OPEN ACCESS
Journal of Multidisciplinary Applied Natural Science Vol. 2 No. 2 (2022)
https://doi.org/10.47352/jmans.2774-3047.119
Research Article
Relationship of Quantitative Traits in Different
Morphological Characters of Pea (Pisum Sativum L.)
Sarah Tasnim, Nilufa Yasmin Poly, Nusrat Jahan, and Ahasan Ullah Khan*
Received : February 17, 2022
Revised : April 16, 2022
Accepted : April 18, 2022
Online : April 20, 2022
Abstract
An experiment was undertaken to elucidate the genetic relationship between different quantitative traits for commercial cultivation
and to evaluate selection criteria in pea breeding programs in five inbred parents. Their 17 F4’s derivatives in pea (Pisum
sativum L.) evaluated ten characters during the winter season (November to February) of 2017-18 at the research farm, BSMRAU,
Gazipur, Bangladesh. Analysis of variance explored significant differences among the genotypes for all the characters. Phenotypic
coefficients of variation (PCV) were close to genotypic coefficients of variation (GCV) for all the characters indicating less
influence on the environment and potentiality of selection. A high heritability relationship with high genetic advance was observed
for plant height, pod per plant, hundred seed weight, and seed yield per plot. Pod length showed a highly significant positive
correlation with pod width and hundred seeds weight. Only days to first flowering showed a highly negative correlation with pod
length and hundred seed weight. Path coefficient analysis revealed that plant height, pod per plant, and seeds per pod had a highly
positive effect on yield per plant. Therefore, associating and selecting those traits, yield improvement must be possible in pea, and
the days to maturity, plant height, pods per plant, pod length, and seed showed a considerable positive and highly significant
correlation with plant height, pod per plant, seed per pod, and yield per plant at both genotypic and phenotypic levels indicating
yield could be increased with the increase of days to maturity, plant height, pods per plant, pod length, and seed.
Keywords Pea, Pisum sativum, plant height, flower, pod, seed, PVC, GCV
1. INTRODUCTION
Pea (Pisum sativum L.) is an annual herbaceous
important member crop that belongs to the family
Leguminosae. Among legumes, Pisum sativum is
the oldest common pea and it is a self-pollinated
(2n=2x=14) food crop [1]. It has initiated in the
Mediterranean region, primarily in the Middle East
[2]. It is an imperative, highly productive, and
nutritionally rich cool-season legume crop, grown
across the world, consumed as food, feed, and
fodder [3][4]. Pea is cultivated for green pod seeds
as vegetable and dry seeds in Bangladesh.
It is a vital crop with a rich history in genetic
study seeing back to the classical work by the father
of genetics Gregor J. Mendel. Genetic deviation
more gives an idea about the scope of development
in a character through simple selection based on
grouping. Generally, the mature dry seeds are used
as dhal and the green seeds are used as fresh,
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© Tasnim, S., Poly, N. Y., Jahan, N., and Khan, A. U. (2022)
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frozen, or canned vegetables. It is an excellent
source of dietary protein, nutritious feed for humans
and livestock. This plant is a great source of
nitrogen having a profound ameliorative effect on
soil. It is widely used as a supplement feed, fresh
vegetables, grains, and green manure, due to its
amusing source of healing properties and nutritional
value [5]. It is a starchy vegetable with high
nutritional value, high in fibers, proteins, vitamin A,
vitamin B6, vitamin C, vitamin K, iron, zinc,
phosphorus, magnesium, copper, and lutein [6]. The
protein of peas contains all the essential amino
acids important for the normal activity of living
organisms [7][8].
Pathak and Jamwal [9] stated that the high
genotypic coefficient of variation (GCV) was noted
for pod yield per plant, moderate to high GCV were
verified for several days to 50% flowering and plant
height. Sureja and Sharma [10] reported that a
considerable amount of phenotypic coefficient of
variation and genotypic coefficient of variation was
observed for most of the characters such as the
plant height, number of pods per plant, and weight
of grains per pod, while the variation was low for
the other characters tested. Breeding efforts have
contributed substantially to improving yield
potential, regional adaptation through resistance or
tolerance to abiotic, and is a highly complex
character and is controlled by a large number of
genes and greatly influenced by the environment
103
42.858**
0.0001
0.13
54.276**
0.001
0.16
1.462**
0.017
2.53
0.048**
0.0001
0.65
1.513**
0.011
1.73
57.372**
0.102
2.62
0.27
0.47
0.474
0.78
1.502
2.86
4.13
5.67
42
Error
CV%
3250.99**
200.779*
114.37**
109.513**
21
Genotype
Note: ** and * Significant at 1% and 5% level of probability, respectively.
DFF = Days to First Flowering, DFPF = Days to 50% flowering, PH = Plant Height (cm), PPP = Pods per Plant (no.), PL = Pod Length (cm), PW = Pod Width (cm), SPP = Seeds per Pod (no.),
DM = Days to Maturity, HSW = Hundred Seed Weight (g),
SYPP = Yield per Plant (g).
0.0002
0.0017
0.0093
0.00002
0.07
0.2306
0.14
60.045
48.966
21.511
2
Replication
DM
DFPF
Source of Variation
Table 1. Analysis of variance for yield and yield related characters in pea.
PH
DFF
df
PPP
PL
SYPP
HSW
SPP
PW
J. Multidiscip. Appl. Nat. Sci.
and quality traits influence the yield directly and
indirectly. These traits are simply inherited and less
influenced by the environment as compared to
yield. So, selection based on these traits has a better
chance of success in comparison to selection for
yield alone. The genotypic correlation indicates the
extent to which the two characters are under the
control of the same set of genes are having the
physiological basis of their expression [11][12].
In the pea gene pool, genotypes with new mutant
traits have looked, changing the plant body. It has
led to a substantial change in the constraints of the
morphostructure of the new variations and
increasing the limit of the changeability of the
quantitative traits. Many researchers differently
evaluate the role of the individual characteristics in
plant thruput formation. Hamed et al. [12] found
that positive heterosis over the better parent for
plant length was ranged from 6.44% to 104.21%. El
-Dakkak [13] found negative heterosis (-16.82%)
based on the tallest parent for this trait. Significant
positive heterosis based on an early parent was
observed in all garden pea crosses for days to the
flowering trait [14], while, Askander and Osman
[15] found negative heterosis in some crosses and
positive heterosis values in the others. The data
from these studies provide an opportunity to
combine appropriate traits in one genotype and
increase the efficiency of the breeding activity [16].
Zayed et al. [17] reported that the maximum
significant heterosis in desirable direction was
recorded for the number of seeds/pod.
Genanasekaran and Padmavathi [18] found that
average heterosis was observed for plant height,
pods per plant, pod length, and seeds per pod. The
plant height, pods per plant, pod length, seed
number and seed weight were effect of yield of pea.
El Hanafi et al. [19] found that the maximum
significant mid-parent heterosis in desirable
direction was recorded for stem length trait.
Hussein [20] confirmed the partial dominance for
earliness and overdominance for the remainder
growth trait stem length and number of branches.
The inheritance of quantitative characters in peas
has long been investigated. Suman et al. [21] and
Manjunath et al. [22] observed that both general
and specific combining abilities were important for
hundred seed weight and the number of seeds per
pod. Also, Askander et al. [23] reported that general
104
J. Multidiscip. Appl. Nat. Sci.
combining ability was significant for the traits plant
height, 100 seeds weight, and pod weight but nonsignificant for seeds pod, while SCA for most
characters was significant in pea. This correlation
study along with path coefficient analysis is more
useful to study the yield conducive traits [12]. This
study aims to find out the relationship between
different quantitative traits for commercial
cultivation and to evaluate selection criteria in pea
breeding programs.
2. MATERIALS AND METHODS
2.1. Materials
2.1.1. Study Period and Site
The experiment was conducted at the
experimental field of Genetics and Plant Breeding
Department, Bangabandhu Sheikh Mujibur Rahman
Agricultural University (BSMRAU), Salna, Gazipur
during the winter season (November to February) of
2017-2018. The experimental site is located at the
center of the Madhupur tract (latitude- 24.09°N and
longitude- 90.26°E) with an elevation of 8.4 meters
from the sea level.
2.1.2. Planting Materials
Five inbred parents viz. IPSA Motorshuti 1,
IPSA Motorshuti 2, IPSA Motorshuti 3, Natore,
Zhikargacha along with seventeen F4’s viz IPSA
Motorshuti 1 × IPSA Motorshuti 2, IPSA
Motorshuti 1 × IPSA Motorshuti 3, IPSA
Motorshuti 3 × IPSA Motorshuti 1, IPSA
Motorshuti 1× Natore, IPSA Motorshuti 1 ×
Zhikargacha, Zhikargacha × IPSA Motorshuti 1,
IPSA Motorshuti 2 × IPSA Motorshuti 3, IPSA
Motor shuti 3 × IPSA Motorshuti 2,
IPSA
Motorshuti 2 × Natore, IPSA Motorshuti 2 ×
Zhikargacha, Zhikargacha × IPSA Motorshuti 2,
IPSA Motorshuti 3 × Natore, Natore × IPSA
Motorshuti 3, IPSA Motorshuti 3 × Zhikargacha,
Zhikargacha × IPSA Motorshuti 3, Natore ×
Zhikargacha, Zhikargacha × Natore produced from
crossing of the inbred parents were included in the
experiment. The F4’s were synthesized in the
previous year of the experiment. All the seeds of the
mentioned genotypes were collected from the
Department of Genetics and Plant Breeding
Department, Bangabandhu Sheikh Mujibur Rahman
Agricultural University (BSMRAU).
2.2. Methods
2.2.1. Experimental Design
Each plot consisted of a single row of 1.5 m
long. The rows were spaced at 25 cm in which
seeds were sown continuously. The experiment was
laid out in a Randomized Complete Block Design
(RCBD) with three replications.
2.2.2. Data Collection
Five randomly selected competitive plants from
parents and 20 plants of F4’s were used for
recording observations on the following parameters.
Genotypic and phenotypic coefficients of variations
were estimated by using those formulas.
2.2.2.1. Univariate Analysis
The data were statistically analyzed. The mean,
range, and standard deviation for each character
have been calculated and analysis of variance for
each of the characters was performed, and mean
values were separated by DMRT. The mean square
(MS) at error and phenotypic variances were
estimated as per [24]. The error MS was considered
as error variance ( 2e), Genotypic variances ( 2g)
were derived by subtracting error MS from the
variety MS and dividing by the number of
replications as shown below:
(1)
Where GMS and EMS are the varietal and error
can square and r is the number of replications. The
phenotypic variance ( 2 p), were derived by adding
genotypic variances with the error variance ( 2e), as
given by the formula 2.
(2)
2.2.2.2. Estimation of Genotypic and Phenotypic
Coefficient of Variation
Genotypic and phenotypic coefficient of
variation (GCV) was calculated by the formula 3.
105
(3)
where,
g
= Genotypic standard deviation,
=
J. Multidiscip. Appl. Nat. Sci.
Table 2. Genotypic (G) and phenotypic (P) correlation coefficient of ten different characters of pea.
Traits
DFF
DFPF
DM
PH
PPP
PL
PW
SPP
HSW
G
0.923**
P
0.895**
DM
G
P
0.454*
0.325
0.687**
0.568**
PH
G
P
0.288
0.129
0.563**
0.409*
0.885**
0.828**
PPP
G
P
0.248
0.155
0.496**
0.411*
0.634**
0.591**
0.676**
0.633**
PL
G
P
-0.655**
-0.728**
-0.418*
-0.543**
0.042
-0.054
0.162
0.110
-0.115
-0.164
PW
G
P
-0.522**
-0.469*
-0.477*
-0.415*
-0.297
-0.179
-0.202
-0.075
-0.332
-0.274
0.737**
0.800**
SPP
G
P
0.194
0.027
0.478*
0.307
0.749**
0.631**
0.790**
0.702**
0.513**
0.425*
0.428*
0.420*
0.091
0.266
HSW
G
P
-0.648**
-0.587**
-0.576**
-0.489*
-0.441*
-0.290
-0.237
-0.046
-0.264
-0.168
0.620**
0.718**
0.841**
0.830**
-0.080
0.133
G
-0.155
0.196
0.484*
0.657**
0.788**
0.390
0.205
0.599**
0.281
P
-0.261
0.084
0.425*
0.636**
0.769**
0.371
0.292
0.557**
0.418*
DFPF
YPP
Note: ** and * Significant at 1% and 5% level of probability, respectively
PH = Plant Height (cm), PPP = Pod Per Plant (no.), PL = Pod Length (cm), PW = Pod Width (cm), SPP = Seed Per Pod (no.), DFF = Days to First Flowering, DFPF = Days to 50% flowering,
DM = Days to Maturity, HSW = Hundred Seed Weight (g), SYPP= Seed Yield Per Plant
Population mean similarly, the phenotypic
coefficient of variation (PVC) was calculated from
the following formula 4.
(4)
Where, p = Phenotypic standard deviation; =
Population mean
2.2.2.3. Estimation of Heritability
Broad sense heritability was estimated by the
formula 5 suggested by [24].
(5)
Where, h2 =Heritability;
2
p =Phenotypic variance.
2
g
=Genotypic variance;
2.2.2.5. Estimation of genotypic and phenotypic
correlation co-efficient
For calculating the genotypic (rg) and
phenotypic (rp) correlation coefficient for all
possible combinations the formula 7 and 8
suggested by Silpashree et al. [24] and Hanson et al.
[25].
(7)
Where, 2gxy = Genotypic covariance between
the traits x and y; 2gx = Genotypic variance of the
trait x; 2gy = Genotypic variance of the trait y.
(8)
2.2.2.4. Estimation of Genetic Advance
The expected genetic advance for different
characters under selection was estimated using the
formula 6 suggested by Silpashree et al. [24].
Genetic advance (GA) = K x h2 x
(6)
Where, 2pxy = phenotypic covariance between
the traits x and y; 2px = phenotypic variance of the
trait x; 2py = phenotypic variance of the trait y.
p
106
J. Multidiscip. Appl. Nat. Sci.
2.2.2.6. Estimation of Path Coefficient Analysis
Path analysis was carried out using the
genotypic correlation coefficients to know the direct
and indirect effects of the components on yield as
suggested and illustrated [26][27].
2.2.3. Statistical Analysis
The collected data were analyzed by the
Analysis of variance (ANOVA) technique using the
computer package program MSTAT and mean
differences were adjudged by the least significant
difference (LSD) test at a 5% level of significance.
3. RESULTS AND DISCUSSIONS
3.1. Mean Performance for Yield and Yield-Related
Characters in Pea
Analysis of variance for all the characters
showed significant differences between the
treatments viz., days to first flowering, days to 50%
flowering, plant height (cm), pods per plant (no.),
pod length (cm), pod width (cm), seeds per pod
(no.), days to maturity, hundred seed weight (g),
yield per plant (g). Thus, there was considerable
genetic variability in the material chosen for
investigation (Table 1).
3.2. Genetic Parameters of Pea
3.2.1. Days to first flowering
Days to first flowering showed a considerable
positive and highly significant correlation with days
to 50% flowering and days to maturity at both
genotypic and phenotypic levels. In contrast days to
first flowering showed a positive but nonsignificant correlation with plant height, seed per
pod, and pod per plant. On the other hand, pod
length, pod width, hundred seed weight have highly
negative and significant correlations with days to
first flowering and it showed a negative and nonsignificant relationship with yield per plant in both
genotypic and phenotypic levels (Table 2).
Gudadinni et al. [28] observed days to first
flowering (30.07 to 64.45), days to 50% flowering
(35.71to 75.55), days to first pod setting (33.92to
68.23), days to first pod picking (45.85 to 82.36),
and those results were supported to this results.
3.2.2. Days to 50% flowering
Days to 50% flowering showed a considerable
positive and highly significant correlation with days
to maturity, plant height, seed per pod, pod per plant
at both genotypic and phenotypic levels. Besides
days to 50% flowering showed considerable positive
but non-significant correlation with yield per plant.
On the other hand, pod length, pod width, hundred
seed weight have a highly negative and significant
correlation with days to 50% flowering in both
genotypic and phenotypic levels (Table 2). Lagiso et
al. [29] found days to 50% flowering were positively
associated with days to maturity.
3.2.3. Days to Maturity
Days to maturity showed a considerable positive
and highly significant correlation with plant height,
pod per plant, seed per pod, and yield per plant at
both genotypic and phenotypic levels. On the
contrary days to maturity showed considerable
negative and significant correlation with hundred
seed weight. On the other hand, pod length, pod
width has a highly negative and non-significant
correlation with days to maturity in both genotypic
and phenotypic level (Table 2). According to Singh
et al. [30], days to maturity was a major yield and
yield contributing character in field pea. Motte et al.
[31] studied on the correlation between yield and
yield components of a pea.
3.2.4. Plant Height
Plant height showed a considerable highly
significant positive correlation with pods per plant,
seeds per pod, and yield per plant at a genotypic
and phenotypic level indicating yield could be
increased with the increase of plant height. Quite
the opposite, plant height exhibited an insignificant
positive association with pod length. On the other
hand, pod width, hundred seed weight have an
insignificant negative correlation with plant height
in both genotypic and phenotypic levels (Table 2).
Riaz et al. [32] reported that plant height showed a
positive correlation with seed yield per plant.
3.2.5. Pods per Plant
Pods per plant showed a considerable significant
positive correlation with seeds per pod, yield per
plant at both genotypic and phenotypic levels
indicating yield could be increased with the
107
J. Multidiscip. Appl. Nat. Sci.
increase of pods per plant. Furthermore, pods per
plant exhibited an insignificant negative association
with pod length, pod width, and hundred seed
weight (Table 2). Siddika et al. [33] assessed pods
per plant exerted a positive direct effect on yield.
correlation with yield per plant at both genotypic
and phenotypic levels. In addition to seeds per pod
showed a considerable negative insignificant
correlation with hundred seed weight (Table 2).
Gayacharan et al. [37] found a positive correlation
with seed yield and seeds per pod in black gram.
Karyawati and Puspitaningrum [38] got the similar
result in lentil. Tiwari and Lavanya [39] found a
significant and positive correlation between seed
yield per plant and the number of seeds per pod.
Similar results were also observed [35] in legume
crop country bean during 2017-2018 in Sylhet,
Bangladesh.
3.2.6. Pod Length
Pod length showed a significant positive
correlation with pod length, pod width, hundred
seed weight at both genotypic and phenotypic
levels. Quite the reverse, pod length exhibited an
insignificant positive association with yield per
plant (Table 2). Character association studies of
Sharma et al. [34] in pea indicated a positive and
insignificant association with seed yield per plant.
Similar results were also observed by Khan et al.
[35] in legume crop country bean during 2017-2018
in Sylhet, Bangladesh.
3.2.9. 100 seed weight
The character 100 seed weight showed a positive
and phenotypically non-significant correlation with
seed yield per plant (Table 2). A significant and
positive correlation was observed with days to
maturity, plant height, pods per plant at both
genotypic and phenotypic levels. The character
showed a nonsignificant positive correlation with
days to 50% flowering, pod length, pod width, and
this character showed a nonsignificant negative
correlation with days to first flowering at both
levels. Siddika et al. [33] observed a positive
correlation between seed yield per plant and 100
seed weight. Similar results were also observed by
Khan et al. [35], Khan et al. [40], and Khan et al.
[41] in legume crop country bean during 2017-2018
in Sylhet, Bangladesh.
3.2.7. Pod Width
Pod width showed a significant positive
correlation with hundred seed weight at both
genotypic and phenotypic levels. In contrast, pod
width showed an insignificant positive correlation
with seed per pod and yield per plant at both
genotypic and phenotypic levels (Table 2). Similar
results were also observed by Khan et al. [36] in
legume crop country bean during 2017-2018 in
Sylhet, Bangladesh.
3.2.8. Seeds per Pod
Seeds per pod showed a significant positive
Table 3. Partitioning of genotypic correlation (rg) into its direct and indirect effects for seed yield
components in pea.
Traits
DFF
DFPF
DM
PH
PPP
PL
PW
SPP
HSW
YPP
DFF
-0.233
0.216
-0.061
0.080
0.175
-0.067
-0.078
-0.005
-0.172
-0.146
DFPF
-0.201
0.251
-0.095
0.159
0.360
-0.044
-0.074
-0.013
-0.156
0.188
DM
-0.103
0.172
-0.138
0.256
0.472
0.006
-0.047
-0.021
-0.122
0.475*
PH
-0.063
0.136
-0.120
0.294
0.514
0.018
-0.032
-0.022
-0.067
0.657**
PPP
-0.053
0.119
-0.085
0.198
0.762
-0.013
-0.053
-0.014
-0.074
0.786**
PL
0.139
-0.099
-0.007
0.047
-0.086
0.112
0.117
-0.012
0.173
0.385
PW
0.114
-0.115
0.040
-0.059
-0.252
0.082
0.161
-0.003
0.237
0.205
SPP
-0.041
0.112
-0.099
0.228
0.381
0.046
0.014
-0.029
-0.022
0.589**
HSW
0.142
-0.139
0.060
-0.070
-0.200
0.069
0.135
0.002
0.283
0.281
Note: Residual effect (R) = 0.05430826
PH = Plant Height (cm), PPP = Pods Per Plant (no.), PL = Pod Length (cm), PW = Pod Width (cm), SPP = Seeds Per Pod (n o.), DFF = Days to First Flowering,
DFPF = Days to 50% flowering, DM = Days to Maturity, HSW = Hundred Seed Weight (g), YPP= Yield Per Plant (g).
108
J. Multidiscip. Appl. Nat. Sci.
3.3. Path Coefficient Analysis
Association of character determined by
correlation coefficient may not provide an exact
picture of the relative importance of the direct and
indirect influence of each yield component on yield.
As a fact, to find out a clear picture of the
interrelationship between yield per plant and other
yield attributes, direct effects were worked out
using path analysis at a genotypic level which also
measured the relative importance of each
component. Seed yield per plant was considered as
a resultant (dependent) variable and plant height,
pods per plant, pod length, pod width, seeds per
pod, days to first flowering, days to 50% flowering,
days to maturity, and hundred seed weight as a
causal (independent) variable.
The cause and effect of the relationship of yield
per plant and yield-related characters have been
presented in Table 3. Residual effects of their
independent variables, which have influenced yield
to a small extent, have been denoted as 'R'.
3.3.1. Days to First Flowering
Days to first flowering showed negative direct
effects with yield per plant (-0.233). This trait
showed the maximum positive indirect effect in
days to 50% flowering (0.216), pods per plant
(0.175), plant height (0.080). In contrast, this trait
showed a negative indirect effect through seeds per
pod (-0.005), days to maturity (-0.061), pod length
(-0.067), pod width (-0.078), yield per plant (0.146), hundred seed weight (-0.172) (Table 3 and
Figure 1).
3.3.2. Plant Height
Plant height showed a positive direct effect on
yield per plant (0.294). This trait projected
maximum positive indirect effects on biological
yield via yield per plant (0.657), pods per plant
(0.514), days to 50% flowering (0.136), and pod
length (0.018). In contrast, this trait projected
negative indirect effects on biological yield through
seeds per pod (-0.022), pod width (-0.032), days to
first flowering (-0.063), hundred seed weight (0.067), and days to maturity (-0.120) (Table 3).
3.3.3. Pods per Plant
Pods per plant showed a positive direct effect on
yield per plant (0.762). Pods per plant showed the
maximum positive indirect effect through yield per
plant (0.786), followed by plant height (0.198) and
days to first flowering (0.119). In contrast, this trait
showed the negative indirect effect via pod length (0.013), seeds per pod (-0.014), pod width (-0.053),
days to first flowering (-0.053), hundred seed
weight (-0.074), and days to maturity (-0.085)
(Table 3). In path coefficient analysis of revealed
that the number of pods per plant had the greatest
direct effect on yield per plant.
3.3.4. Days to 50% Flowering
Days to 50% flowering showed a positive direct
effect on yield per plant (0.251). This trait showed
the maximum positive indirect effect through pods
per plant (0.360) followed by yield per plant
(0.188), plant height (0.159). In contrast, this trait
showed a negative indirect effect through seeds per
pod (-0.013), pod length (-0.044) pod width (0.074) days to maturity (-0.095) hundred seed
weight (-0.156) and days to first flowering (-0.201)
(Table 3). Hageblad [42] showed that yield had
positive associations with days to 50% flowering.
3.3.5. Days to Maturity
Days to maturity showed positive direct effects
with yield per plant (-0.138). This trait showed the
maximum positive indirect effect through yield per
plant (0.475) which was significantly followed by
pods per plant (0.472), plant height (0.256), days to
50% flowering (0.172), and pod length (0.006). In
contrast, this trait showed a negative indirect effect
through seed per pod (-0.021), width (-0.047), days
to first flowering (-0.013), and hundred seed weight
(-0.122) (Table 3 and Figure 1).
3.3.6. Pod Length
Pod length showed a positive direct effect on
yield per plant (0.112). This trait showed the
maximum positive indirect effect through yield per
plant (0.385) followed by hundred seed weight
(0.173), days to first flowering (0.139), pod width
(0.117), and plant height (0.047). In contrast, this
trait showed a negative indirect effect through days
to maturity (-0.007), seeds per pod (-0.012), pods
per plant (-0.086), and days to 50% flowering (0.099) (Table 3).
109
J. Multidiscip. Appl. Nat. Sci.
Figure 1. Path diagram of yield contributing characters in vegetable pea (1. Days of first flowering;
2. Days of 50 flowering; 3. Days to maturity; 4. Plant height; 5. Pods per plant; 6. Pod length;
7. Pod width; 8. Seeds per pod; 9. 100 seed weight; 10. Yield per plant).
3.3.7. Pod Width
Pod width showed a positive direct effect on
yield per plant (0.161). This trait showed the
maximum positive indirect effect through hundred
seed weight (0.237) followed by yield per plant
(0.205), days to first flowering (0.114), pod length
(0.082), and days to maturity (0.040). In contrast,
this trait showed a negative indirect effect through
seeds per pod (-0.033), plant height (-0.059), days
to 50% flowering (-0.115), and pods per plant (0.252) (Table 3).
3.3.8. Seeds per Pod
Seeds per pod showed a negative direct effect on
yield per plant (-0.029). This trait showed the
maximum positive indirect effect through yield per
plant (0.589) followed by pods per plant (0.381),
plant height (0.228), days to 50% flowering (0.112),
pod length (0.046), and pod width (0.014). In
contrast, this trait showed a negative indirect effect
through hundred seed weight (-0.022), days to first
flowering (-0.041), and days to maturity (-0.099)
(Table 3). Tanni et al. [43] also observed similar
results in the okra promising genotypes in Sylhet
during 2018.
3.3.9. 100 Seed Weight
Hundred seed weight showed positive direct
effects with yield per plant (0.283). This trait
showed the maximum positive indirect effect
through yield per plant (0.281) followed by days to
first flowering (0.142), pod width (0.135), pod
length (0.069), days to maturity (0.060), and seeds
per pod (0.002). In contrast, this trait showed a
negative indirect effect on plant height (-0.070),
days to 50% flowering (-0.139), and pods per plant
(-0.200) (Table 3). Goulart et al. [44] investigated
pigeon pea (Cajanas cajan) varieties revealed that
100-grain weight had the highest positive direct
effect on grain yield.
3.3.10. Residual Effect
The residual effect of the present study was
0.054 indicating that 94.60% of the variability was
accounted for 10 yield contributing traits included
in the present study. The rest amount of the
110
J. Multidiscip. Appl. Nat. Sci.
(Bangladesh; Department of Crop Genetics and
Plant Breeding, Institute of Crop Science, Beijing
-100081 (China);
Nilufa Yasmin Poly — Department of
Biochemistry and Molecular Biology, Khulna
Agricultural
University,
Khulna-9208
(Bangladesh);
Nusrat Jahan — Department of Plant
Pathology, Sylhet Agricultural University, Sylhet
-3100 (Bangladesh);
variability might be controlled by other yield
contributed traits that were not included in the
present investigation.
4. CONCLUSIONS
Based on the findings of the present
investigation, it can be concluded that the analysis
of variance revealed that all the characters showed
significant differences between the treatments.
Phenotypic coefficients of variation (PCV) were
close to genotypic coefficients of variation (GCV)
for all the characters. High heritability associated
with high genetic advance per mean was observed
for plant height, pod per plant, hundred seed
weight, and seed yield per plot. The correlation
analysis revealed that seed yield per plant showed a
positive and significant correlation with the
characters' days to maturity, plant height, and pods
per plant and seeds per pod at both genotypic and
phenotypic levels. Days to fifty percent flowering,
plant height, pods per plant, pod length, pod width,
100 seed weight showed positive direct effects on
yield per plant. Hence, yield improvement in pea
would be achieved through the association and
selection of these characters. We can observe the
days to maturity, plant height, pods per plant, pod
length, and seed showed a considerable positive and
highly significant correlation with both genotypic
and phenotypic levels indicating yield could be
increased with the increase of the best performance
in the experiment.
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AUTHOR INFORMATION
Corresponding Author
Ahasan Ullah Khan — Department of
Entomology, Sylhet Agricultural University,
Sylhet-3100 (Bangladesh); Department of
Agroforestry and Environmental Science, Sylhet
Agricultural
University,
Sylhet-3100
(Bangladesh);
orcid.org/0000-0002-7029-8215
Email: ahasanullahsau@gmail.com
Authors
Sarah Tasnim — Department of Genetics and
Plant Breeding, Bangabandhu Sheikh Mujibur
Rahman Agricultural University, Gazipur-1700
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