Response of Common Bean Cultivars to Phosphorus Application in Boloso Sore and Sodo Zuria Districts, Southern Ethiopia

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East African Journal of Sciences (2015) Volume 9 (1) 49 - 60
___________________________________________
*Corresponding author. E-mail: drjshanka2011l@gmail.com ©Haramaya University, 2015
ISSN 1992-0407
Response of Common Bean Cultivars to Phosphorus Application in Boloso Sore and Sodo
Zuria Districts, Southern Ethiopia
Dereje Shanka1*, Nigussie Dechassa2, and Setegn Gebeyehu3
1Wolaita-Sodo University, P. O. Box 238, Wolaita-Sodo, Ethiopia
2 Haramaya University, P. O. Box.138, Dire Dawa, Ethiopia
3International Rice Research Institute, Dar es Salaam, Tanzania
Abstract: Common bean (Phaseolus vulgaris L.) is an important food crop in Southern Ethiopia.
However, the productivity of the crop is constrained by low soil fertility, particularly, phosphorus
deficiency due to soil acidity. Therefore, field experiments were conducted to study the response of
the crop to phosphorus application on Nitisols at Areka Agricultural Research Centre and Kokate
research station in southern Ethiopia. The treatments consisted of three common bean cultivars
(Hawassa-Dume, Nasir, and Red-Wolaita) and five phosphorus fertilizer rates (0, 23, 46, 69, and 92 kg
P2O5 ha-1). The experiments were laid out as a randomized complete block design in a factorial
arrangement and replicated three times per treatment. Analysis of the data indicated that the main
effects of cultivar and phosphorus significantly (P < 0.05) influenced grain yield, number of pods per
plant, seed weight, leaf area index, and above-ground dry biomass yield. The interaction effects of
cultivar and phosphorus rate also significantly (P < 0.05) influenced the number of pods produced per
plant at one location (Areka). At Areka, Nasir produced a significantly higher grain yield (2504.8 kg ha-
1) than Hawassa-Dume (1951 kg ha-1) and Red-Wolita (2198 kg ha-1). However, at Kokate, the grain
yields of the three common bean cultivars were in statistical parity. Application of 69 and 23 kg P2O5
ha-1 resulted in the optimum grain yields of the crop at Areka (2498 kg ha-1) and Kokate (2219 kg ha-
1), respectively. The results of the economic analysis indicated that cultivar Nasir produced the highest
net benefit (15903 Birr ha-1). It could, thus, be concluded that cultivating Nasir at the rates of 69 P2O5
ha-1 at Areka and 23 kg P2O5 ha-1 at Kokate is most economical for smallholder farmers in the study
area.
Keywords: Biomass yield; Economic analysis; Grain yield; Phaseolus vulgaris L.
1. Introduction
Common bean is one of the most important
leguminous crops cultivated for direct human
consumption (Broughton et al., 2003). It is also among
the most important legumes in Ethiopia with multiple
uses. However, the national average yield of the crop at
farmer field is about 1500 kg ha-1 (CSA, 2013), which is
far lower than the average yield reported at research
sites that which ranges from 2500 to 3000 kg ha-1
(Frehiwot, 2010).
The low yield of the crop in the country is attributed
to declining soil fertility, rainfall variability, pest
pressure, poor agronomic practices and poor
accessibility to quality seed (Katungi et al., 2010). Soil
acidity is one of the problems constraining bean
productivity in Ethiopia (Mesfin, 2007). Previous
reports on physico-chemical properties of soils of the
study areas indicated acidity of the soils (Abayneh et al.,
2003; Abay, 2011; Abay and Tesfaye, 2011). The major
problems associated with soil acidity are toxicity of
Aluminum (Al) and Magnisium (Mn) and poor
availability of essential plant nutrients such as
phosphorus (P), Calcium (Ca), Magnesium, Nitrogen
(N), and Molybdenum(Mo) (Kochian et al., 2004). Soil
fertility problems related to soil acidity are common
features of the study areas (Abayneh et al., 2003; Abay,
2011). At low pH (<5.5), oxides and hydroxides of Iron
(Fe) and Al react with phosphate, leading to strong
adsorption and low availability of the nutrient
(Fairhurst et al., 1999). Hence, P is the major limiting
nutrient in acid soils in the study areas (Abayneh et al.,
2003; Abay, 2011).Wortmann et al. (2004) also reported
that P deficiency is a widespread problem in bean
production areas of Eastern and Southern Africa.
Common bean production is often constrained by
phosphorus deficiency in the soil since the nutrient
plays pivotal roles in nodule initiation (Kouas et al.,
2005) and N2 fixation (Kouas et al., 2005; Tiessen, 2008;
Fageria, 2009) and many other energy transfer
processes in photosynthesis and other biochemical
processes (Fageria, 2009). Furthermore, in Ethiopia,
bean production is taking place on smallholder farms
with little input (Ferris and Kaganzi, 2008). Under such
production system, phosphorus becomes a serious
yield-limiting factor (Lunze et al., 2012).
Application of phosphate fertilizers has been
suggested to enhance availability of soil P and crop
yields (Vance et al., 2003). One of the strategies to
improve bean yield on P deficient soils is application of
adequate levels of P (Fageria, 2002). Furthermore,
various research findings revealed significant
increments in the grain yields of legumes including
beans in response to P fertilizer application (Birhanu,

Dereje et al. East African Journal of Sciences Volume 9 (1) 49 - 60
50
2006; Magani and Kuchinda, 2009). Previous research
done on acid soils in Ethiopia revealed significant
increases in yield of leagumes including common bean
as a result of P fertilizer application (Getachew et al.,
2005; Gifole et al., 2011). The grain yield of common
bean was significantly influenced by the application of
P fertilizer on acidic Nitisolsof Areka (Gifole et al.,
2011).
The grain yield of common bean obtained by
smallholder farmers in Southern Ethiopia is low, which
is about 1140 kg ha-1 (CSA, 2013). It is hypothesized
that the low yield of the crop in the region is due to low
availability of P in the soil and its consequent low
uptake by crop plants. However, no research has been
done in the study area to elucidate this problem. This
research was, therefore, conducted to investigate the
response of three common bean cultivars to
phosphorus application.
2. Materials and Methods
2.1. General Description of the Study Areas
Field experiments were conducted in 2014 at Areka
Agricultural Research Centre and Kokate Research
Station, in Boloso Sore and Sodo Zuria districts,
respectively, in Southern Ethiopia. Areka Agricultural
Research Centre located between 703'25'' N latitude and
37040'52'' E longitude. The altitude of Areka reaches up
to 2230 meters above sea level (Abayneh et al., 2003).
The major soil type of the center is Haplic Alisol
(FAO, 2006), which is very deep and clayey in texture
(Abayneh et al., 2003). On the other hand, the Kokate
research center is situated in Wolaita zone, and is
located at 6052'42'' N and 37048' 25'' E at an altitude of
2156 meters above sea level.
2.2. Soil Analysis
Samples were randomly collected using an auger to the
soil depth of 30 cm in a zigzag pattern from the
experimental field only at planting. Soil texture was
determined by the Bouyoucas hydrometer method
(Bouyoucos, 1951). Available P was determined by
Bray I method using ammonium fluoride as an
extractant and measuring the concentration of the
nutrient at 880 nm (Bray and Kurtz, 1945). Soil organic
carbon was determined by the wet digestion method
(Walkley and Black, 1934). Total N was determined by
the wet oxidation procedure of the Kjeldhal method
(Bremner, 1995). Soil pH in water was determined
potentometrically in a supernatant suspension of 1:2.5
soils: water ratio using a combined glass electrode pH
meter (Chopra and Kanwar, 1976). Exchangeable
potassium was estimated by the ammonium acetate
(1M NH OAc at pH 7) extraction method as described
by Rowell (1994).
2.3. Physico-chemical Properties of Soils of the
Experimental Sites
The physico-chemical properties of the experimental
soils determined before sowing of the common bean
crop at the two locations are shown in Table 1.
Table 1. Physico-chemical properties of soils of the study area
According to the rating of Landon (1991) and Hazelton
and Murphy (2007), the pH of the soil is very strongly
acidic at both locations. Similarly, according to the
rating of Cottenie (1980), the available phosphorus
content of the soil is low. The soils of both locations
are sandy clay loam. This shows that the soil has
limitation in terms of these two chemical properties for
crop production. Therefore, managing soil pH and
phosphorus availability is important for enhancing
plant growth and production in the study area.
2.4. Meteorological Conditions of the Study Areas
In 2014, the rainfall was good in amount compared to
the previous twelve years at both locations. The rainfall
data showed the area received 1484 and 123.7 mm total
annual and mean monthly rainfall, respectively in 2014
(Figure 1). Similarly, at Kokate, despite uneven
distribution, the rainfall was higher in amount
compared to the past twelve years. The total annual and
mean monthly rainfall amounts received during 2014
were1552.1 and 158.6 mm, respectively (Figure 1).
Beans are well adapted to medium rainfall in tropical
and temperate regions. Excessive rain causes flower
drop (Fageria, 2011). A total rainfall of 350 to 500 mm
during the growing season combined with low relative
humidity is ideal for common bean growth (Salcedo,
2008). Hence, the rainfall received during the growing
season at both locations was adequate for common
bean growth.
Location
pH
(1:25 Soil:
H20)
Total N
(%)
OC
(%)
Available
P (mg kg-1)
Exchangeable
K(cmol(+)kg-1)
Soil Texture
Sand
(%)
Clay
(%)
Silt
(%)
Kokate
4.4
0.15
1.7
8.9
4.69
63
18
20
Areka
4.6
0.33
3.9
7.0
3.98
62
11
27

Dereje et al. Response of Common Bean Cultivars to Phosphorus Application
51
Figure 1. Monthly Rainfall and Monthly maximum and minimum temperatures for Areka and Kakate in 2014.
Source: Areka Research Center, Areka and National Meteorological Agency of Ethiopia Hawassa branch, Hawassa.
Temperature is another climatic variable that affects
crop yield. In 2014, the average monthly temperature in
the study area ranged from 18.8 to 21.9 0 C at Kokate
and 18.3 to 19.3 0 C at Areka. Further, during the
growing season, average monthly temperature varied
from 18.8 to 21.6 0 C at Kokate and 18.30 to 21.7 C at
Areka (Figure 1). The crop grows well at temperatures
ranging from 15 to 27°C and will withstand
temperatures up to 29.5°C (Salcedo, 2008). The
minimum and maximum tempratures atboth locations
lies in the temprature range suitable for common bean
growth (Figure 1).
2.5. Treatments and Experimental Design
The treatments consisted of three common bean
cultivars (Hawassa-Dume, Nasir, and Red-Wolaita) and
five phosphorus rates (0, 23, 46, 69 and 92 kg P2O5 ha-
1). The experiment was laid out as a Randomized
Complete Block Design (RCBD) in a factorial
arrangement and replicated three times per treatment.
Each treatment was assigned to the plots randomly.
The size of each experimental plot was 3.0 m x 2.8 m.
2.6. Experiment procedures
The experimental field was ploughed by a tractor three
times prior to planting at both locations. The planting
was done on 27 and 29 2014 at Areka and Kokate,
respectively. The phosphorus fertilizer used was triple
super phosphate [Ca (H2PO4)2; 48.1% P2O5], which
was applied in band at planting time based on the
specific rates required. Nitrogen was applied at the rate
of 18 kg N ha-1 in the form of urea [CO (NH2)2; 46%
N], at the active stage of vegetative growth before
flowering (MORAD, 2008). Weeding was done as
required. Similarly, other crop management practices
such as pest and disease control was done for all
experimental plots. The outer most one row on each
side of a plot was left as a boarder row. Two rows at
one side and the other at the opposite side of the plots
next to the boarder rows were used for destructive
sampling. The remaining three rows were used for yield
data measurement. The crop was harvested on 6 and 7
July 2014, respectively at Areka and Kokate.
2.7. Data Collection and Measurement
Leaf area was measured using a leaf area meter from
five randomly selected plants from rows left for
destructive sampling. Leaf area index (LAI) was
calculated as the ratio of the total leaf area per plant to
the area occupied by the plant. Days to flowering were
recorded as the number of days from seedling
emergence to the time when 50% of the plants in the
net plot area had the first flower. Days to maturity were
taken as the number of days from emergence to the
days when 95% of the plants grown in the net plot area
were ready for harvest. 100 seed weight was determined
from 100 randomly taken seeds from plants grown in
the net plot area. Number of pods per plant and
number of seeds per pod were determined from 5
randomly selected plants in the net plot areas at
harvest. Aboveground dry biomass yield was
determined from the aboveground part of five
randomly chosen plants that were cut at the ground
level from the net plot area at maturity and by sun-
drying the fresh aboveground biomass. Grain yield was
taken from whole plants harvested from the net plot
area, excluding plants grown in border rows at harvest.
Grain yield was determined by weighing the beans
using a sensitive balance and adjusted to 10 % moisture
level.
2.8. Statistical Analysis
The data of the two locations were tested for
homogeneity of variance using F-test (Gomez and
Gomez, 1984). All data were subjected to analysis of
variance using SAS version 8, Statistical software (SAS,
2004). Significant treatment mean differences were
separated using the LSD test at 0.05 probability level.
2.9. Economic Analysis
Partial budget analysis to evaluate the economic
viability of the technologies was performed following
the procedures described by CIMMYT (1988).Only the
costs that vary were considered for analysis. A

Dereje et al. East African Journal of Sciences Volume 9 (1) 49 - 60
52
treatment that is non-dominated and having a MRR of
greater or equal to 100% and the highest net benefit is
said to be economically profitable (CIMMYT, 1988).
3. Results and Discussion
3.1. Effect on Growth Parameters
Leaf area index
Leaf area index is an important trait, which contributes
for increased crop production (Fujita et al., 1999). Leaf
area index responded to the main effects of
phosphorus and cultivar at both locations (Table 2).
Table 2. Main effects of cultivar and phosphorus fertilizer rate on leaf area index at Areka and Kokate research centres
in 2014 main growing season
Where, LSD = Least significant difference. Means followed by the same letter are not significantly different at 5% level of significance.
At Areka, significantly higher leaf area index was
recorded for Red-Wolaita than the other cultivars.
However, at Kokate, Nasir had significantly higher leaf
area index than Red-Wolaita and Hawassa-Dume. On
the other hand, Nasir and Hawassa-Dume at Areka and
Red Wolaita and Hawassa-Dume at Kokate had leaf
area indices that were in statistical parity (Table 2).
Corroborating this result, Butraa, (2009) observed a
highly significant effect (P = 0.001) of common bean
genotype on leaf area index. Similarly, Fujita et al.
(1999) reported significant variations in the leaf area
index pigeon pea.
The optimum leaf area index at both locations was
recorded when P was applied at the rate of 46 kg P2O5
ha-1. As a result, compared to the control treatment,
increasing the P rate up-to 46 kg P2O5 ha-1 resulted in
36 and 18% increases in leaf area index at Areka and
Kokate, respectively (Table 2). Hence, the significant
effect of P application on leaf area index might be due
to unique bonding properties of P that make it critical
in nucleotide-based metabolic processes and direct
involvement of the nutrient in generation of high-
energy compound such as ATP, which is essential for
establishing enzymatic machinery for energy storage
and transfer (Sinclai and Vadez, 1999), thereby playing
a pivotal role in the synthesis of cellulose and
hemicelluloses in leaves (Fujita et al., 1999). In
agreement with the findings of the present study,
different workers also observed significant increases in
leaf area index of different crops including common
bean due to phosphorus application (Magani and
Kuchinda, 2009; Olivera et al., 2004; Meseret and Amin,
2014). For instance, Meseret and Amin, (2014) reported
significant increases in common bean leaf area in
response to P application at Arbaminch, Southern
Ethiopia. However, the results of this study are in
contrast to the findings of Sulieman and Hago (2009),
who reported a non-significant effect of phosphorus
application on leaf area index of common bean after 10
weeks, which was indicated to be due to heavy clay
alkaline nature of the soil used for growing the crop.
Aboveground Dry Biomass
Three-factor interaction effect of location × cultivar ×
phosphorus was significant for aboveground dry
biomass yield (Table 3). Means of aboveground dry
biomass yield of the common bean cultivars varied
across the locations when different rates of phosphorus
were applied (Table 3). The maximum biomass was
produced by Red-Wolaita from plots that received 92
kg P2O5 ha-1 at Kokate, which was in statistical parity
with Nasir grown on plots that received 69 and 92 kg
P2O5 ha-1 at the same location, whilst the minimum dry
biomass was produced by Hawassa-Dume at Areka,
when grown on plot receiving no phosphorus
application.
Cultivar
Leaf area index
Areka
Kokate
Mean
Hawassa-Dume
2.9b
3.2b
3.027b
Nasir
3.1b
3.7a
3.413a
Red-Wolaita
3.6a
3.1b
3.287a
F-value
Cultivar
LSD
***
0.39
***
0.25
***
0.24
Phosphorus
rate (P2O5 kg-1)
0
2.5b
2.9c
2.73b
23
2.6b
3.1bc
2.77b
46
3.4a
3.4ab
3.39a
69
3.8a
3.5a
3.63a
92
3.8a
3.6a
3.68a
F-value
P
CV (%)
LSD (0.05%)=
***
18.84
0.58
***
9.97
0.32
***
9.95
0.31

Dereje et al. Response of Common Bean Cultivars to Phosphorus Application
53
The variation in aboveground dry biomass yield of
the cultivars across P levels and location might be
attributed to the genotypic variations of the cultivars in
leaf area index, which may affect photosynthesis and
photo-assimilate synthesis (Fujita et al., 1999) and slight
variations in inherent soil fertility status of the soils of
the two locations. Consistent with these results, other
researchers also reported significant increases in
biomass yield in response to P application (Gifole et al.,
2011; Fageria et al., 2010, 2012). In a similar study,
Mourice and Tryphone, (2012) reported that common
bean cultivars produced different dry matter at
different phosphorus levels. In other words, the
cultivars have different fertilizer and environmental
requirements.
Table 3. Mean aboveground biomass yield as influenced by the interaction of phosphorus, location, and cultivar in 2014
main growing season.
Phosphorus
(kg P2O5 ha-1)
Kokate
Areka
Aboveground dry biomass yield (kg ha-1)
Hawassa-
Dume
Nasir
Red-
Wolaita
Hawassa-
Dume
Nasir
Red-
Wolaita
0
4854.2mno
4817.2mnop
4342.6nop
3890.5p
4460.6nop
5291.3lmn
23
7421.7def
5656.6jklm
5623.6kml
4184.7op
7049.8efgh
6160.8hijkl
46
5999.8ijkl
6756.9fghi
6403.4ghijk
6721.5fghi
8125.1cde
6676.4fghi
69
6784.9fghi
8807.3ab
7823.3cde
7013.6efgh
8162.5bcd
6598.2fghij
92
6932.9efghi
8468.4abc
9285.4a
7830.1cde
7360.1defg
7536.7cdef
LSD (0.05)=
962.59
Where, LSD = Least significant difference. Means followed by the same letter are not significantly different at 5% level of significance.
However, application of P beyond 69 kg P2O5 ha-1 did
not result in significant increases in aboveground dry
biomass yield of Nasir. Similarly, at Areka, significant
increase in aboveground dry biomass yield was not
observed beyond 69 kg P2O5 ha-1 for this cultivar
3.2. Effect on Yield Components Number of Pods
per Plant
Number of pods per plant was influenced significantly
by the interaction of cultivar and phosphorus fertilizer
rate only at Kokate (Table 4). The results showed that
Red-Wolaita produced the highest number of pods per
plant in response to the application of 92 kg P2O5 ha-1,
which was in statistical parity with the number of pods
produced by Red Wolaita and Nasir at the rates of 69
kg P2O5 ha-1and Hawassa-Dumeat at 69 and 92 kg
P2O5 ha-1 at Kokate. Also at nil P rate, Red-Wolaita
produced the highest number of pods per plant whilst
Hawassa-Dume produced the lowest number of pods
per plant, indicating this cultivar is more sensitive to P
deficiency than the other cultivars. On the other hand,
at 69 kg P2O5 ha-1, all cultivars produced statistically
equal numbers of pods per plant, suggesting that the
three cultivars are responsive equally to high rates of P
application. On the other hand, the lowest number of
pods per plant was recorded for Hawassa-Dume. At
Areka, cultivar Nasir produced a significantly higher
number of pods per plant than Hawassa-Dume and
Red Woliata (Table 7). The variation in the number of
pods per plant might be related to the genotypic
variation of the cultivars. In accord with the results of
the present study, different authors reported significant
variations in the number of pods per plant for common
bean (Fageria et al., 2010; Mourice and Tryphone, 2012)
and soybean (Mahamood et al., 2009) genotypes.

Dereje et al. East African Journal of Sciences Volume 9 (1) 49 - 60
54
Table 4. Number of pods per plant as influenced by the interaction effect of cultivar and phosphorus at Kokate,
Southern Ethiopia, in 2014 growing season
Where, CV = Coefficient of variance; LSD = Least significant difference. Means followed by the same letter are not significantly different at
5% level of significance.
In general, the number of pods per plant significantly
increased in response to increasing the rate of
phosphorus up-to the highest rate (Tables 4 and 9). At
Areka, application of 46 kg P2O5 ha-1 produced the
optimum number of pods per plant (Table 9). In line
with this result, different authors reported significant
variations in the number of pods per plant for different
crops including common bean due to P applications
(Ali et al., 2002; Meseret and Amin, 2014). In contrast,
Malik et al. (2002) reported a non-significant increase in
the number of pods produced per plant by rice bean.
Seeds per pod
Common bean cultivars produced significantly
different numbers of seeds per pod when grown at
different P rates; however in most cases, the cultivars
produced statistically equal number of seeds per pod
across the P rates (Table 5). This indicates that the trait
is mainly controlled genetically rather than the
variations in external environment. Hence, in
agreement with this finding, Mesfin et al. (2014)
reported significant common bean cultivars×
phosphorus interaction effects on the number of seeds
per pod in Dolla (Bolosso Sore district) and Gununo.
However, the same authors reported significantly
higher number of seeds per pod for some of the
cultivars tested.
Table 5. Mean number of seeds per pod as influenced by interaction effect of cultivars and phosphorus in 2014,
Southern Ethiopia.
Where, LSD = Least significant difference. Means followed by the same letter are not significantly different at 5% level of significance.
Averaged across the P rates, Red-Wolaita
produced the highest number of seeds per pod
(Table 5). On the other hand, the minimum
number of seeds per pod was produced by Nasir.
Consistent with the results of this study, Mourice
and Tryphonne (2012) also observed significant
variations in number of seeds per pod among
common bean genotypes. The variation in number
of seeds per pod could be attributed to the
variation in the size of seeds of the cultivars. In
other words, a higher or relatively better number
of seeds per pod at lower P level might be a
compensation for small seed size at lower P levels.
On the other hand, absence of significant variation
among the cultivars across the P levels indicate
that this trait is mainly controlled genetically rather
than by application of phosphorus fertilizer as
pointed out by other workers (Mourice and
Tryphonne, 2012).
Phosphorus
(kg P2O5 ha-1)
Cultivar
Hawassa-Dume Nasir Red-Wolaita
0 8.10h 10.13egf 12.90cd
23 8.56hg 11.03def 12.66cd
46 9.06hgf 11.30de 13.40bc
69 14.60abc 14.20abc 15.33ab
92 15.80a 13.00cd 16.1a
F-value
C×P ***
CV (%) 9.94
LSD (0.05) = 1.987
Phosphorus
(kg P2O5 ha-1 )
Cultivars
Hawassa-dume
Nasir
Red-
Wolaita
0
4.8bc
4.5bcd
5.7a
23
4.7bcd
4.8bcd
4.7bcd
46
4.4cd
4.5bcd
5.0bcd
69
4.5bcd
4.7bcd
4.6bcd
92
5.1ab
4.2d
4.8bcd
Mean
4.7
4.54
4.96
LSD (0.05)=
0.64

Dereje et al. Response of Common Bean Cultivars to Phosphorus Application
55
3.3 Effect on Plant Penology and Seed Weight
Days to maturity were significantly influenced by
the main effects of location and phosphorus
application. Increasing phosphorus rate hastened
days to maturity (Table 6).
The early maturity of the crop due to P
application might be related to the metabolic role
phosphorus plays in hastening growth and
physiological processes. Consistent with this result,
Gefole et al. (2011) reported that phosphorus
application significantly reduced days to maturity.
Table 6. Main effects of location, cultivar, and phosphorus fertilizer rate on mean seed weight and days to maturity of
common bean at Areka and Kokate in 2014 growing season.
Location
Seed weight (g)
Days to maturity
Kokate
26.7a
90.8a
Areka
25.9b
89.3b
F-test
Location
***
***
LSD(0.05)=
0.53
0.83
Cultivar
Hawassa-Dume
26.3
90.7
Nasir
26.6
89.6
Red-Wolaita
26.0
89.8
F-test
Cultivar
ns
ns
LSD (0.05) =
ns
ns
Phosphorus (kg P2O5 ha-1)
0
25.1c
91.4a
23
25.2c
91.2a
46
26.6b
90.7a
69
27.2ab
88.6b
92
27.6a
88.2b
F-test
Phosphorus
***
***
CV (%)
LSD (0.05)=
4.76
0.84
2.18
1.31
Where CV = Coefficient of variance; LSD = Least significant difference. Means followed by the same letter are not significantly different at
5% level of significance.
Hundred seed weight
Hundred-seed weight varied due to the main effects of
location and phosphorus application (Table 6). The
highest seed weight was recorded for Kokate whilst the
lowest seed weight was recorded for Areka. The
variation in hundred seed weight between the two
locations might be attributed to the slight variation in
inherent soil fertility status of the two locations (Table
1). Similarly, a significant increase in hundred seed
weight compared to the control was observed only when
the P rate was increased up to 46 kg P2O5 ha-1. The
increase in hundred seed weight as a result of increased
P application may be attributed to important roles the
nutrient play in regenerative growth of the crop (Zafar et
al., 2013), leading to increased seed size (Fageria et al.,
2009), which in turn may improve hundred seed weight.
In a similar study, Amare et al. (2014) observed
significant variations in thousand seed weights of
common bean as a result of phosphorus application.
3.4. Effect on Grain Yield
Grain yield was significantly influenced by the main
effect of cultivar only at Areka whilst phosphorus
application had a significant effect at both locations on
this parameter (Table 7).
At Areka, common bean cultivar, namely, Nasir
produced a significantly higher grain yield than the other
cultivars. The grain yield produced by Nasir exceeded
that produced by Hawassa-Dume and Red-Woliata by
nearly 28% and 14 %, respectively (Table 7). However,
Hawassa-Dume and Red-Wolaita produced grain yields
that were in statistical parity. Similarly, at Kokate, the
highest and the lowest grain yields were produced by
Red-Wolaita and Hawassa-Dume, respectively. Red-
Wolaita produced 13% higher grain yields compared to
Hawassa-Dume (Table 7).
Further, averaged across the two locations, no
significant differences existed between the common
bean cultivars, namely, Nasir and Red Wolaita. However,
the grain yields of the aforementioned two common
bean cultivars significantly exceeded that of Hawassa-
Dume. Grain yield in common bean is related to yield

Dereje et al. East African Journal of Sciences Volume 9 (1) 49 - 60
56
attributing traits such as number of pods per plant and
seed weight (Fageria et al., 2009). Hence, the variation in
grain yield among common bean cultivars might be
related to the variations observed among the cultivars in
the number of pods per plant and seed weight (Table 7).
For instance, the high yielding cultivars Nasir and Red-
Wolaita produced heavier seeds compared to the low
yielding cultivar, Hawassa-Dume (Table 6).
Differences in grain yield among the common bean
cultivars also might be related to the genotypic variations
for P use efficiency (Fageria and Costa, 2000; Fageria et
al., 2010), which may arise from variation in P
acquisition (Lynch, 1995) and translocation and use of
absorbed P for grain formation (Horst et al., 1993; Shen
et al., 2011) in common bean. Hence, the cultivars which
produced higher grain yield might have either better
ability to absorb the applied P from the soil solution or
translocate and use it for grain formation than the low
yielding cultivar. In agreement with the findings of this
study, several researchers observed significant variations
in grain yield for different crop genotypes, including
common bean (Korkmaz, 2010; Fageria et al., 2010,
2012; Mourice and Tryphone, 2012; Gobeze and Legese,
2015).
Table 7. Main effects of cultivar and phosphorus fertilizer rate on grain yield and number of pods per plant at Areka and
Kokate in 2014 growing season
Where, CV = Coefficient of variance; LSD = Least significant difference. Means followed by the same letter are not significantly different at
5% level of significance.
At Areka, increasing the rate of P from nil to 23 kg P2O5
ha-1 did not increase grain yield. Significant increase in
grain yield of the crop was observed over the control
treatment. However, at this location, the optimum grain
yield was already obtained at 69 kg P2O5 ha-1. This
indicated that increasing the rate of phosphorus beyond
69 kg P2O5 ha-1 resulted in a non-significant yield
increment (Table 7). Thus, increasing the rate of
phosphorus from nil to 69 kg P2O5 ha-1 increased grain
yield by nearly 47% compared to the control treatment.
This result corroborates the finding of Gifole et al.
(2011), who reported that increasing the rate of
phosphorus application increased grain yield of common
bean at Areka.
At Kokate, the pattern of response of the grain yield
of common bean to the increasing rate of the P fertilizer
was similar with that observed at Areka (Table 7).
However, although the maximum grain yield was
obtained at the highest rate of phosphorus (92 kg P2O5
ha-1), the optimum grain yield was attained already at 23
kg P2O5 ha-1, indicating that there was no need to
increase the rate of the fertilizer beyond this rate at this
location for enhancing the grain yield of the crop.
Hence, increasing the rate of phosphorus application
from nil to 23 kg P2O5 ha-1 resulted in about 25%
increase in grain yield of the crop at this location (Table
7). The grain yield obtained at nil rate of phosphorus
application at Kokate was higher than the one obtained
at Areka at the same rate of the fertilizer by about 11%.
This difference and the lack of response in grain yield to
higher application rates of phosphorus than 23 kg P2O5
ha-1 at Kokate indicates that the soil of the latter is in a
much better status in P content and availability for better
growth and productivity of the crop than the soil of the
former (Table 1).
The results of this study showed increased grain yields
in response to the increasing the rate of P application.
The increase in grain yield might be attributed to overall
Grain yield Number of pods per plant
Cultivar
Areka
Kokate
Mean
Areka
Kokate Mean
Hawassa-Dume
1951.2b
2178.3
2064.8b
12.56b
11.2b 11.9b
Nasir
2504.8a
2352.8
2428.8a
14.78a
11.9b 13.4a
Red-Wolaita
2197.8b
2467.1
2332.5a
12.76b
14.1a 13.4a
Mean
2217.9
2332.7
F-test
Cultivar
LSD (0.05%)
***
257.8
ns
ns
***
206.0
*
1.98
*** ***
0.93 1.02
Phosphorus
(kg P2O5 ha-1)
0
1695.7d
1889.3b
1792.5d
11.01b
10.4b 10.7c
23
1994.1cd
2218.9ab
2106.5c
11.51b
10.8b 11.2c
46
2201.5bc
2360.4a
2280.9bc
14.2a
11.3b 12.8b
69
2498.3ab
2546.2a
2522.3ab
15.0a
14.7a 14.9a
92
2699.8a
2648.8a
2674.3a
15.06a
15.0a 15.0a
Mean
2217.9
2332.7
Phosphorus
C*V
CV
LSD (0.05%) =
***
ns
15.5
332.8
**
ns
19.34
435.8
***
ns
12.11
266.0
***
ns
19.8
2.6
*** ***
*** ns
9.93 10.56
1.2 1.3

Dereje et al. Response of Common Bean Cultivars to Phosphorus Application
57
improvement in growth attributes such as leaf area index
and aboveground dry biomass yield, thereby increasing
yield attributing traits such as number of pods per plant,
hundred seed weight upon partitioning, which also
showed an increasing trend as a result of P application.
Different workers also reported association of increase
in these yield attributing traits with increase in grain yield
(Ali et al., 2002; Sofi et al., 2011; Amare et al.,
2014).Consistent with the results of this study, other
workers reported significant increases in the grain yields
of common bean in response to phosphorus application
under field and greenhouse conditions (Vesterager et al.,
2006; Gifole et al., 2011; Gobeze and Legese, 2015;). In
contrast, Tolera et al. (2005) reported a non-significant
effect of P application on grain yield of climbing bean
intercropped with maize at Bako, Western Oromia
region of Ethiopia on an acid soil.
3.5. Economic Analysis
Grain yield was significantly influenced by the main
effects of phosphorus fertilizer application at both
locations (Tables 7). However, the effect of cultivar was
significant only at Areka.
Table 8. Results of the economic analysis for common bean cultivars and P at Areka and Kokate in 2014 growing
season.
Where, ETB = Ethiopian Birr (currency); TCV = Total cost that vary; NB = Net benefit; MRR = Marginal rate of return; Price for
phosphorus Fertilizer = 12.34 ETB kg-1, Price for common bean cultivars Red-Wolaita = 7.0 ETB kg-1, Nasir = 8.05 ETB kg-1,
Hawassa-Dume = 8.05 ETB kg-1, average price for common bean = 7.7 ETB kg-1.
The economic analysis for Areka indicated that planting
of the cultivar Nasir produced the highest net benefit
(15903.1 Birr ha-1) with acceptable marginal rate of
return compared to other cultivars (Tables 8). Further,
compared to other phosphorus rates, the highest net
benefit with acceptable marginal rate of return was
obtained when phosphorus was applied at the rates of
69 and 23 kg P2O5 ha-1 at Areka and Kokate,
respectively (Tables 7).
4. Conclusion
The results of this study have demonstrated that
phosphorus application improved the performance of
the common bean cultivars at both locations. However,
the amounts of phosphorus fertilizer required for
production of optimum grain yields of the crop at the
two locations varied. Thus, application of phosphorus at
the rates of 69 kg P2O5 ha-1 at Areka and 23 kg P2O5 ha-1
at Kokate resulted in optimum grain yields of the crop.
Nasir was found to be the most productive cultivar for
economical production in the study areas.
5. Acknowledgements
The authors thank the Federal Ministry of Education of
Ethiopia for financing this work as part of PhD
research. Haramaya University is acknowledged for
facilitating the PhD study, and Areka Research Centre
and Hawassa University for facilitating the field work.
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