0.4/hill) compared to untreated
check where the incidence and severity
of sheath blight was 93.6% and 81.9%
*Corresponding author: bhuvanavk2001@gmail.com
respectively. The number of plant-
hoppers in untreated check plot was
26/hill. Similarly, chlorantraniliprole @
0.3 ml/l in combination with
hexaconazole @ 2 ml/l (6.3% WE) gave
less incidence (8.3%) and severity of
sheath blight (12.8%) and also less stem
borer and lesser leaf folder damaged
leaves per hill (1.9) followed by
pymetrozine @ 0.5 g/l + validamycin @
2 ml/l (9.6%, 15.0% and 1.2/hill, 12.5%
WE). There was no reduction in the
efficacy of these insecticides and
fungicides when used as tank mix and
phytotoxicity symptoms were not
observed in any of the treatments. Thus,
all the insecticides and fungicides
combinations used in the present
investigation are compatible with each
other and can be safely combined as
tank mix for the control of rice pests
and diseases, thus, saving labour costs.
Key words: Insecticides, fungicides,
compatibility, rice, sheath blight, brown
plant-hopper and leaf folder.
65 Journal of Rice Research 2013, Vol. 6 No. 2
Rice (Oryza sativa L.) is the primary
source of food for more than half of the
world’s population. Occurrence of diseases
and insect pests together in rice demands
the necessity of fungicidal and insecticidal
application at the same place and time. In
many endemic areas, sheath blight, brown
planthopper (BPH), leaf folder and stem
borer occur at the same stage of the crop
growth. Therefore, a combined application
of effective fungicides and insecticides is a
practical necessity. In Andhra Pradesh,
Godavari delta farmers are regularly going
for 2-3 sprays in rice crop, and mixed
combinations of fungicides and
insecticides is a common practice in view
of labour shortage at these locations.
Keeping this in view, the study was
undertaken with effective fungicides like
hexaconazole, validamycin and
trifloxystrobin 25% + tebuconazole 50%
WG @ 2.0 ml/l, 2.0 ml/l and 0.4 g/l,
respectively along with the effective
insecticides like buprofezin, pymetrozine,
acephate, chlorantraniliprole, dinotefuran
and imidacloprid + ethiprole 80% WG @
1.6 ml/l, 0.5 g/l, 1.5 g/l, 0.3 ml/l, 1.8 g/l
and 0.8 g/l, respectively to find their
efficacy on sheath blight and insect pests
like BPH, leaf folder and stem borer as
well as the compatibility of the test
fungicides and insecticides.
Materials and Methods
The experiments were conducted during
the kharif 2011 and 2012 seasons in
Randomized Block Design. Three
fungicides viz., hexaconazole 5% EC,
validamycin 3% l and trifloxystrobin 25%
+ tebuconazole 50% (Nativo 75% WG) @
2 ml/l, 2 ml/l and 0.4 g/l, respectively and
six insecticides viz., buprofezin 25% SC,
pymetrozine 50% WG (Plenum), acephate
75% SP, chlorantraniliprole 18.5% SC
(Coragen), dinotefuran 20% SG (Token)
and imidacloprid + ethiprole 80% WG
(Glamor) @ 1.6 ml/l, 0.5 g/l, 1.5 g/l, 0.3
ml/l, 1.8 g/l, and 0.8 g/l, respectively, were
evaluated as tank mix of fungicide and
insecticide combinations for their efficacy
against sheath blight, brown planthopper
and leaf folder and to investigate their
compatibility as tank mix application for
the purpose of reducing the application
cost in the event of simultaneous
occurrence of both diseases and pests
during crop growth period. An untreated
control was also maintained for
comparison. Popular susceptible rice
variety, MTU-7029 (Swarna) was
transplanted during kharif 2011 and 2012
seasons in a randomized block design with
10 treatments and three replications. A
spacing of 15 x 15 cm was adopted in a
gross plot size of 9.945 sq m. A pure
culture of a virulent isolate of Rhizoctonia
66 Journal of Rice Research 2013, Vol. 6 No. 2
solani was multiplied on typha leaf bits.
Inoculation with R. solani was carried out
at maximum tillering stage
(Bhaktavatsalam et al., 1978). The
colonized typha bits were placed between
the tillers of rice plant, 5-10 cm above the
water level. The data on the disease
incidence and subsequent spread were
collected from the date of first incidence of
the disease till 30 days after final spray.
The per cent disease incidence and
severity was calculated from the data
collected from 25 hills of each treatment in
each replication as per the Standard
Evaluation System for rice (IRRI, 1996).
The disease incidence and severity data
were transformed into arc sine values
before statistical analysis. Similarly natural
incidence in these treatments was also
recorded. The grain yield was recorded
from each gross plot and calculated to
kg/ha. The data was subjected to statistical
scrutiny, and the results are furnished.
The disease and pests were first
noticed in the experimental plots at
maximum tillering stage during both
seasons. Three fungicidal and insecticidal
combination sprays were given at 15 days
interval starting from the appearance of
initial disease symptoms and pest
incidence depending upon the initial
disease symptoms/insect damage and the
subsequent pest pressure. A spray fluid of
500 L/ha was used to ensure thorough
coverage of the plants. Symptoms of
phytotoxicity, if any, were also recorded at
5 and 10 days after the imposition of the
treatments. Yield data was also recorded.
Results and Discussion
During 2011, the data revealed that among
different fungicide and insecticide
combinations used for the control of
sheath blight, planthoppers and leaf folder,
combination product of imidacloprid +
ethiprole @ 0.8 g/l + hexaconazole @ 2.0
ml/l has recorded less sheath blight
incidence (7.3%) severity (14.4%) and also
lesser number of plant-hoppers (0.1 per
hill) closely followed by trifloxystrobin
25%+ tebuconazole 50% WG @ 0.4 g/l in
combination with buprofezin @ 1.6 ml/l
(5.4%, 11.8%, 3/hill), pymetrozine @ 0.5
g/l + validamycin @ 2 ml/l (11.6%,
18.5%, 0.3/hill), pymetrozine @ 0.5 g/l +
hexaconazole @ 2 ml/l (13.8%, 19.6%,
0.6/hill) and buprofezin @ 1.6 ml/l +
hexaconazole @ 2 ml/l (5.6%, 11.9%,
6.9/hill) compared to untreated check
where the incidence and severity of sheath
blight was 87.1 and 85.7 per cent
respectively. The number of planthoppers
per hill in untreated check plot was 38.1
per hill. No significant differences were
found among treatments with respect to
leaf folder damaged leaves. In 2011, the
incidence of leaf folder was very low.
67 Journal of Rice Research 2013, Vol. 6 No. 2
While, chlorantraniliprole @ 0.3 ml/l in
combination with hexaconazole @ 2 ml/l
gave less disease incidence (12.2%) and
severity of sheath blight (18.5%) and also
lesser per cent white ears (6.3) closely
followed by acephate @ 1.5 g/l +
hexaconazole @ 2 ml/l (11.6%, 15.3%,
7.5%) compared to control where the per
cent white ears was 19.6 (Tables 1 and 2).
This confirms that the fungicides and
insecticides involved in the trial are
compatible in all fungicide insecticide
combination from the point of sheath
blight, brown planthopper and stem borer
management.
During 2012, the data presented in
Tables 1 and 2 revealed that among
different fungicide and insecticide
combinations, dinotefuran @ 1.8 g/l +
hexaconazole @ 2 ml/l combination has
recorded less sheath blight incidence
(3.8%) severity (7.8%) and also lesser
number of planthoppers (0.2/hill) closely
followed by combination of pymetrozine
@ 0.5 g/l + hexaconazole @ 2 ml/l (4.5%,
10.1% and 0.3/hill) and combination of
(imidacloprid + ethiprole) @ 0.8 g/l +
hexaconazole @ 2 ml/l (11.1%, 22.0% &
0.7/hill) compared to untreated check
where the incidence and severity of sheath
blight was cent per cent and 78.1 per cent
respectively. The number of plant-hoppers
per hill in untreated check plot was 13.9
per hill. Similarly chlorantraniliprole @
0.3 ml/l in combination with hexaconazole
@ 2 ml/l gave less disease incidence
(4.4%) and severity of sheath blight
(7.2%) and also lesser leaf folder affected
leaves per hill (3.7), reveal that the
combinations did not in any way lower the
effectiveness of the fungicides against
sheath blight and insecticides against BPH
and leaf folder. Phytotoxicity symptoms
were not observed in any of the treatments
which indicated the positive compatibility
of the evaluated chemicals.
The pooled data revealed that
among different fungicide and insecticide
combinations used for the control of
sheath blight, planthoppers and leaf folder,
combination of pymetrozine @ 0.5 g/l +
hexaconazole @ 2 ml/l has recorded less
sheath blight incidence (9.1%) severity
(14.8%) and also lesser number of plant
hoppers (0.5/hill) closely followed by
pymetrozine @ 0.5 g/l + validamycin @ 2
ml/l (9.6%, 15.0%, 0.7/hill) and
combination of imidacloprid + ethiprole @
0.8 g/l + hexaconazole @ 2 ml/l (9.2%,
18.2% and 0.4/hill), compared to untreated
check where the incidence and severity of
sheath blight was 93.6% and 81.9%,
respectively. The number of planthoppers
per hill in untreated check plot was 26per
hill. The other combinations viz.,
buprofezin @ 1.6 ml/l + trifloxystrobin
25% + tebuconazole 50% WG @ 0.4 g/l
(8.3%, 15.7%, 4.2/hill), buprofezin @ 1.6
68 Journal of Rice Research 2013, Vol. 6 No. 2
ml/l + hexaconazole @ 2 ml/l (4.8%,
9.9%, 5.5/hill) and dinotefuran @ 1.8 g/l +
hexaconazole @ 2 ml/l (19.4%, 26.8%,
9.5/hill) were also found superior over
control. Similarly chlorantraniliprole @
0.3 ml/l in combination with hexaconazole
@ 2 ml/l gave less incidence (8.3%) and
severity of sheath blight (12.8%) and also
lesser leaf folder infested leaves per hill
(1.9) closely followed by pymetrozine @
0.5 g/l + validamycin @ 2 ml/l (9.6%,
15%, 1.2/hill) compared to control where
the number of leaf folder damaged leaves
were 4.20 per hill (Tables 1 and 2). The
overall results revealed that tank mixing of
fungicides with insecticides involved in
the present studies did not reduce the
efficacy of the fungicides against rice
sheath blight and that of insecticides
against brown planthopper and leaf folder.
Hence, they are compatible with each
other for spray application to control the
rice pests. These findings are in
conformity with the findings of Singh et
al. (2010), where in it was reported that
the combination treatments of fungicides
(tricyclazole and iprobenphos) and
insecticides (indoxacarb and cartap
hydrochloride) were biologically as
effective as their individual treatments
against neck blast, leaf folder and stem
borer of rice, respectively during kharif
2006 and 2007 along with corresponding
grain yield in Taraori Basmati. Similar
reports were reported by Prajapati et al.
(2005) that insecticide triazophos (20% EC
@ 0.02%) alone or tank mixed with
fungicides carbendazim (50% WP @
0.05%) and tricyclazole (75% WP @
0.04%) was found effective in controlling
leaf folder damage as well as white backed
plant-hoppers as compared to untreated
control. Bhatnagar (2004) reported that the
combination of cartap (Padan 50% WP)
and tricyclazole (Beam 75% WP) was
effective in reducing the damage by rice
leaf folder and blast, and found to be
compatible.
Thus, the effectiveness of the six
insecticides viz., buprofezin, pymetrozine,
acephate, chlorantraniliprole, dinotefuran
and imidacloprid + ethiprole did not in any
way get hindered by mixing with the
fungicides. All the treatments with
fungicide-insecticide combinations had
significantly higher grain yield as
compared to the control.
References
Bhaktavatsalam, G., Satyanarayana, K., Reddy
A.P.K. and John, V.T. 1978. Evaluation for
sheath blight resistance in rice. International
Rice Research Newsletter 3: 9-10.
Bhatnagar, A. 2004. Compatibility of pesticides
against rice leaf folder and blast. Annals of
Plant Protection Sciences 12(1): 208-210.
IRRI. 1996. Standard Evaluation System for rice.
INGER Genetic Resource Centre, 4th Edn.
July, 1996.
Prajapati, K.S., Korat, D.M., Dodia, J.F., Pathak,
A.R. and Patel, R.C. 2005. Field Evaluation of
compatibility of insecticides and fungicides on
rice. Pesticide Research Journal 17(1): 30-32.
69 Journal of Rice Research 2013, Vol. 6 No. 2
Singh, R., Sunder, S., Dodan, D.S., Ram, L. and
Singh., R. 2010. Evaluation of scented rice
genotypes and fungicides against blast and
compatibility of pesticides used against neck
blast, stem borer and leaf folder. Indian
Phytopathology 63(2): 212-215.
70 Journal of Rice Research 2013, Vol. 6 No. 2
Table 1. Efficacy of fungicides and insecticides as tank mix against sheath blight of rice
S.
No
Treatments
Dose/L
*Disease incidence (%)
*Disease severity (%)
*Yield (kg/ha)
2011
2012
Pooled
2011
2012
Pooled
2011
2012
Pooled
T1
Buprofezin 25% SC (Applaud) +
hexaconzole 5% EC
1.6 ml +
2.0 ml
5.6
(13.6)a
4.0
(11.5)a
4.8
(12.6)a
11.9
(20.1)a
8.0
(16.1)a
9.9
(18.3)a
7859a
3776a
5817a
T2
Buprofezin + validamycin 3% L
1.6 ml +
2.0 ml
32.7
(34.9)c
22.3
(27.4)b
27.5
(31.6)d
45.4
(42.3)b
27.4
(30.7)c
36.4
(37.1)d
7196ab
3385a
5291b
T3
Buprofezin + (trifloxystrobin 25%
+ tebuconazole 50% WG (Nativo
75% WG)
1.6 ml +
0.4 g
5.4
(12.8)a
11.2
(18.7)a
8.3
(16.5)a
11.8
(20.0)a
19.5
(26.0)b
15.7
(23.3)b
7864a
3522a
5693a
T4
Pymetrozine 50% WG (Plenum) +
hexaconazole
0.5 g +
2.0 ml
13.8
(21.8)b
4.5
(12.1)a
9.1
(17.5)a
19.6
(26.1)a
10.1
(18.4)a
14.8
(22.6)ab
7615a
3759a
5687a
T5
Pymetrozine + validamycin
0.5 g +
2.0 ml
11.6
(19.7)b
7.5
(14.2)a
9.6
(17.9)b
18.5
(25.5)a
11.4
(18.3)a
15.0
(22.6)ab
7479a
3731a
5605a
T6
Acephate 75% SP + hexaconazole
1.5 g +
2.0 ml
11.6
(19.7) b
6.6
(14.4) a
9.1
(17.6)ab
15.3
(22.9)a
12.0
(20.0)ab
13.7
(21.7)a
7954a
3611a
5783a
T7
Chlorantraniliprole 18.5% SC
(Coragen) + hexaconazole
0.3 ml +
2.0 ml
12.2
(19.9) b
4.4
(10.9) a
8.3
(16.4)a
18.5
(24.9)a
7.2
(13.5)a
12.8
(20.8)a
7458a
3814a
5636a
T8
Dinotefuron 20% SG (Token) +
hexaconazole
1.8 g +
2.0 ml
34.9
(36.1)c
3.8
(11.2)a
19.4
(26.0)c
45.8
(42.6)b
7.8
(16.2)a
26.8
(31.1)c
6948bc
3817a
5383ab
T9
(Imidacloprid + ethiprole 80%
WG) (Glamor) + hexaconazole
0.8 g +
2.0 ml
7.3
(15.2)ab
11.1
(18.8)ab
9.2
(17.5)a
14.4
(21.8)a
22.0
(27.6)bc
18.2
(25.2)b
8242a
3724a
5983a
T10
Control
--
87.1
(69.0)d
100
(90.0)c
93.6
(75.3)e
85.7
(67.8)c
78.1
(62.2)d
81.9
(64.9)e
6010c
2116b
4063c
CD(P=0.05)
6.8
9.8
5.0
7.7
8.9
4.3
1180.1
988.1
635.4
CV
15.1
25.0
11.7
14.3
20.7
8.7
9.2
16.3
6.7
*Mean of three replications
Figures in the parentheses are arc sine transformed values.
71 Journal of Rice Research 2013, Vol. 6 No. 2
Table 2. Efficacy of insecticides and fungicides as tank mix against major rice pests
S.
No
Treatments
Dose/L
*BPH (No./hill)
*Leaf folder
infested leaves/hill
White
ears (%)
2011
2012
Pooled
2011
2012
Pooled
2011
T1
Buprofezin 25% SC (Applaud)+ hexaconzole
5% EC
1.6 ml +
2.0 ml
6.9
(2.5)b
4.2
(2.0)bc
5.5
(2.3)bc
0.0
(0.0)
5.5
(2.3)b
2.7
(1.7)b
14.1
(22.0)b
T2
Buprofezin + validamycin 3% L
1.6 ml +
2.0 ml
3.8
(1.9)b
5.6
(2.3)c
4.7
(2.1)b
0.1
(0.2)
4.9
(2.2)b
2.5
(1.6)b
8.5
(16.6)a
T3
Buprofezin + (trifloxystrobin 25% +
tebuconazole 50% WG (Nativo 75% WG)
1.6 ml +
0.4 g
3.0
(1.7)b
5.3
(2.1)c
4.2
(2.0)b
0.0
(0.0)
7.2
(2.7)c
3.6
(1.9)bc
20.7
(26.9)c
T4
Pymetrozine 50% WG (Plenum) + hexaconazole
5% EC
0.5 g +
2.0 ml
0.6
(0.7)a
0.3
(0.5)a
0.5
(0.7)a
0.0
(0.0)
4.5
(2.1)b
2.3
(1.5)ab
12.5
(19.4)ab
T5
Pymetrozine + validamycin 3% L
0.5 g +
2.0 ml
0.3
(0.4)a
1.1
(0.8)ab
0.7
(0.7)a
0.0
(0.0)
2.4
(1.5)a
1.2
(1.1)a
14.6
(22.4)bc
T6
Acephate 75% SP + hexaconazole 5% EC
1.5 g +
2.0 ml
28.1
(5.3)d
4.2
(2.0)bc
16.1
(4.0)d
0.1
(0.1)
4.3
(2.1)b
2.2
(1.5)ab
7.5
(15.7)a
T7
Chlorantraniliprole 18.5% SC (Coragen) +
hexaconazole 5% EC
0.3 ml +
2.0 ml
80.4
(9.0)f
20.1
(4.3)d
50.2
(7.1)f
0.0
(0.0)
3.7
(1.9)ab
1.9
(1.4)a
6.3
(13.6)a
T8
Dinotefuran 20% SG (Token) + hexaconazole
5% EC
1.8 g +
2.0 ml
18.7
(4.3)c
0.2
(0.4)a
9.5
(3.1)c
0.0
(0.0)
5.5
(2.3)b
2.7
(1.6)b
10.0
(18.2)a
T9
(Imidacloprid + ethiprole 80% WG) (Glamor) +
hexaconazole 5% EC
0.8 g +
2.0 ml
0.1
(0.2)a
0.7
(0.7)a
0.4
(0.6)a
0.0
(0.0)
6.0
(2.4)bc
3.0
(1.7)b
10.6
(18.6)a
T10
Control
--
38.1
(6.2)e
13.9
(3.7)d
26.0
(5.1)e
0.1
(0.2)
8.3
(2.8)c
4.2
(2.0)c
19.6
(26.2)c
CD(0.05)
0.8
1.2
0.8
0.5
0.4
6.7
CV
14.2
35.9
15.8
NS
12.7
12.8
23.0
*Mean of three replications.
Figures in the parentheses are arc sine transformed values.
