Qualitative and Quantitative Traits Associate Genetic Variability of Soybean (Glycine max) Mutants for Expedited Varietal Improvement Program

Abstract

Background: Soybean is an excellent source of protein, also richer in oil than most legumes, making them a good source for
vegetable oil and biofuels. Among various difficulties the maturity period of existing soybean varieties is the main hindrance of
utilizing this for the existing cropping system. The narrow genetic base of cultivated soybean varieties and germplasm limit the
scope to utilize directly in the breeding program.
Methods: Mutation breeding is one of the techniques that provide large genetic diversity from a single source. To broaden the
genetic diversity Binasoybean-3 and Binasoybean-4 were imposed to different doses of gamma radiation. The mutants were selected based on their agronomic performance and grouped at five different clusters at M5 generations. Maximum selection pressure was done during maturity period with protein and oil content.
Result: Finally, eight mutants were selected for the advance breeding program, whereas mutants SM-03-15-5 mature within 90 days, containing 38% protein and 18.4% oil content will be considered directly for further steps of varietal release system.

Full text

Volume Issue 1
LRF-735
[1-6]
RESEARCH ARTICLE Legume Research- An International Journal, Volume Issue : ()
Qualitative and Quantitative Traits Associate Genetic Variability
of Soybean (Glycine max) Mutants for Expedited Varietal
Improvement Program
Md. Amirul Alam1, M.S.H. Bhuiyan2, M.A. Malek2,
R.M. Emon2, Khadija Khatun2, Humayun Kobir3 10.18805/LRF-735
ABSTRACT
Background: Soybean is an excellent source of protein, also richer in oil than most legumes, making them a good source for
vegetable oil and biofuels. Among various difficulties the maturity period of existing soybean varieties is the main hindrance of
utilizing this for the existing cropping system. The narrow genetic base of cultivated soybean varieties and germplasm limit the
scope to utilize directly in the breeding program.
Methods: Mutation breeding is one of the techniques that provide large genetic diversity from a single source. To broaden the
genetic diversity Binasoybean-3 and Binasoybean-4 were imposed to different doses of gamma radiation. The mutants were selected
based on their agronomic performance and grouped at five different clusters at M5 generations. Maximum selection pressure was
done during maturity period with protein and oil content.
Result: Finally, eight mutants were selected for the advance breeding program, whereas mutants SM-03-15-5 mature within 90
days, containing 38% protein and 18.4% oil content will be considered directly for further steps of varietal release system.
Key words: Correlation coefficients, Mutation breeding, Oil content, Protein, Soybean, Trait selection.
INTRODUCTION
Sharply increasing trend of the world population with limiting
cultivable land and changing climates creates continuous
pressure on food security (Brivery et al., 2021). It provides
additional pressu re to ensure SDGs (Sustainable
Development Goals) second goal (United Nation, 2015)
whereas by the end of 2050 earth’s population is predicted
to reach 9.8 billion demands for major cereals will increase
three-fold with doubling the requirements of animal-sourced
food (ASF) Ittersum et al., (2016). Considering various uses
of soybean products, the projected demand for this grain
will be 371.3 million metric tons in 2030 with a 1.8% annual
growth rate (Siamabele, 2021). The development of higher
yield potential soybean variety is the main focus for soybean
breeders to ensure food security of this century (Kuchlan
and Kuchlan, 2023). A narrow genetic base is the major
threat to varietal improvements of soybean. Using pedigree
relationships Gizliceet et al., (1994) showed that 35
ancestors contributed to 95% of genes of mostly cultivated
soybean in North America. For crops with a limited genetic
base like soybean, an efficient strategy is using mutation
breeding that enhances the modification of a few traits
without altering the remaining genotype. Mutation breeding
techniques have been used widely to improve desirable traits
like as seedcoat color (Tsuda et al., 2015), redu ced
Lipoxygenase (Lee et al., 2013) seed yield and oil quality
(Lakhssassi et al., 2017) of soybean. Considering the
remarkable success of the mutation technique in soybean
trait development, reported research was conducted to focus
mutation induced genetic variability for various genetic
parameters of soybean and their utilization in the future
varietal development process.
MATERIALS AND METHODS
Binasoybean-3 and Binasoybean-4 are two soybean
varieties developed by the Bangladesh Institute of Nuclear
Agriculture (BINA), Mymensingh was subjected to 150 Gy,
250 Gy, 350 Gy and 450 Gy doses of gamma radiation in
2017. Continuous selection was done from M2 to M4
1Faculty of Sustainable Agriculture, Horticulture and Landscaping
Program, Universiti Malaysia Sabah, Sandakan Campus, Sandakan
90509, Sabah, Malaysia.
2Plant Br eeding Divis ion, Bangladesh Institute of Nuclear
Agriculture, Mymensingh-2202, Bangladesh.
3Additional Agriculture Officer, Control Room, DAE, Khamarbari,
Dhaka.
Corresponding Author: Md. Amirul Alam, Faculty of Sustainable
Agriculture, Horticulture and Landscaping Program, Universiti
Malaysia Sabah, Sandakan Campus, Sandakan 90509, Sabah,
Malaysia. Email: amirulalam@ums.edu.my
How to cite this article: Alam, M.A., Bhuiyan, M.S.H., Malek, M.A.,
Emon, R.M., Khatun, K. and Kobir, H. (2023). Qualitative and
Quantitative Traits Associate Genetic Variability of Soybean (Glycine
max) Mutants for Expedited Varietal Improvement Program. Legume
Research. doi:10.18805/LRF-735.
Submitted: 03-01-2023 Accepted: 27-05-2023 Online: 13-06-2023

Legume Research- An International Journal
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Qualitative and Quantitative Traits Associate Genetic Variability of Soybean (Glycine max) Mutants for Expedited Varietal...
generation. Twenty-three genotypes have been selected
from the M4 generation, which was considered as material
for this experiment (Table 1).
The experimental site, design and management
The experimental was conducted at BINA, Mymensingh
following randomized complete block design with three
replications. Sowing was done within the second week of
January 2021 Rabi Season. Spacing between plants in a row
was 8-10cm, whereas 25 cm for each row. Unit plot size was
16 m2 (4 m4 m). Recommended management were followed
to ensure proper growth and development of plants.
Data analyses
From each experimental unit randomly selected 15 plants
were considered as a sample. Data on various quantitative
characters such as days to maturity (days), plant height
(cm), number of branches plant-1(no.), pods plant-1 (no.),
pod length (cm), seeds pod-1 (no.) were taken from selected
sample of each experimen tal unit. Geno typic and
Phenotypic Variability with Coefficient of Genotypic and
Phenotypic Variation, heritability and genetic progress was
calculated using the formula developed by Steel et al.
(1997). The heat maps were created using online
heatmapper tool (www2.heatmapper.ca) whereas box plots
were designed by RStudio. Protein content was determined
by the formula of Beljkas et al. (2010) and oil content by
Arnoid et al. (1944).
RESULTS AND DISCUSSION
Genotypic mean sum of square for days to maturity, plant
height, pods plant-1, thousand seed weight and seed yield
showed highly significant (P<0.01) variations among the
mutant and parents (Table 2). The CV range varied from 1.2
to 22.47. Maximum CV values were obtained from seed yield
followed by thousand seed weight, whereas a minimum CV
value was carried out by seeds pod-1 followed by branches
plant-1. Genotypic (2g) and phenotypic variance (2p) with
phenotypic (PCV) and genotypic (GCV) coefficients of
variation follow similar patterns.
The genotypic (2g) variance ranges from 0.06 to
5956.18 and phenotypic (2g) variance ranges from 0.18 to
6028.46. The maximum genotypic (2g) and phenotypic
variance (2p) were obtained from seed yield followed by
pods plant-1 and days to maturity. The mode of expression of
genotypic (GCV) and phenotypic (PCV) coefficients were like
genotypic (2g) and phenotypic variance (2p) that indicate
higher phenotypic variance and coefficients than genotypic
variance and coefficients. Although the CV% was higher for
the seed yield (Kg/ha), it might be due to the diversity of the
genotypes studied here. Another supremacy of mutation
Table 1: List of genotypes considered in this research selected from M4 generations.
Name of the mutants Parent Dose (Gy) Name of the mutants Parent Dose (Gy)
SB-03-15-27 Binasoybean-3 150 SB-04-15-21 Binasoybean-4 150
SB-03-15-67 Binasoybean-3 150 SB-04-15-4 Binasoybean-4 150
SB-03-15-37 Binasoybean-3 150 SB-04-20-9 Binasoybean-4 200
SB-03-15-5 Binasoybean-3 150 SB-04-20-21 Binasoybean-4 200
SGB-03-20-7 Binasoybean-3 200 SB-04-20-11 Binasoybean-4 200
SB-03-25-41 Binasoybean-3 250 SB-04-20-3 Binasoybean-4 200
SB-03-25-5 Binasoybean-3 250 SB-04-25-3 Binasoybean-4 250
SB-03-25-15 Binasoybean-3 250 SB-04-35-2 Binasoybean-4 350
SB-03-30-9 Binasoybean-3 300 Binasoybean-3 Wield Parent -
SB-03-30-10 Binasoybean-3 300 Binasoybean-4 Wield Parent -
SB-03-35-20 Binasoybean-3 350 BARI Soybean-5 Check Variety -
SB-04-15-19 Binasoybean-4 150 Total 23
Table 2: Estimates of genetics parameters for different quantitative and qualitative characters.
Trait GMS CV (%) 2g2P (GCV) (PCV) h2b GA GA (%)
Days to maturity 458.53 7.51 145.89 166.75 10.47 11.20 87.49 23.27 20.18
Plant height 378.18 9.18 115.68 146.80 17.87 20.13 78.80 19.66 32.68
Branch/plant 1.24 2.4 0.42 0.41 26.43 26.29 78.58 1.32 14.45
Pods/plant 439.79 3.4 146.17 146.71 23.13 23.48 79.84 14.93 34.64
Seeds/pod 0.54 1.2 0.06 0.18 17.79 17.11 82.32 4.4 15.26
Pod length 0.71 8.9 0.14 0.89 10.46 17.72 34.90 6.53 12.74
Thousand seed wt. 175.09 13.95 34.39 86.30 6.77 11.90 32.35 6.12 7.49
Seed yield (kg/ha) 79353.21 22.47 5956.18 6028.46 25.46 25.75 67.54 48.16 52.76
Oil (%) 11.49 3.37 2.43 6.62 8.64 14.26 38.34 3.94 10.79
Protein (%) 1.25 6.54 1.25 6.13 3.06 7.00 19.78 1.67 2.76

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Qualitative and Quantitative Traits Associate Genetic Variability of Soybean (Glycine max) Mutants for Expedited Varietal...
breeding is its ability to crate narrow genetic difference with
higher heritability, that was reflected in this study.
The genotypic coefficient of variation ranged from 6.77
to 26.29 which indicates considerable variation among the
character studied. Out of eight traits higher genotypic coefficient
of variation was observed on branches plant-1, seed yields and
pods per plant (26.29, 25.46 and 23.13, respectively). Highest
PCV (28.48) were shown for pods plant-1 followed by branches
plant-1 (26.43) and seed yield (25.75). The difference between
GCV and PCV was higher for pod length, thousand seed weight
and pods plant-1. On the others the lowest difference was
performed by the trait’s days to maturity and plant height,
whereas it was minimum for branches plant-1, seeds pod-1 and
seed yield (Table 2). Estimates ranged of broad sense
heritability were 32.35 to 87.49. More than 80% heritability was
obtained from days to maturity, branches plant-1, pods plant-1,
seeds pod-1 and it was above 60% for plant height and seed
yield. Heritability combined with genetic advance guided more
accurate selection efficiency than heritability alone. Genetic
advance was maximum for seed yield (48.16) whereas the
maximum genetic advanced over mean was also higher for
seed yield followed by pods plant-1, plant height and lowest for
thousand seed weight.
The genotypic correlations were higher than phenotypic
correlations with some exceptions (Table 3). For the number
of branches plant-1 phenotypic correlations were higher with
number of pods plant-1 (0.61), seeds pod-1 (0.43) and pod
length (0.80). Plant height has a significant positive relation
with number of pods plant-1 and negative relation with pod
length and thousand seed weight for both genotypic and
phenotypic correlations with higher genotypic values. A total
number of pods plant-1 has a strong relation with branches
plant-1, plant height and reveres relation with thousand seed
weight. The yield had a highly significant positive correlation
with number of pods plant-1, seeds pod-1and thousand seed
weight. In case of yield maximum genotypic correlations
were obtained from number of pods plant-1 (0.87), thousand
seed weight (0.46) followed by number of seeds pod-1.
Selection of superior genotypes
The first three traits accounted eigen values were more than
one and it was maximum for days to maturity (2.595) and
minimum eigen values was obtained from seed yield (0.255,
Table 4). Similarly, days to maturity contributed 32.4% of
the total variation followed by plant height (19.5). The lowest
percentage of variation was obtained from seed yield (3.2%,
Table 4).
Considering the performance eight traits of studied
soybean genotypes were grouped into five clusters (Table 5
and Fig 1). The number of genotypes ranged from 2 to 10 in
Table 4: Eigen values, percent of variation and total variation contribution of 8 characters of 23 genotypes of soybean.
Principal component characters Eigen values Percent of total variation Cumulative variation
Days to maturity 2.595 32.4 32.4
Plant height (cm) 1.560 19.5 52.0
Branch/plant 1.118 14.0 65.9
pods/plant 0.956 12.0 77.9
Seeds/pod 0.567 7.1 85.0
Pod length 0.553 6.9 91.9
Thousand seed wt 0.392 4.9 96.8
Seed yield (kg/ha) 0.255 3.2 100.0
Table 3: Correlation coefficients of pair’s genetic parameters for yield associated quantitative characters of soybean.
Traits PH NBP NPP NSP PL TW Yield
DM rg0.22 -0.41 0.12 -0.41* 0.05 -0.04 0.09
rp0.18 -0.38** 0.39** -0.11 0.43 0.06 0.08
PH rg-0.24 0.67** 0.30 -0.43 * -0.58** -0.33
rp-0.21 0.59** 0.27* -0.21 -0.32** -0.29*
NBP rg0.41* 0.14 0.01 0.18 -0.14
rp0.61** 0.43 0.96 0.10 -0.14
NPP rg0.20** -0.15 -0.14* -0.07
rp0.02 -0.09 -0.08* -0.01
NSP rg0.55** 0.82** 0.20*
rp0.32** 0.47** 0.73**
PL rg0.80** 0.24
rp0.58** 0.14
TW rg0.46*
rp0.27*
** Significant at P0.01 and * Significant at P0.05.

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Qualitative and Quantitative Traits Associate Genetic Variability of Soybean (Glycine max) Mutants for Expedited Varietal...
different clusters. The distribution pattern indicated that the
maximum number of test genotype 10 was grouped into cluster
II (43.48%), 6 genotypes in cluster V (26.08%) and V (6)
followed by 3 genotypes in cluster IV (13.04%). Cluster I and
cluster III contained the lowest (2) number of genotypes and
that was 8.70% of the total population. Seed yield and maturity
period were a main focus for the present circumstance of
Bangladesh. Based on yield (about 3000 kg ha-1) and maturity
period (around 100 days), eight genotypes were selected. SB-
04-15-4 (3380 kg ha-1) ensures maximum seed yield, whereas
SB-03-15-5 (93 days) matures earlier than others (Fig 2).
Varietal response against radiation was not uniform
because that mutation can cause genomic instability in cells
by altering the number of c opies of the genome,
amplification, rearrangement and deletion of genes (Morgan
et al., 2003). Mutants obtained from different parents with
Table 5: List of distributed genotypes in different clusters with their percentage over total genotypes.
Cluster Number of Percentage of Name of genotype
number genotypes genotype
I 2 8.70 SB-03-35-20, SB-04-15-21
II 10 43.48 SB-03-15-27, SB-03-15-67, SB-03-15-5, SB-03-20-7, SB-03-25-41, SB-03-25-5, SB-
03-25-15, SB-03-30-9, SB-04-20-9, SB-04-20-21
III 2 8.70 SB-03-15-37, SB-04-15-19
IV 3 13.04 SB-04-15-4, SB-04-20-3, SB-04-25-3
V 6 26.08 SB-04-20-11, SB-04-35-2, SB-03-30-10, Binasoybean-3, Binasoybean-4, BARI
Soybean-5
T
he red and blues colors in the legend indicate highest and lowest values, respectively. DM=
Days
to maturity, PH=Plant height (cm), NPB=Number of prim ary branches plant-1, NP=Number of
pods plant-1, NSP=Number of seed pod-1, TW=Thousand seed weight (g) and SY= Seed yield.
Fig 1: Heatmap representations of 23 soybean genotypes into different clusters.
Fig 2: Performance of 23 soybean genotypes considering seed yields and maturity period.
different does place in one group. In group II, there were
ten genotypes; out of them, eight were obtained from
Binasoybean-3 and two from Binasoybean-4. Two parents
and check variety BARI soybean-5 was in the same group
(V) indicating they originated from the similar genetic
background. Presence of the other three mutants in group
V (SB-04-20-11, SB-04-35-2 and SB-03-30-10) indicates the
narrow genetic distance with the existing soybean variety of
Bangladesh. Continuous selection pressure from existing
germplasm is responsible for narrowing the genetic background
of existing soybean cultivars. Considering the pattern-based
cropping system, soybean breeder needs to consider
maximum yield with a minimum maturity period. Soybean
mutants SB-03-15-5, SB-03-15-7, SB-03-25-5, SB-03-25-15,
SB-03-30-10, SB-04-15-19, SB-04-15-4 and SB-04-20-3
provide maximum yield and the mature around 100 days.

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Qualitative and Quantitative Traits Associate Genetic Variability of Soybean (Glycine max) Mutants for Expedited Varietal...
The protein and oil content of these eight genotypes
were selected based on yield potential and maturity period
with two parents (SB-03-15-5, SB-03-15-7, SB-03-25-5, SB-
03-25-15, SB-03-30-10, SB-04-15-19, SB-04-15-4, SB-04-
20-3, Binasoybean-3 and Binasoybean-4) showed
significant different (Fig 3 and 4). Maximum protein content
was obtained from SB-03-15-7 (40%) which was statistically
identical with SB-04-15-19 (39.2%) followed by SB-03-15-5
(38%), on the others lowest protein content was obtained
from the parent Binasoybean-4 (32.8%). Accordingly
maximum oil content was obtained from SB-04-15-4 (19%)
and SB-04-20-3 (19.2%) followed by SB-03-15-5 (18.4%).
The success of mutation breeding for developing early
maturity with higher yield soybean mutants was supported
by Malek et al. (2022) and Nilahayati et al. (2019). The
positive responses of mutation breeding regarding maturity
were also found in sesame (Bhuiyan et al., 2019), lentil
(Laskar et al., 2017) and in linseed (Terfa et al., 2020) that
support the effectiveness of mutation breeding towards
specific trait improve. KEX-2 and Bangsakong are the two
mutant soybean varieties developed by Korea Atomic Energy
Research Institute that ensures 30% and higher, whereas
Josaengseori (mutant of soybean) led to 2.4 times higher
seed yield than their parent. Among this KEX-2 also matured
(A = SB-03-15-5, B = SB-03-15-7, C = SB-03-25-5, D = SB-03-25-15, E = SB-03-30-
10,
F = SB-04-15-19, G = SB-04-15-4, H = SB-04-20-3, I = Binaso ybean-3 and J =
Binasoybean-4). Same letter(s) do not differ signific antly at 5% level of significance.
Fig 4: Oil content (%) of selected soybean mutant with their
parents.
11 days earlier than the original cultivar (Ha et al., 2014).
Both protein and oil content were higher at the mutant SB-
03-15-5, moderate at SB-03-15-7 and higher protein and low
oil content at SB-04-15-19. Generally, there was a negative
relation between oil and protein content that was contradictory
to this result but fully support by Deswal et al. (2015), where
they found mutation increased protein and oil content of the
same genotypes. This is the beauty of mutation, which has a
tremendous ability to change alleles without affecting the
linked gene (Yao et al., 2023). Patil et al. (2017) finds out that
Glycine max is the main source of various high-protein alleles.
Two parents of this study were also from Glycine max. Prenger
et al. (2019) mention that deletion on chromosome 12 was
associated with increased protein content using mutation on
two soybean genotypes (G00-3213 and G00-3880) and their
work fully supports our findings.
CONCLUSION
Based on the genetic variability and coefficient study it was
found that plant height, maturity period and pods plant-1
was the most dominant yield contributing traits of soybean.
Based on agronomic trait, performance studied genotypes
were grouped into five clusters. Considering overall
performance and protein contain SB-03-15-5, SB-03-15-
7, SB-03-25-5, SB-03-25-15, SB-03-30-10, SB-04-15-19,
SB-04-15-4 and SB-04-20-3 have been selected for future
advancement. Among them SB-03-15-5, SB-03-25-5 and
SB-03-25-15 will be used for advanced breeding trials,
whereas SB-04-15-19, SB-04-15-4, SB-04-25-3 and SB-
04-35-2 will be used as parent material for varietal
improvement program.
ACKNOWLEDGEMENT
The authors sincerely acknowledge Bangladesh Institute of
Nuclear Agriculture (BINA) and the Faculty of Sustainable
Agriculture, Universiti Malaysia Sabah for all the supports for
conducting the study and publishing the research findings.
Fig 3: Protein content (%) of selected soybean mutant with their parents.
(A = SB-03-15-5, B = SB-03-15-7, C = SB-03-25-5, D = SB-03-25-15, E = SB-03-30-10,
F = SB-04-15-19, G = SB-04-15-4, H = SB-04-20-3, I = Binasoybean-3 and J =
Binasoybean-4). Same letter(s) do not differ significantly at 5% level of significance.

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Declaration of competing interest
The authors declare that they have no known competing
financial interests or personal relationships that could have
appeared to influence the work reported in this paper.
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