International Journal of Plant Research 2014, 4(3): 63-71
DOI: 10.5923/j.plant.20140403.01
Character Expression and Differences in Yield Potential
of Ten Genotypes of Cowpea (Vigna unguiculata L. Walp)
Ajayi A. T.1,*, Adekola M. O.1, Taiwo B. H.2, Azuh V. O.3
1
Department of Plant Science and Biotechnology, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria
2
Department of Agriculture, University of Reading, Berkshire, United Kingdom
3
Department of Botany, University of Ibadan, Ibadan, Nigeria
Abstract Cowpea, an important grain legume in the tropics and sub-tropics; serves as a source of protein in the diets of
the people with tremendous ability to fix atmospheric nitrogen for soil improvement. Ten (10) genotypes of cowpea were
grown during the rainy season of 2013 to study the interrelationship among quantitative traits. Estimates of phenotypic and
genotypic coefficients of variation, broad sense heritability, and genetic advance as percent of mean and correlations were
performed on 20 quantitative traits. The experiment was laid out in a randomized complete block design (RCBD) with three
replications at the Research Field of the Department of Plant Science and Biotechnology, Adekunle Ajasin University,
Akungba-Akoko, Ondo State, Nigeria. Genotypes differed significantly at (P ≤ 0.01) for all traits studied which showed the
existence of sufficient genetic variability among the tested genotypes. High broad sense heritability values for all traits
studied except for plant height (moderate) shows that these traits are less influenced by environmental effects; which make
them effectively transmitted to the progeny. The high positive genotypic and phenotypic correlations between numbers of
pods per plant, number of seeds per pod, number of seeds per plant and seed weight indicates that selection for these will
result in increase in yield.
Keywords Broad sense heritability, Genetic advance as percent of mean, Cowpea, Genotypic coefficient of variation,
Phenotypic coefficient of variation
1. Introduction
Cowpea, a grain legume, very high in protein content (20 –
25%), has been an important crop grown in the tropical and
sub-tropical regions of the world; where it serves as a source
of protein for both urban and rural populations ([1]; [2]). It is
widely distributed in sub-Saharan Africa, Europe and United
States of America [3]. It has a very good ability to improve
soils as a consequence of its potential to fix atmospheric
nitrogen ([4]; [5]; [2]). Within two decades, IITA made
significant advances on cowpea seeds improvement, hence
production in Nigeria showed a significant improvement of
about 44% and 40% increase in area planted and yield
respectively from 1961 to 1995 ([6]; [7]), in fact over
850,000 tons of cowpea is produced annually in Nigeria [8].
Still the production and release of improved cowpea varieties
have been slow especially in Nigeria, especially in the humid
regions while highest yields have been obtained in drier
regions of the country [9]. However, the claim by [10] that
selection of appropriate genotype for environmental stress
* Corresponding author:
[email protected] (Ajayi A. T.)
Published online at http://journal.sapub.org/plant
Copyright © 2014 Scientific & Academic Publishing. All Rights Reserved
was limited by inadequate screening techniques and the lack
of genotypes showing clear differences in environmental
stress was also true for cowpea in Nigeria and still applicable
today.
Before embarking on any form of crop improvement
programme, in any crop species, a thorough knowledge
concerning the amount of genetic variability existing in such
crop species for various traits is essential [11]. Assessment of
the variations in yield determining quantitative traits of the
crop is a pre-requisite in breeding to improve yield [12]. In
crop species, phenotypes are controlled mainly by genetic
make-up of such crops coupled with the kinds of
environment where they are being grown as well as the
interactions between the genotypes and the environments. It
is necessary therefore, to partition the observed phenotypic
variability into heritable and non-heritable components with
suitable parameters such as phenotypic and genotypic
co-efficient of variation, heritability and genetic advance.
Thus, knowledge of genetic variability, heritability and
genetic advance in cowpea is essential for a breeder in
selecting best genotypes for improvement. Estimates of
genetic parameters provide an indication of the relative
importance of the various types of genes effects, affecting
the total variation of a plant character. In fact, genotypic and
phenotypic coefficients of variation and heritability
64
Ajayi A. T. et al.: Character Expression and Differences in Yield Potential
of Ten Genotypes of Cowpea (Vigna unguiculata L. Walp)
accompanied with genetic advance are very important
parameters in improving traits [13].
The importance of selecting and evaluating varieties for
quantitative traits and yield capacity in any breeding
programme has been previously pointed out by [14] and
assessment of genetic diversity in cowpea genotypes would
facilitate development of cultivars for adaptation to specific
production constraints. Several workers ([15]; [16]; [17];
[18]; [19]; [20]; [21]) have calculated Genotypic and
phenotypic components of variance, heritability and genetic
advance for different yield characters in cowpea and other
crops and have revealed that selection was effective for a
population with broad genetic variability and character with
high heritability.
Yield, being a complex character and controlled by a large
number of contributing characters and their interactions,
which in turn are governed by a few numbers of genes, also
is influenced to a great extent by environment. Correlation of
characters also helps to simultaneously select for more than
one character of importance at a time. Still, the total
correlation is insufficient to explain the true association
between characters, as the yield is dependent on many
components characters. It would be more desirable to
consider the relative magnitude of various characters in order
to have a clearer picture of yield components for effective
selection programme [11].
The objectives of the present research were to study the
level of genetic variability for yield and it components and
correlation of characters in 10 genotypes of cowpea from
IITA.
time.
2.1. Data Collection and Analysis
Data on emergence percentage (10 days after planting),
morphological and agronomical characters (at eight weeks
after planting and at maturity respectively) were collected
from 10 randomly selected plants and their means were
recorded for all observations according to International
Board for Plant Genetic Resources (IBPGR), cowpea
descriptors [22].
Analysis of variance was estimated according to the
procedure of [23].
Genotypic and phenotypic coefficients were estimated
according to [24] and [25] as:
VG = MSG – MSE/r……………….eqn. 1
VP = VG + MSE…………………...eqn. 2
Where, MSG, MSE and r, are: mean square genotypes,
mean square error and number of replicates respectively.
The phenotypic coefficient of variation (PCV %) and
Genotypic coefficient of variation (GCV %) were estimated
by method of [26] and [14] as:
PCV = √Vp X 100/ ͞X........................eqn. 3
GCV = √Vg X 100/ ͞X…………….....eqn. 4
Where, VP, VG and ͞X are phenotypic variance, genotypic
variance and grand mean respectively for traits under
consideration, and were classified according to [27] as
follows:
0 – 10% = low; 10 – 20% = moderate;
20% = high.
2
2. Materials and Methods
The experiment was conducted at the Research Field of
the Department of Plant Science and Biotechnology,
Adekunle Ajasin University, Akungba-Akoko (latitude 7.20
N, longitude 5.440 E, Altitude 423M above sea level), Ondo
State Nigeria, between April and July, 2013. 10 cowpea
genotypes used in this study were collected from
International Institute of Tropical Agriculture (IITA) Ibadan.
The collected accessions are: IT98K-205-8, IT98K-555-1,
TVu-4886,
TVu-4866,
IT89KD-288,
TVu-9225,
TVu-11986, TVu-9256, TVu-9252 and TVu-11979; coded
as G1, G2, G3, G4, G5, G6, G7, G8, G9 and G10
respectively for easy statistical analysis and presentation of
data. The 10 cowpea genotypes were evaluated in a field laid
out in a Randomized Complete Block Design with three (3)
replications. Each replicate consisted of 10 row plots of 10
genotypes, each of which was regarded as a treatment, with
1m distance between treatments. Each treatment consisted of
30 plants, and the total number of plants on the field was 900.
Each treatment was sown at a spacing of 30cm between
plants and 50cm between rows. Weeding of the experimental
field was done as when required to keep the weed pressure
low. Sniper and Cypermethrin (cyperforce) were used at
different growth stages to control insect pests at appropriate
Broad sense heritability (H B) was expressed as the
percentage of the ratio of VG to VP as described by Allard et
al. [28] as:
h2B =Vg/Vp x 100…………………eqn. 5
and was categorized according [29] as follows:
0 – 30% = low; 30 – 60% = moderate;
60% = high.
Genetic advance (GA) was estimated by the method given
by [30] as:
GA = h2B x K x √Vp……………eqn. 6
Where, K is a constant (2.06) at 50% selection pressure;
√Vp is standard deviation of VP and h2B is the heritability
ratio. GA was also calculated as percentage of the mean
(GAM) according to the formula of [14] and categorized as 0
– 10% = low; 10 – 20% = moderate;
20% = high.
Genotypic and phenotypic correlations were estimated
according to [31].
VXY (G) = COV XY (G) / √VX (G) x VY (G)………. eqn. 7
VXY (P) = COV XY (P) / √VX (P) x VY (P) …………..eqn. 8
Where COVXY (G) is genotypic covariance between x and
y; COV XY (P) is phenotypic covariance between x and y; VX
(G) and VX (P) are genotypic and phenotypic variances of
character x; VY (G) and VY (P) are genotypic and phenotypic
variances of character y.
Test of significance of correlation was tested by the
International Journal of Plant Research 2014, 4(3): 63-71
following statistics:
2
t = r√ n – 2/√ 1 – r ….…….…..…..eqn. 9
Where, r and n are correlation coefficients and number of
observations respectively. The ‘t’ table was entered with (n –
2) degree of freedom.
Twenty quantitative (20) traits were measured using the
International Board for Plant Genetic Resources (IBPGR)
Cowpea Descriptors, which are: Emergence percentage (%),
plant height (cm), number of leaves per plant, number of
nodes on the main stem, number of main branches, terminal
leaflet length (cm), terminal leaflet width (cm), number of
peduncle per plant, peduncle length (cm), number of days to
flowering, number of pods per peduncle, number of pods per
plant, pod length (cm), pod weight (g), pod wall thickness,
number of seeds per pod, number of seeds per plant, seed
length (mm), seed width (mm) and 100-seed weight (g).
3. Results
Analysis of variance showed that the mean squares for all
traits (Table 2) indicated the existence of high significant
differences among the genotypes. Wide range significant
variations were observed in emergence percentage (22% to
90%), plant height (12.17cm to 26.26cm), number of leaves
per plant (12 to 43), and number of nodes on main stem (4 to
10), number of peduncle per plant (11 to 18), peduncle length
(13.58cm to 39.52cm), number of days to flowering (43days
to 88 days), number of pods per peduncle (0 to 4), number of
pods per plant (0 to 67), pod length (0.00cm to 19.34cm),
number of seeds per pod (0 to 19), number of seeds per plant
(0 to 1052), seed length (0.00cm to 8.42cm), seed width
(0.00cm to 5.27cm) and 100-seed weight (0.00g to 16.53g).
The range of variations among the genotypes for other traits
was low (Table 1).
Phenotypic variance was higher than genotypic variance
in all the traits studied, similarly the phenotypic coefficients
of variation (PCV) was higher than genotypic coefficient of
variation (GCV) in all the traits studied. PCV and GCV
values ranged from 6% and 5% respectively for terminal
leaflet length to 56% and 55% respectively for number of
seeds per plant (Table 2). The values of PCV and GCV were
low for terminal leaflet length; number of main branches and
terminal leaflet width had moderate PCV and GCV while all
other traits had high PCV and GCV values (Table 2).
Heritability values for the studied traits ranged from 54%
for plant height to 99% in pod length, pod wall thickness,
seed length and seed weight. All traits had high heritability
estimates (65% to 99%) except for plant height (54%) which
was moderate (Table 2). Low genetic advance as per cent of
means (GAM) was recorded for terminal leaflet length (9%),
and moderate GAM was recorded for terminal leaflet width
(20%) while all other measured traits had high genetic
advance as percent of means (24% to 110%) (Table 2).
65
The estimates of genotypic and phenotypic correlations
between all combinations of the 19 pair of traits among the
studied traits showed plant height to be highly significant
and positively correlated with number of leaves per plant
(0.76 and 0.52), number of nodes on main stem (0.66 and
0.44), number of main branches (0.69 and 0.41), terminal
leaflet width (0.51 and 0.30) and number of days to
flowering (0.52 and 0.38). This trait was also found to be
positive and highly correlated with terminal leaflet length
(0.26) only at the genotypic level. Plant height was also
found to be highly significant and negatively correlated with
peduncle length (-0.72 and -0.51), number of pods per
peduncle (-0.45 and -0.33), number of pods per plant (-0.33
and -0.23), number of seeds per plant (-0.64 and -0.45), and
seed weight (-0.78 and -0.56). Number of leaves per plant
was positive and highly correlated with number of nodes on
main stem (0.95 and 0.79), number of main branches (0.87
and 0.67), terminal leaflet length (0.35 and 0.27) and number
of days to flowering (0.45 and 0.42). It was also found to be
highly significant and negatively correlated with number of
pods per plant (-0.61 and -0.55), number of seeds per plant
(-0.83 and -0.77) and seed weight (-0.75 and -0.70). Number
of nodes on main stem was positive and highly correlated
with number of main branches (0.86 and 0.63), terminal
leaflet length (0.47 and 0.35) and number of days to
flowering (0.41 and 0.36). Number of nodes was also found
to be highly significant and negatively correlated with
number of pods per plant (-0.65 and -0.56), seeds per plant
(-0.62 and -0.55) and seed weight (-0.64 and -0.57). Number
of main branches was positive and highly correlated with
terminal leaflet length (0.41 and 0.27), number of days to
flowering (0.57 and 0.46), and highly correlated with
number of peduncle per plant (0.32 and 0.24) only at the
genotypic level. It was also found to be highly significant
and negatively correlated with number of pods per plant
(-0.51 and -0.39), seeds per plant (-0.55 and -0.44) and seed
weight (-0.56 and -0.46). Terminal leaflet width was found to
be positive and highly correlated with peduncle length (0.39
and 0.30) and number of seeds per plant (0.55 and 0.51) but
was found to be negative and highly correlated with number
of days to flowering (-0.45 and -0.35). Peduncle length was
positive and highly correlated with number of seeds per pod
(0.76 and 0.72) and seed weight (0.77 and 0.74), but was
highly significant and negatively correlated with number of
days to flowering (-0.88 and -0.83). Number of days to
flowering was highly significant and negatively correlated
with number of pods per peduncle (-0.79 and -0.78), number
of pods per plant (-0.81 and -0.77), pod length (-0.84 and
-0.83), pod weight (-0.85 and -0.75), pod wall thickness
(-0.83 and -0.81), number of seeds per pod (-0.89 and -0.79),
number of seeds per plant (-0.67 and -0.65), seed length
(-0.79 and -0.78), seed width (-0.64 and -0.63) and seed
weight (-0.68 and -0.67). Many traits were found to be highly
correlated among the tested genotypes (Table 3).
690.40±34.18bcd
8.34±0.13f
4.69±0.02f
13.40±0.21d
T17
T18
T19
T20
14.77±0.19e
5.27±0.05h
8.42±0.11f
762.65±77.69cd
11.87±0.52b
1.12±0.01h
2.30±0.01d
15.28±0.07d
64.53±7.12e
3.87±0.06d
47.47±1.09a
37.91±1.07c
16.73±1.99b
5.43±0.35abc
9.73±0.33a
5.00±0.31bc
6.72±0.40ab
20.40±1.20ab
15.68±0.88ab
46.67±3.33ab
G2
13.2±0.12d
2.85±0.08c
6.37±0.06c
332.65±10.62ab
10.67±0.07b
0.77±0.01c
1.59±0.06bc
13.57±0.16c
31.2±1.17bc
2.13±0.07b
46.27±0.87a
29.81±0.20b
14.6±0.83a
5.55±0.47abc
10.79±0.34a
5.13±0.17bc
9.61±0.40cd
35.00±1.10cde
19.49±1.20abc
58.33±1.67b
G3
11.50±0.26c
2.81±0.04c
6.38±0.07c
330.61±24.14ab
10.87±0.18b
0.69±0.00b
1.31±0.03b
12.54±0.19b
30.40±2.02b
2.20±0.11b
47.20±0.41a
30.56±0.21b
13.73±0.18ab
5.35±0.14abc
10.05±0.30a
5.13±0.07bc
8.69±0.11d
35.53±0.76de
22.47±0.20bc
85.00±5.00d
G4
16.53±0.18f
4.99±0.06g
8.41±0.08f
473.65±32.71bc
13.87±0.13c
0.95±0.00ef
1.72±0.13c
16.57±0.13f
34.20±2.11bc
3.07±0.07c
62.67±2.56b
33.70±1.21bc
11.13±0.33a
5.44±0.31abc
10.05±0.65a
4.33±0.27ab
5.43±0.17ab
14.93±1.33a
18.25±0.54abc
68.33±8.82c
G5
10.47±0.12b
2.54±0.02b
5.73±0.03b
744.89±26.06cd
15.87±0.24d
0.93±0.02de
2.21±0.05d
16.17±0.09ef
67.87±3.88e
4.00±0.12d
44.93±0.94a
38.57±0.65c
17±1.42b
5.67±0.31bc
10.83±0.64a
4.47±0.24abc
6.33±0.37bc
25.60±2.10bc
17.65±0.98abc
75.00±0.00c
G6
10.33±0.08b
4.16±0.03d
7.59±0.08d
939.67±19.93d
17.87±0.07e
1.05±0.03g
2.73±0.07e
17.65±0.08g
52.6±1.25de
4.40±0.12e
46.4±1.30a
39.52±2.38c
11.93±0.07a
6.43±0.05c
9.54±0.52a
4.00±0.12ab
4.47±0.17a
11.93±0.69a
22.41±1.36bc
90.00±0.0d
G7
11.27±0.14c
4.28±0.02de
7.93±0.08e
1051.59±60.23d
15.87±0.29d
0.88±0.02d
2.24±0.12d
15.81±0.18def
66.40±4.54e
3.80±0.12d
42.93±0.47a
36.72±0.68c
17.53±1.58b
6.25±0.40c
9.63±0.51a
5.00±0.12bc
6.20±0.20bc
27±2.50bcd
20.73±2.32abc
75.00±5.00c
G8
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
0.00±0.00a
87.87±0.59c
13.58±2.39a
15.73±0.50ab
4.68±0.25ab
9.77±0.32a
5.73±0.47c
9.00±0.64d
42.8±4.22e
26.61±3.49c
78.33±11.67d
G9
10.30±0.17b
4.46±0.12e
7.54±0.07d
1024.64±23.56d
19.53±0.24f
0.93±0.01fg
2.89±0.05e
19.34±0.12h
52.47±1.27de
4.47±0.07e
46.33±1.83a
33.84±0.91bc
12.07±0.53a
6.39±0.47c
10.19±0.22a
4.67±0.57bc
6.40±0.61bc
20.93±3.48ab
25.35±3.98c
84.13±6.71d
G10
Means followed by the same alphabet within a row are not significantly different from one another at P ≤ 0.05 using Duncan Multiple Range Test (DMRT). Values are means of measurements ± Standard error (S.E).
T1: Emergence percentage; T2: Plant height (cm); T3: number of leaves per plant; T4: number of nodes on the main stem; T5: number of main branches; T6: terminal leaflet length (cm); T7: terminal leaflet width (cm); T8:
number of peduncle per plant; T9: peduncle length (cm); T10: number of days to flowering; T11: number of pods per peduncle; T12: number of pods per plant; T13: pod length (cm); T14: pod weight (g); T15: pod wall
thickness (mm); T16: number of seeds per pod; T17: number of seeds per plant; T18: seed length (mm); T19: seed width (mm); T20: 100-seed weight (g).
15.33±1.00cd
T16
44.33±0.88a
T10
0.96±0.01ef
39.22±1.11c
T9
T15
11.77±1.13a
T8
2.26±0.08d
4.19±0.21a
T7
T14
9.07±0.75a
T6
15.65±0.43de
3.37±0.12a
T5
T13
6.89±0.43ab
T4
3.80±0.11d
14.53±2.35a
T3
45.87±5.07cd
12.17±0.79a
T2
T12
21.67±6.67a
T1
T11
G1
Trait
Table 1. Mean Values of 20 Quantitative Traits among the tested Cowpea Genotypes
66
Ajayi A. T. et al.: Character Expression and Differences in Yield Potential
of Ten Genotypes of Cowpea (Vigna unguiculata L. Walp)
635.07
6.66
3.58
11.18
T17
T18
T19
T20
59.21**
7.60**
19.17**
412001.59**
88.66**
0.31**
2.12**
86.17**
1343.05**
5.81**
576.63**
181.14**
76.05**
1.55**
0.95**
1.50**
7.06**
316.95**
58.13**
1360.74**
MS
19.80
2.55
6.42
141392.28
30.18
0.11
0.82
28.80
473.81
1.98
195.74
63.69
27.62
0.68
0.40
0.63
2.72
114.99
27.84
531.48
б‾2Ph
19.71
2.52
6.37
135304.65
29.24
0.10
0.65
28.69
434.62
1.93
190.44
58.72
24.22
0.44
0.27
0.43
2.17
100.98
15.15
414.63
б‾2g
39.81
49.48
38.05
56.25
41.71
38.85
46.92
37.64
48.84
43.98
27.28
23.94
41.52
14.87
6.37
17.16
26.17
43.12
26.26
33.57
PCV
39.73
44.34
37.89
55.02
41.06
38.67
41.77
37.57
46.77
43.61
26.73
22.98
38.88
11.95
5.23
14.11
23.11
40.41
19.37
29.65
GCV
99.58
98.82
99.16
95.69
96.89
99.36
79.27
99.62
91.73
98.37
97.28
92.2
87.67
65.00
68.00
67.57
79.78
87.82
54.40
78.01
h2B %
81.66
81.76
77.73
110.87
83.70
79.52
76.62
77.24
92.29
98.12
54.30
45.56
74.99
19.97
8.93
24.10
43.09
78.00
29.44
53.96
GAM
T1: Emergence percentage; T2: Plant height (cm); T3: number of leaves per plant; T4: number of nodes on the main stem; T5: number of main branches; T6: terminal leaflet length
(cm); T7: terminal leaflet width (cm); T8: number of peduncle per plant; T9: peduncle length (cm); T10: number of days to flowering; T11: number of pods per peduncle; T12:
number of pods per plant; T13: pod length (cm); T14: pod weight (g); T15: pod wall thickness (mm); T16: number of seeds per pod; T17: number of seeds per plant; T18: seed
length (mm); T19: seed width (mm); T20: 100-seed weight (g). MS: mean squares; б‾2Ph: phenotypic variance; б‾2g: genotypic variance; PCV: phenotypic coefficients of variation;
GCV: genotypic coefficients of variation; h2B: broad sense heritability; GAM: genetic advance as percent of mean
13.17
T16
51.64
T10
0.83
33.34
T9
1.93
12.66
T8
T15
5.54
T7
T14
9.95
T6
14.26
4.67
T5
T13
6.29
T4
3.18
24.87
T3
44.57
20.09
T2
T12
68.67
T1
T11
MEAN
TRAITS
Table 2. Estimates of Means, Mean Squares, Variance Components, Heritability and Genetic Advance as Percent of Mean among the tested Cowpea Genotypes
International Journal of Plant Research 2014, 4(3): 63-71
67
T2
1.00
1.00
T3
0.76**
0.52**
1.00
1.00
T4
0.66**
0.44**
0.95**
0.79**
1.00
1.00
T5
0.69**
0.41**
0.87**
0.67**
0.86**
0.63**
1.00
1.00
T6
0.26**
0.15
0.35**
0.27**
0.47**
0.35**
0.41**
0.27**
1.00
1.00
T7
0.51**
0.30**
-0.04
-0.03
-0.20
-0.15
-0.00
0.00
0.35**
0.23*
1.00
1.00
T8
-0.01
-0.00
0.24*
0.21
0.20
0.17
0.32**
0.24*
0.22
0.17
-0.06
-0.04
1.00
1.00
T9
-0.72**
-0.51**
-0.79**
-0.71**
-0.81**
-0.69**
-0.83**
-0.65**
-0.14
-0.12
0.39**
0.30**
-0.12
-0.11
1.00
1.00
T10
0.52**
0.38**
0.45**
0.42**
0.41**
0.36**
0.57**
0.46**
-0.07
-0.06
-0.45**
-0.35**
0.07
0.06
-0.88**
-0.83**
1.00
1.00
T11
-0.45**
-0.33**
-0.78**
-0.73**
-0.80**
-0.71**
-0.79**
-0.64**
-0.14
-0.11
0.57**
0.46**
-0.15
-0.14
0.95**
0.91**
-0.79**
-0.78**
1.00
1.00
T12
-0.51**
-0.35**
-0.61**
-0.55**
-0.65**
-0.56**
-0.51**
-0.39**
-0.00
-0.00
0.56**
0.43**
0.04
0.03
0.91**
0.84**
-0.81**
-0.77**
0.91**
0.87**
1.00
1.00
T13
-0.45**
-0.32**
-0.77**
-0.76**
-0.71**
-0.64**
-0.75**
-0.61**
0.05
0.04
0.59**
0.47**
-0.20
-0.19
0.92**
0.89**
-0.84**
-0.83**
0.89**
0.92**
0.81**
0.77**
1.00
1.00
T14
-0.38**
-0.25**
-0.76**
-0.63**
-0.75**
-0.60**
-0.77**
-0.57**
-0.09
-0.07
0.65**
0.46**
-0.17
-0.14
0.95**
0.81**
-0.85**
-0.75**
0.97**
0.98**
0.91**
0.77**
0.93**
0.94**
1.00
1.00
T15
-0.62**
-0.45**
-0.81**
-0.76**
-0.80**
-0.71**
-0.76**
-0.62**
-0.05
-0.04
0.46**
0.37**
-0.14
-0.13
0.96**
0.92**
-0.83**
-0.81**
0.94**
0.93**
0.85**
0.81**
0.90**
0.92**
0.83**
0.90**
1.00
1.00
T16
-0.33**
-0.23**
-0.73**
-0.68**
-0.68**
-0.61**
-0.81**
-0.65**
-0.02
-0.01
0.64**
0.51**
-0.23*
-0.21
0.91**
0.86**
-0.89**
-0.79**
0.96**
0.94**
0.82**
0.77**
0.97**
0.95**
0.97**
0.94**
0.89**
0.87**
1.00
1.00
T17
-0.64**
-0.45**
-0.59**
-0.53**
-0.62**
-0.55**
-0.55**
-0.44**
-0.05
-0.04
0.65**
0.51**
-0.11
-0.10
0.76**
0.72**
-0.67**
-0.65**
0.87**
0.85**
0.84**
0.79**
0.76**
0.74**
0.91**
0.79**
0.73**
0.72**
0.84**
0.81**
1.00
1.00
T18
-0.68**
-0.49**
-0.83**
-0.77**
-0.77**
-0.69**
-0.72**
-0.59**
-0.22*
-0.18
0.33**
0.26**
-0.21
-0.14
0.91**
0.87**
-0.79**
-0.78**
0.81**
0.80**
0.72**
0.69**
0.82**
0.89**
0.83**
0.75**
0.93**
0.92**
0.78**
0.80**
0.64**
0.62**
1.00
1.00
T19
-0.63**
-0.45**
-0.91**
-0.84**
-0.87**
-0.77**
-0.69**
-0.56**
-0.35**
-0.28**
0.30**
0.24*
-0.22
-0.21
0.83**
0.79**
-0.64**
-0.63**
0.79**
0.72**
0.68**
0.65**
0.47**
0.43**
0.81**
0.73**
0.90**
0.89**
0.71**
0.75**
0.66**
0.64**
0.91**
0.91**
1.00
1.00
T20
-0.78**
-0.56**
-0.75**
-0.70**
-0.64**
-0.57**
-0.56**
-0.46**
0.03
0.02
0.15
0.13
-0.15
-0.14
0.77**
0.74**
-0.68**
-0.67**
0.61**
0.60**
0.55**
0.52**
0.79**
0.78**
0.59**
0.59**
0.83**
0.82**
0.60**
0.61**
0.37**
0.36**
0.84**
0.84**
0.95**
0.94**
1.00
1.00
**Significant at 1% level, * Significant at 5% level
T2: Plant height (cm); T3: number of leaves per plant; T4: number of nodes on the main stem; T5: number of main branches; T6: terminal leaflet length (cm); T7: terminal leaflet width (cm); T8: number of peduncle per plant;
T9: peduncle length (cm); T10: number of days to flowering; T11: number of pods per peduncle; T12: number of pods per plant; T13: pod length (cm); T14: pod weight (g); T15: pod wall thickness (mm); T16: number of seeds
per pod; T17: number of seeds per plant; T18: seed length (mm); T19: seed width (mm); T20: 100-seed weight (g).
T20
T19
T18
T17
T16
T15
T14
T13
T12
T11
T10
T9
T8
T7
T6
T5
T4
T3
T2
Traits
Table 3. Genotypic and Phenotypic Correlations between Traits (genotypic above and phenotypic below in each row) among the tested Cowpea Genotypes
68
Ajayi A. T. et al.: Character Expression and Differences in Yield Potential
of Ten Genotypes of Cowpea (Vigna unguiculata L. Walp)
International Journal of Plant Research 2014, 4(3): 63-71
4. Discussions
To conquer the problem of low productivity in cowpea, it
is pertinent to identify high yielding genotypes among with
resistance to major biotic and abiotic constraints among
available germplasm collection. Identification of these better
genotypes, their introduction in breeding programmes
coupled with establishment of suitable selection criteria will
be helpful for successful varietal improvement programme.
Analysis of variability among genotypes for various traits
and association of traits in relation to yield contributing
factors of the crop would be of great importance for
successful breeding programme. For this research, analysis
of variance revealed high significant differences for all traits
studied, which indicated the existence of sufficient genetic
variability among the tested genotypes. These patterns of
high level of variability have been observed by many
researches on cowpea ([12]; [21]) and on many other crops
[32]. The high genotypic coefficients of variations (GCV)
and phenotypic coefficients of variations (PCV) associated
with traits like emergence percentage, number of leaves per
plant, number of nodes on main stem, number days to
flowering, peduncle length, number of peduncles per plant,
number of pods per peduncle, number of pods per plant, pod
length, pod weight, pod wall thickness, number of seeds per
pod, number of seeds per plant, seed length, seed width and
seed weight implied that these traits are governed by genetic
factors; and existence of greater magnitude of genetic
variability in the listed traits as a consequence and possibility
of their improvement through selection. The results agree
with several workers [33]; [34]; [35]). The moderate GVCs
and PVCs experienced in traits like terminal leaflet width,
number of main branches and plant height were in line with
findings of [35], and show the presence of moderate
variability among the studied genetic stock [11], and indicate
that selection for these traits is less effective compared to
those traits with high GVCs and PVCs.
High broad sense heritability values for all traits studied
except for plant height are in accordance with results of
many researchers on cowpea ([18]; [19]; [36]; [37]) and
these shows that these traits are less influenced by
environmental effects, which makes them effectively
transmitted to the progeny [21]. There is an influence of
fixable additive gene effects for inheritance of these traits
([38]; [39]) and therefore, selection for these traits may lead
to fast genetic improvement. Similar results of high
heritability estimates have been reported for days to
flowering, pod length, pod weight, number of pods per plant,
number of seeds per pod and 100-seed weight in cowpea
([40]; [41]). For heritability estimates to be reliable, it must
be accompanied by high genetic advance ([32]; [21]) for a
reliable index for selection of traits [18].
High heritability and high genetic advance as percent of
mean (GAM) was observed for almost all studied traits
except for terminal leaflet length and terminal leaflet width,
69
observations which indicate additive gene effects, and
suggest that effective progress in improvement through
selection could be achieved for yield. These results are in
agreement with the findings of [40]; [21] on cowpea and
several workers on other crops ([42]; [11]; [32]).
The estimates of genotypic and phenotypic correlations
among the measured characters obtained in this study would
be of interest for breeding objectives. The degree of
correlation among traits is an important factor in economic
and complex character as yield [43]. Correlations are
measures of the intensity of association between traits,
whereby selection for a trait results in progress for all traits
that are positively correlated and retrogress for traits that are
negatively correlated [43]. The high negative significance
genotypic and phenotypic correlations between plant heights,
number of pods per plant, pod length, seeds per pod and seed
weight imply that plant with higher height may have fewer
numbers of pods and seeds. This contradicts the results of
[44]. The high significance genotypic and phenotypic
correlations between number of days to flowering and
number of pods per plant, pod length, seeds per pod, and
seeds per plant and seed weight indicate that genotypes
which flower earlier produce more pods and seeds per plant.
This agrees with the work of [45] and [44]. The high positive
genotypic and phenotypic correlations between numbers of
pods per plant, number of seeds per pod, number of seeds per
plant and seed weight indicates that selection for these will
result in increase in yield. Based on phenotypic and
genotypic association between yield and yield contributing
traits, it is suggested that selection should be made for the
characters, which are having positive significant association
to improve the seed yield per plant in cowpea.
The results from this research have shown that enough
variability and genetic heritability exist in the studied traits
among the tested cowpea genotypes. High mean values for
yield and its component traits, high genotypic coefficients of
variation, high heritability and genetic advance coupled with
high genotypic and phenotypic positive significant
associations among yield and yield contributing traits
warrant effective selection for further improvement. This
study identified genotypes G1, G2 and G5 for further genetic
studies based on the highest seed weights and high number of
seeds per plant.
ACKNOWLEDGEMENTS
The authors acknowledge the contribution of the Genetic
Resources Center, International Institute of Tropical
Agriculture (IITA), Ibadan, for providing the cowpea
genotypes used for this study. Our profound gratitude also
goes to Dr. Gueye Badara of Genetic Resources Center, IITA,
Ibadan, for his prompt responses to us during the period of
this research.
Ajayi A. T. et al.: Character Expression and Differences in Yield Potential
of Ten Genotypes of Cowpea (Vigna unguiculata L. Walp)
70
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