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Article

Evaluation of the Impact of Chemical Mutagens on the Phenological and Biochemical Characteristics of Two Varieties of Soybean (Glycine max L.)

by
Anas Hamisu
1,
Bhupendra Koul
1,*,
Ananta Prasad Arukha
2,
Saleh Al Nadhari
3 and
Muhammad Fazle Rabbee
4,*
1
Department of Botany, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara 144411, Punjab, India
2
Department of Nephrology and Hypertension, Mayo Medical Sciences, Rochester, MN 55902, USA
3
Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia
4
Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea
*
Authors to whom correspondence should be addressed.
Life 2024, 14(7), 909; https://doi.org/10.3390/life14070909
Submission received: 27 May 2024 / Revised: 5 July 2024 / Accepted: 18 July 2024 / Published: 22 July 2024
(This article belongs to the Special Issue Effects of Environmental Factors on Challenges of Plant Breeding)

Abstract

:
Mutagenic effectiveness and efficiency are the most important factors determining the success of mutation breeding, a coherent tool for quickly enhancing diversity in crops. This study was carried out at Lovely Professional University’s agricultural research farm in Punjab, India, during the year 2023. The experimental design followed a randomized complete block design (RCBD) with three replications. The experiment aimed to assess the effect of three chemical mutagens, sodium azide (SA), ethyl methyl sulphonates (EMSs), and methyl methane sulfonate (MMS), at three different concentrations (0.2%, 0.4%, and 0.6%), in SL958 and SL744 soybean varieties to select the mutant exhibiting the highest yield. The data were collected and analysed using a two-way ANOVA test through SPSS software (version 22), and the means were separated using Duncan’s multiple range test (DMRT) at the 5% level of significance. Between the two varieties, the highest seed germination percentage (76.0% seedlings/plot) was recorded in SL958 (0.4% SA), while the lowest (30.33% seedlings/plot) was observed in 0.6% MMS as compared to the control (53% and 76% in SL744 and SL958 at 10 days after sowing, respectively). Several weeks after sowing, the average plant height was observed to be higher (37.84 ± 1.32 cm) in SL958 (0.4% SA) and lower (20.58 ± 0.30 cm) in SL744 (0.6% SA), as compared to the controls (SL958: 26.09 ± 0.62 cm and SL744: 27.48 ± 0.74 cm). The average leaf count was the highest (234.33 ± 3.09 tetrafoliate leaves/plant) in SL958 (0.4% SA) while it was the lowest (87 leaves/plant) in 0.6% MMS as compared to the control (SL744 180.00 ± 1.63 and SL958 160.73 ± 1.05). The highest total leaf areas recorded in the SL958 and SL744 M1plants were 3625.8 ± 1.43 cm2 and 2311.03 ± 3.65 cm2, respectively. Seeds of the SL958 variety treated with 0.4% SA resulted in the development of tetrafoliate leaves with a broad leaf base and the maximum yield (277.55 ± 1.37 pods/plant) compared to the narrow pentafoliate leaves obtained through the treatment with EMS. Meanwhile, in the SL744 variety, the same treatment led to tetrafoliate leaves with a comparatively lower yield of 206.54 ± 23.47 pods/plant as compared to the control (SL744 164.33 ± 8.58 and SL958 229.86 ± 0.96). The highest protein content (47.04 ± 0.87% TSP) was recorded in the SL958 (0.4% SA) M2 seeds followed by a content of 46.14 ± 0.64% TSP in the SL744 (0.4% SA) M2 seeds, whereas the lowest content (38.13 ± 0.81% TSP) was found in SL958 (0.6% MMS). Similar observations were recorded for the lipid and fibre content. The 0.4% SA treatment in SL958 proved to be efficient in generating the highest leaf area (tetrafoliate leaves) and a reasonable yield of M1 (the first generation after mutation) plants.

1. Introduction

The term plant mutation is used to describe a sudden heritable change in the genetic material of a plant at the gene and chromosome level. Mutations are the tools used to study the nature and function of genes, which are responsible for quality traits (disease resistance, early maturation, semi-dwarfism, etc.) and quantity traits (increased seed productivity, seed weight, biomass, oil content, etc.) in crops, thus acting as means for the genetic improvement of economic crops [1,2]. Mutation breeding (variant breeding) is a technique for creating novel crop varieties by inducing genetic diversity in plants using chemical or physical techniques [1,2].
The advantages of mutation breeding are as follows: (i) the improvement of economic traits and quality characteristics in crops within a short period of time, (ii) traits can be transferred from a mutant variety to its offspring, (iii) the technique is simple and inexpensive, (iv) reliable, and (v) hazard-free and environment-friendly. Its disadvantages include the following: (i) it requires stringent screening for the mutant with the desired trait, (ii) there is a chance of unpredictable outcomes due to random genetic recombination, and (iii) its success relies on the desired qualities being present in the current gene pool [3,4].
There are two types of mutagens: (i) physical mutagens, including (a) ionizing (particulate: alpha, beta, fast, and thermal neutrons; non-particulate: X-rays and gamma rays) and (b) non-ionizing (UV-rays); and (ii) chemical mutagens, such as (a) alkylating agents: EMS (ethyl methane sulfonate), MMS (methyl methane sulfonate), and mustard gas; (b) deamination agents (nitrous acid); (c) base analogues (5-bromouracil and 2-aminopurine); (d) acridines (acriflavine and proflavin); and (e) other chemicals (hydroxylamine and sodium azide). Chemical mutagens are easy to handle, readily available, inexpensive, cost-effective, more efficient, and have a greater specificity than physical mutagens [5]. The genetic makeup of economic crops has been improved by mutation breeding along with a significant increase in crop production. The improvement of economic traits and quality characteristics for the improvement of crops within a short period can be achieved with the help of induced mutagenesis. Induced morphological mutants are useful for the development of improved varieties when they are used in cross-breeding programs [6].
Despite their benefits and drawbacks, mutagens have been used to create several better cultivars of many crops, including a wheat mutant (Sharbati Sonora) of an amber-coloured grain variety with a higher protein and lysine content developed through gamma irradiation [7]; a rice mutant of the TEMB-1 variety with a semi-dwarf phenotype (90–95 cm) that matures early (130–135 days), lodging-resistant, aromatic, and has a high yield (4.5–5 tons per ha) [8,9]; a barley mutant of the diamant variety with large kernels that matures early and has high yields [10]; a soybean mutant of the TGX-1954 variety that matures early, drought tolerant, disease resistant, and has a higher yield [11]; a chickpea mutant of the BGM-413 variety that is salinity tolerant, tastes good, can be used in cooking, matures early, has a high yield, and has a high protein content [12]; a cotton mutant of a virescent variety with early maturation, disease resistance, drought tolerance, and a higher yield capacity [13]; a sugar cane mutant of the Co0238 variety that has a high fibre content (13.05%) [14]; a tea mutant that is early sprouting, resistant to disease, and suitable for fine green tea developed through irradiation (Co60c) [15]; and a vegetable mutant of the Capsicum annum variety with a high yield, increased vitamin content, and disease resistance [16,17]. Thus, many features, including yield, lodging resistance, disease resistance, maturity, culm length, etc., have been developed through mutation breeding.
The soybean (Glycine max (L.) Merrill) is known as the “golden bean” and the “miracle crop” of the twenty-first century. It contains high-quality oil (20%), protein (40%), starch (36–40%), vitamins A, B, and D, 6–7% minerals (calcium, iron, manganese, phosphorus, copper, and thiamine), 8–10% fibre, and phytochemicals such as flavonoids, saponins, alkaloids, steroids, and tannins [18].
In India, soybean is also used in various food products, including tofu, soya sauce, simulated milk, and meat products, and the oil is frequently used for cooking [19]. Soybean meal is used as a supplement in livestock feed. Apart from this, it is used in industries for the production of biofuels and functional foods [20]. The industrial use of soybeans ranges from the production of yeasts and antibodies to the manufacture of soaps and disinfectants [21]. The top five soybean-producing nations worldwide are Brazil (120.7 MT), the United States (116.4 MT), Argentina (43.9 MT), China (20.3 MT), and India (13 MT). More than 90% of the world’s production comes from these countries [19]. India is the fifth largest soybean-producing country in the world. Madhya Pradesh, Rajasthan, and Maharashtra contribute 88% of the country’s total soybean production [20]. Soybean can play an important role in crop diversification in Punjab, provided it is able to compete with paddy, wheat, and cowpea in terms of economics. Yellow mosaic is a serious disease in the northwest’s plains, causing yield losses up to 80 percent. Thus, the development of high-yielding and yellow-mosaic-resistant varieties is the main breeding objective of the soybean breeding programme at Punjab Agricultural University, Ludhiana, India. The two most recent varieties, SL958 and SL744, have been released. These have medium levels of maturity, are non-shattering, have a light yellow grain with a grey hilum, and are resistant to the yellow mosaic virus [22,23].
In the 1970s and 1980s, as reported by the International Food Policy Research Institute, Punjab was among the highest producers of soybean with a net domestic product (NDP) of 5.1–6.1 MT on average compared to the national average of 3.4 for India [24]. Agriculture in Punjab is limited to wheat and rice, which has resulted in the excess mining of underground water resources for irrigation. Over the past 54 years, this has lowered the water table to the extent of 15 cm per year. Soybean production might serve as a supplement or as part of crop rotation, since it requires a lower amount of water.
This study assesses the impact of three chemical mutagens, sodium azide, ethyl methyl sulphonates, and methyl methane sulphonate, on the two aforementioned soybean varieties through field trials, with the aim of unveiling their potential to generate genetic variability and screening the improved soybeans with a higher yield potential.

2. Materials and Methods

2.1. Seed Procurement and Germination Test

Soybean seeds were obtained from Punjab University of Agriculture, Ludhiana, India (30.9041° N latitude and 75.8066° E longitude). Two soybean varieties (SL958 and SL744) were selected based on their characteristics, including their high yield, medium level of maturity, and soil preference. A germination test was conducted by broadcasting a hundred seeds of SL744 and SL 958 in two earthen pots filled with fertile organic soil. Following the placement of seeds, a light covering of soil was applied, and the pots were consistently watered. Germination percentage was closely observed over five days, with results indicating up to 95% germination. The cleared and manually ploughed site for seed production was laid out according to the experimental plot design (RCBD) measuring 8 × 60 m2, and seeds were sown accordingly.

2.2. Mutagens’ Procurement and Seed Treatments

Chemicals were obtained from Loba chemie Pvt. Ltd., Mumbai, India. The seeds were soaked in distilled water for 6 h and later on treated with ethyl methane sulphonate (EMS), methyl methane sulfonate (MMS), and sodium azide (SA) for 6 h. They were immersed at different concentrations (0.0%, 0.2%, 0.4%, 0.6%) of three chemicals, respectively. The 0.0% concentration was the control. Fifty mL phosphate buffer solution was added to each treatment so as to maintain the osmotic content of the cell at pH of 3. Another set of seeds were soaked in distilled water and phosphate buffer solution as a control. The procedure was periodically repeated at room temperature (25–30 °C). After the end of the treatments, seeds were extensively rinsed with running tap water approximately 8–10 times. Subsequently, both treated and untreated control seeds were sown in the field using a randomized complete block design with three replications to induce mutation generation [25].

2.3. Field Location and Experimental Design

The research was carried out at Lovely Professional University’s agricultural research farm (31.3192° N latitude and 75.5723° E longitude) during the year 2023. The area lies within the sub-tropical belt in Northwest India. Semi-arid deserts of Rajasthan lie towards the southern border. It is characterized by three major seasons: summer (April to June); rainy (July to September); and winter (October to March). The climate ranges from sub-humid (northeast) to semi-arid (southwest), with harsh winters and summers. The area is characterised by sandy loam soil. Temperature ranges from −4 °C to 47 °C. Average annual rainfall is 650 mm. The land area measuring 620 m2 was divided into 60 plots (3 columns of 20 plots each), each measuring 2 × 1.5 m2, with a spacing of 0.75 m between plots and 1 m gap (as irrigation channel) between replications (Figure 1). Each plot consisted of four ridges that were spaced 0.37 m apart, with the two innermost ridges serving as net plots. The rows’ alley was used for destructive and non-destructive sampling, while the border rows were used for discard sampling. The experimental design followed a randomized complete block design (RCBD) with three replications.
Before planting, the soil was ploughed, harrowed, and ridged to remove debris, weeds, and clods for proper aeration and moisture for crop growth. Seeds were sown with a spacing of 75 cm on each ridge immediately after the rain during third week of May 2023.
Three seeds were manually sown per hole and later thinned into two plants per stand at 2 weeks after sowing (WAS). They were harvested manually using hoe and sickle. Physiologically matured pods were collected and sun-dried to reduce the moisture content, and later, manual threshing was carried out to separate the seeds from the chaff.

2.4. Plant Growth Characteristics

Various plant growth characteristics (seed germination, plant height, leaf number, leaf area, leaf variation, nodule counts, days to 50% flowering, and days to 50% podding) were recorded for the control and the M1 plants of two soybean varieties (SL744 and SL958) at the different stages of their growth after sowing.
For calculation of germination percentage, 96 seeds were sown in each plot. After seed germination, the seedlings were counted, and seed germination percentages were recorded for control and test plots (as shown in Figure 2), which were compared statistically. The seed germination percentages were used to plot the graphs (x axis: chemical treatments; y axis: seed germination percentage) using MS Excel version 13. Plant height was taken at intervals of 4, 8, and 12 weeks after sowing. Five plants were randomly selected from each plot, and their heights were measured from base to apex using a measuring tape. The average heights of the M1 plants were compared with those of the respective controls.
The number of leaves and leaf area per plant were also recorded at intervals of 4, 8, and 12 weeks after sowing. Five plants were randomly selected from each plot for leaf count and leaf area, and then average values were recorded for control and M1 plants of both varieties, which were later compared statistically. The leaf variation between the two varieties in the test plots was also studied at the aforementioned intervals, and the data were compared with the respective controls. The leaf chlorophyll content of the control and M1 plants was estimated at specific intervals (4, 8, and 12 weeks after sowing) from five randomly selected plants per plot (by inserting the measurement tool into the lower surface of the leaf and closing the head) using a SPAD meter (Minolta, Europe).
The numbers of days from sowing to 50% flowering and 50% podding among the control and test plots were also recorded and statistically compared. The harvested M2 seeds were evaluated in a biochemical analysis.

2.5. Biochemical Analysis Method

2.5.1. Estimation of Fiber Content (%)

For estimation of seed fibre content, two grams of the powdered seed sample (control and M1 seeds) of each variety (SL744 and SL958) was introduced into separate beakers followed by addition of distilled water (100 mL) and 10% H2SO4 (20 mL). The beaker was kept on a hot plate for 30 min. Thereafter, the suspension was filtered and then heated again using 1.25% NaOH for 30 min, filtered, and rinsed with hot water. It was allowed to drain, and the residue was scraped into a pre-weighed crucible (W1). It was then put into a muffle furnace to dry for 2 h at 600 °C, kept in a desiccator to cool, and weighed as W2 [26]. The percentage fibre content was then calculated as shown below:
Calculation:
W0 = Weight of empty crucible
W1 = Weight of crucible + residue
W2 = Weight of empty crucible + weight of residue after drying
% Crude fibre = (W1 − W2)/(W1 − W0) × 100

2.5.2. Determination of Protein Content (%)

Micro Kjeldahl method was used to analyse the protein content of the control and M1 seeds of each variety (SL744 and SL958), which involved three steps: digestion, distillation, and titration [26]. The % nitrogen (N) and crude protein content were calculated as mentioned below:
Calculation:
% Nitrogen (N) = (TV × NA × 0.014 × DF)/(volume of aliquot × sample weight) × 100
% Crude protein (g) = C.F × % N
where,
  • TV = Titre value
  • NA = Normality of acid
  • Sample weight = 2 g.
  • DF = Dilution factor
  • Vol. of aliquot = 10 mL
  • Conversion factor C.F = 6.25.

2.5.3. Determination of Lipid Content (%)

Two grams of the powdered seed sample (control and M1 seeds) of each variety (SL744 and SL958) were placed in separate labelled thimbles, and their mouths were covered with cotton wool. N-hexane (200 mL) was then added into the 250 mL extractor flask. The covered porous thimbles were placed in a condenser, and the Soxhlet apparatus was assembled. Extraction was allowed for about 5–6 h. Thereafter, the extracted sample in the thimbles was transferred into a dried crucible. The weight of the crucible and extracted sample was taken as W1. The crucible containing the sample was oven-dried at 105–110 °C for 1 h and later cooled in a desiccator, and the weight was taken as W2 [26]. The % weight of lipid was calculated as mentioned below:
Calculation:
W0 = Weight of empty crucible
W1 = Weight of crucible + grounded extracted sample (oil) before
W2 = Weight of empty crucible + weight of extracted sample (oil) after drying
% weight of lipid = (W2 − W1)/(W1 − W0) × 100

2.6. Statistical Analysis

The experimental data were collected from 5 randomly selected plants in each of the experimental plots (Figure 1). A two-way ANOVA was used to analyse the data through SPSS software (version 22), and the means were separated using Duncan’s multiple range test (DMRT) at 5% level of significance.

3. Results

3.1. Effect of Chemical Mutagens on Seed Germination

Data were recorded at three different periods (4DAS, 8DAS, and 10DAS) for the ten different treatments using the two varieties of soybean (SL744 and SL958) (Figure 2A,B). The highest seed germination percentage (76.0% seedlings/plot) was recorded in SL958 using 0.4% SA. The lowest value (30.33% seedlings/plot) was observed in SL958 using 0.6% MMS. The untreated control and treatment had same value (76% seedlings/plot) for SL958. However, in SL744, the % seed germination was higher (65.0% seedlings/plot) with 0.4% SA, and the lowest value (39.33.0% seedlings/plot) was observed in SL744 with 0.2% MMS compared to that of the control (53.0%).

3.2. Effects of Chemical Mutagens on Plant Height

The Table 1 shows the results of the effect of chemical mutagens on the plant heights of the control and M1 plants. The treatments differed significantly from each other and the untreated controls (p = 5%) in most of the data-recording periods. At 12 WAS, the T9-treated (0.4% SA) plots exhibited the highest plant height (37.84 ± 1.32 cm) for the SL958 variety, followed by T2 (35.06 ± 1.42 cm) with 0.2% EMS. Meanwhile, the lowest height (21.90 ± 0.63 cm) was recorded for T7 (0.6% MMS). Moreover, for the SL744 variety at 12 WAS, the T2 (0.2% EMS)-treated plots exhibited the highest plant height (24.80 ± 1.07 cm), and the lowest height was recorded for T10 (20.58 ± 0.30 cm) with 0.6% SA. These results, however, differed significantly from those of the untreated control plants (SL958: 26.09 ± 0.62 cm and SL744: 27.48 ± 0.74 cm).

3.3. Effect of Chemical Mutagens on Leaf Count

Data of leaf count were also collected from the same experimental plots to compare the effect of the three different chemical mutagens on the two soybean (SL744 and SL958) varieties, as shown in Table 2. The results showed that at four weeks after sowing (4 WAS), there were significant differences in the number of leaves among the treatments. This indicated that the chemical mutagens had a strong effect on the leaf count. However, at eight and twelve weeks after sowing (8 and 12 WAS), there was a highly significant difference in the number of leaves among the treatments, indicating that the treatments had a positive impact on the leaf count. At 4 WAS, the T7 treatment (0.6% MMS) caused a significant reduction in the number of leaves (17.47 ± 0.70 leaves/plant) in SL958, which was significantly different from the other treatments. At 8 and 12 WAS, the same treatment (0.6% MMS) exhibited the most significant reduction in the number of leaves (81.58 ± 4.03 leaves/plant and 87.00 ± 0.82 leaves/plant, respectively). These results differed significantly from those of all the treatments, including the untreated control plants (156.77 ± 1.05 leaves/plant and 160.73 ± 1.05 leaves/plant). At 12 WAS, the T9 treatment (0.4% SA) recorded the highest leaf count (234.33 ± 3.09 leaves/plant) in SL958. Similarly, in SL744, the highest leaf count (199.33 ± 2.62 leaves/plant) was observed in response to the T9 treatment (0.4% SA), which significantly differed from that of the untreated control plants (180.00 ± 1.63 and 160.73 ± 1.05).

3.4. Effect of Chemical Mutagens on Leaf Variation

Plant morphology is considered to be an important tool for the screening of desirable mutants. In our study, chemical mutagens caused the appearance of leaf abnormalities, including unifoliate, bifoliate, tetrafoliate, and pentafoliate characteristics (Figure 3A,B). Morphological changes, such as variations in leaf shape (broad and narrow leaves), were also observed in this study. Broad leaves were observed in the SL958 variety for 0.2% EMS (A: tetrafoliate), 0.2% MMS (G: tetrafoliate), 0.2% SA (D: pentafoliate), and 0.4% SA (H: tetrafoliate), while in the SL744 variety, broad leaves were observed for 0.2% EMS (J: tetrafoliate), 0.4% EMS (K: tetrafoliate), 0.6% MMS (O: trifoliate), 0.4% MMS (N: trifoliate), and 0.4% SA (Q: tetrafoliate).
Narrow leaves with pointed tips along with thinner stems were observed in SL958 for 0.4% EMS (B: pentafoliate), 0.6% EMS (C: trifoliate), 0.4% MMS (E: trifoliate), 0.6% MMS F: trifoliate), and 0.6% SA (I: trifoliate), in comparison to the untreated control plants. Meanwhile, in SL744, narrow leaves were observed for 0.6% EMS (L: tetrafoliate), 0.2% MMS (M: tetrafoliate), 0.2% SA (P: trifoliate), and 0.6% SA (R: tetrafoliate). It was interesting to note that in the pentafoliate leaves, the leaflets were much more narrow and the area was much more reduced than in their tetrafoliate counterparts, which had a broad leaf base.

3.5. Effect of Chemical Mutagens on Leaf Area (cm2)

Table 3 shows the results of the effect of the chemical mutagens on the leaf area of the control and M1 plants. The results revealed that at 4 WAS, the T9 plots (0.4% SA) recorded the highest leaf area (62.5 ± 0.82 cm2) in SL958, while the T7 plots (0.6% MMS) recorded the lowest (22.2 ± 0.00 cm2). Similarly, at 4 WAS, the T9 plots (0.4% SA) recorded the highest leaf area (61.06 ± 0.47 cm2) in SL744, while the T4 plots (0.6% EMS) recorded the lowest (22.72 ± 0.00 cm2).
However, at 8 WAS, the response in the T2 (0.2% EMS) plots differed significantly (p < 5%) from the untreated plots in having the highest leaf area (2628.4 ± 1.16 cm2) in SL958, while the T8 (0.2% SA) plots had the lowest (148.9 ± 0.50 cm2). In SL744, the T5 (0.2% MMS) plots recorded the highest leaf area (2042.6 ± 1.20), whereas the T4 plots (0.6% EMS) recorded the lowest (496.0 ± 1.08 cm2) leaf area. At 12 WAS, the results followed a similar trend. The T9 plot (0.4% SA) exhibited the highest leaf area (3625.8 ± 1.43 cm2) in SL958, while the T7 (0.6% MMS) plot recorded the lowest area (267.9 ± 1.09 cm2). In SL744, the T9 (0.4% SA) plots recorded the highest leaf area (2311.03 ± 3.65 cm2), whereas the T10 plots (0.6% SA) recorded the lowest (731.54 ± 1.11 cm2) leaf area compared to that of the untreated control (2190.6 ± 2.05 and 2256.6 ± 1.72).

3.6. Effect of Chemical Mutagens on Number of Days to 50% Flowering

The time (days) to reach 50% flowering for the untreated control and M1 plants is displayed in Table 4. In SL744 and SL958, the untreated control plants took the most number of days to reach 50% flowering (68.00 and 63.33 days, respectively), while the T9 (0.4% SA)-treated plants in SL958 took the least amount of time (39.67 ± 0.94 days). However, the T7-treated (0.6% MMS) M1 plants took the most number of days (50.33 ± 1.25 days) for the SL958 variety. Meanwhile, for SL744, T8 (0.2% SA) took the most number of days to reach 50% flowering (51.33 ± 0.47), while the T9 (0.4% SA)-treated plants for SL744 took the least amount of time (46.67 ± 1.70 days).
This revealed that the chemical mutagens at a low dose accelerated flowering in the M1 plants as compared to the untreated controls.

3.7. Effect of Chemical Mutagens on Podding

The time (days) to reach 50% podding in the untreated control and M1 plants is displayed in Table 5. It shows that the T9 (0.4% SA)-treated M1 plants of the SL958 variety exhibited early podding (69.00 ± 0.82 days) as compared to the untreated control plants (82.67 ± 1.25 days).
Similar results were observed for the T9 M1 plants of the SL744 variety, for which podding occurred at 77.00 ± 2.87 days, compared to the delayed podding of the untreated control plants (86.33 ± 0.94 days).
In terms of yield among both of the varieties, the highest yield (277.55 ± 1.37 pods/plant) was recorded for the M1 plants of the SL958 variety treated with 0.4% SA (T9), while the lowest (217.55 ± 2.20 pods/plant) was recorded for the T4 plants treated with 0.4% EMS compared to the untreated control (229.86 ± 0.96 pods/plant). However, in the SL744 variety, the highest yield (273.00 ± 4.55 pods/plant) was recorded for T4 (0.4% EMS), while the lowest (112.2 pods/plant) was observed in the SL744 variety treated with 0.2% EMS (T2). The results indicate that 0.4% SA effectively enhanced the yield of the SL958 variety.

3.8. Effects of Chemical Mutagens on Plant Chlorophyll Content (nmol/cm2)

Table 6 shows the effects of chemical mutagens on plant chlorophyll content at 4, 8, and 12 WAS. At 4 WAS, there was significant difference in chlorophyll content in the M1 plants of the SL744 variety, while for the SL958 variety, there was no significant difference among the T2 and T3; T6, T5, and T7; and T4, T8, T9, and T10 plots.
At 8 WAS, the chlorophyll content was found to be the highest (47.25 ± 3.07 nmol/cm2) in the T2 M1 plants (0.2% EMS) and the lowest (41.06 ± 4.06 nmol/cm2) in the T10 (0.6% SA) M1 plants of the SL744 variety. Meanwhile, in SL958, the highest chlorophyll content (45.76 ± 1.02 nmol/cm2) was found in the T9 plot and the lowest (40.97 ± 0.51) in the T10 plot.
However, at 12 WAS, among both of the varieties, the chlorophyll content was the highest (48.10 ± 0.71 nmol/cm2) in the T2 (0.2% EMS) plot of the SL958 variety and the lowest (41.33 ± 3.63 nmol/cm2) in the T7 (0.6% MMS) plot of the SL958 variety, which differed substantially from the control plants (39.54 nmol/cm2).

3.9. Effect of Chemical Mutagens on Protein, Lipid, and Fiber Content in M2 Seeds

Table 7 presents the percentages of protein, lipid, and fibre in the untreated control and M2 seeds. The results show that the T9 treatment (0.4% SA) recorded the highest protein percentage (47.04 ± 0.87%) in SL958 and lowest was recorded for the T7 treatment (0.6% MMS) (37.13 ± 0.0.72%) compared to the untreated control (39.87 ± 0.96%). However, in the SL744 variety, the highest (46.14 ± 0.64) was recorded in T9 (0.4% SA) and the lowest in T10 (0.6% SA) (39.82 ± 1.07%). This was significantly different compared to the untreated controls (36.64 ± 3.83%).
The highest lipid percentage (22.34 ± 0.59%) was observed in the T9 (0.4% SA) M2 plants of the SL958 variety, while the lowest (19.87 ± 0.47%) was recorded in the T10 plants (0.6% SA), as compared to the untreated controls (20.74 ± 0.64%). The highest lipid percentage (21.74 a ± 0.77%) was observed in the T8 (0.2% SA) M2 plants of the SL744 variety, while the lowest (18.69 ± 0.55%) was recorded in the T7 plants (0.6% MMS) compared to the untreated controls (21.39 ± 0.37%).
The highest fibre content was observed in the T9 plants (0.4% SA), which was 18.23 ± 0.12% in the M2 seeds of SL958, while the lowest (16.59 c ± 0.36%) was observed in the T7 plants (0.6% MMS) in SL958 compared to the controls (17.71 ± 0.39%). The highest fibre content was observed in the T8 plants (0.4% SA), which was 17.89 ± 0.39% in the M2 seeds of SL744, while the lowest (16.23 ± 0.93%) was observed in the T6 (0.4% MMS) plants in SL744 compared to the controls (16.99%).

4. Discussion

The present findings signify that induced mutagenesis can play a crucial role in improving the genetic makeup of crop plants in order to feed the teaming population of billions of people. Chemical mutagens caused the appearance of leaf variations including unifoliate, bifoliate, tetrafoliate, and pentafoliate characteristics. In our study, the seed germination percentage increased with lower doses of SA, EMS, and MMS (0.4%) and decreased with increasing dose (0.6%) compared to the untreated controls. Every living cell requires energy in the form of ATP molecules to carry out all biological reactions. When ATP levels are low, the rate of biological reactions inside the cell decreases [27]. Higher doses of SA (0.6%) can hinder ATP biosynthesis, resulting in a decreased availability of ATP molecules; as a result, the germination rate may slow down. Our findings are in consonance with those of Apparao (2005) [28], who reported that there was a reduction in germination percentage with higher doses of SA (25%) and an increase in germination with 5% SA in cowpea seeds. The decrease in seed germination count was observed in sesame seed with higher doses of SA (0.0776%) and an increased germination count was observed with lower doses (0.0473%) [29]. Furthermore, Aliyu et al. [30] reported that a nonlinear decline in mutagenic efficiency in Sesamum indicum was observed with increasing concentration and dose of sodium azide, and the best growth was recorded in terms of morphological and yield traits at a lower (0.5 mM) concentration of sodium azide. The decline in mutagenic effectiveness with increasing concentration of sodium azide might be attributed to increasing chromosome damage with increasing concentration of the mutagen.
Increased plant height was observed with lower doses (0.4%) of SA (37.8 cm) in the SL958 soybean variety and also with lower doses (0.2%) of EMS (24.80 cm) in the SL744 variety. This might be attributed to the effect of chemical mutagens on plant growth hormones. An increase in mutagen concentration often results in more physiological damage and direct DNA damage, as well as biochemical disturbances, auxin destruction, and changes in ascorbic acid content. These damages are phenotypically reflected in plant growth. The reduction in plant height caused by chemical mutagens can be attributed to any of the aforementioned factors. Our results are in agreement with the findings of Markeen et al. [31] in ‘urd bean’, who reported a decrease in plant height with higher doses of EMS (12%), attributed to gross injury at the cellular level. Our findings are also in consonance with the observations of OlaOlorun et al. [32]. In wheat plants, their results indicated that the plant height increased by 21.2 cm with 0.1% EMS and decreased by 16.3 cm with 0.7% EMS [32].
There was an increase in leaf number (229/234 leaves per plant) at a low dose of EMS (0.2%) and SA (0.4%), respectively, and a decrease in leaf number (164/220 leaves/plant) with high doses of EMS (0.6%) and SA (0.6%) in the M1 plants of the SL958 variety. Meanwhile, in the SL744 variety, the leaf number (199.33 leaves per plant) was higher with lower doses of SA (0.4%), and there was a decrease in leaf number (135.53 leaves/plant) with high doses of EMS (0.6%). Our observations are in consonance with the findings of Gupta et al. [33], who reported an increase in leaf number in soybean plants with lower doses of EMS (0.4%) and decrease in leaf number with higher doses of EMS (6%). However, it was also reported by Habib et al. [34] that there was a gradual reduction in the morphological characteristics of sunflower seedlings with the increasing dose of EMS in comparison to non-treated control seedlings.
In our findings, the highest leaf area (3625.8 cm2) was observed in response to T9 (0.4% SA) in SL958, and the leaf area decreased (2703.4 cm2) with higher doses (0.6% SA). However, in the SL744 variety, the leaf area (2311.03 cm2) was higher with lower doses of SA (0.4%), and there was a decrease in leaf number (731.54 leaves/plant) with high doses of SA (0.6%). This result is similar to the findings of Al-Qurainy. Al-Qurainy reported that in Eruca sativa plants, with lower doses of SA (3%), the leaf area increases, and with higher doses (5%), the leaf area decreases [35]. Jabeen and Mirza found that in Capsicum annum, the leaf area increases with lower EMS doses (0.01%) and declines with higher doses (0.5%) [25].
In our study, broad leaves were observed with lower doses (0.2% SA pentafoliate leaves and 0.4% SA tetrafoliate leaves) in SL958, and narrow leaves were observed with higher doses (0.6%). Meanwhile, in SL744, broad leaves were observed with lower doses (0.2% EMS tetrafoliate leaves and 0.6% EMS tetrafoliate leaves), and narrow leaves were observed with higher doses (0.6%) of EMS. This is in consonance with the findings of Khursheed et al. [36], who reported that with lower doses of EMS (0.23%), broad leaves were observed, and with higher doses of EMS (0.25%), narrow leaves were observed in faba bean plants. It was also reported that with a much higher dose of EMS (0.3%), trifoliate leaves were observed, which is similar to our findings (0.6% EMS: trifoliate leaves). Ahire et al. [37] reported that there was an increased number of pentafoliate leaves (3) with lower doses EMS (0.2%) and decreased number of pentafoliate leaves (1) with higher doses (0.4%). No tetrafoliate leaves were observed with either of the doses (2% EMS or 0.4% EMS) in soybean plants. Espina et al. [38] reported that with higher doses of EMS (0.23%), tetrafoliate leaves were observed, and with lower doses of EMS (0.14%), pentafoliate leaves were observed in soybean plants [38].
In our study, the number of days to 50% flowering increased with increasing dose and decreased with decreasing dose of the chemicals. The T9 (0.4% SA)-treated plants in SL958 took the least time to flower (39.67 days) and the T4-treated plants (0.6% EMS) took the most time (51 days) in the SL958 variety. However, in the SL744 variety (51.33 days), the time was higher with lower doses of EMS (0.2%), and there was a decrease in the number of days (46.67 days) with the doses of SA (0.4%). Our results are in consonance with those of Kumar and Pandey (2019), who investigated the impact of EMS on Coriandrum sativum L. seeds by exposing them to various concentrations (0.1%, 0.3%, and 0.5%) for 3 and 5 h, respectively. They found that as EMS concentrations increased, there was a delay in the amount of time to 50% flowering compared to a control [39]. Samadi et al. (2022), while working with corn, reported a similar observation [40].
The plant chlorophyll content was observed to be higher (48.10 nmol/cm2) with lower doses of EMS (0.2%) and decreased (41.76 nmol/cm2) with increasing doses of MMS (0.6%) in the SL958 variety. Furthermore, in the SL744 variety, the chlorophyll content was observed to be higher (46.43 nmol/cm2) with lower doses of EMS (0.2%) and decreased (41.47 nmol/cm2) with increasing doses of SA (0.6%). Devi et al. [17] reported that there was a progressive increase in chlorophyll content with lower doses of 10% EMS and 10% SA and a decrease in chlorophyll content with higher doses of EMS (40%) and SA (40%) in chili (Capsicum annuum L.). Dinkar et al. [41] reported a higher frequency of chlorophyll mutations in chickpeas treated with 0.5% EMS. Selvaraj et al. [42] reported that lower doses of SA (5%) increase the chlorophyll content and higher doses (10%) decrease the chlorophyll content in rice plants.
Podding was observed to be higher (277.55 pods/plant) with 0.4% SA (SL958) and lower (112.22 pods/plant) with 0.2% EMS (SL744). Our results are contrary to the findings of Parchin et al. [43], who reported that a higher yield was obtained from fenugreek plants (Trigonella foenum-graecum) that received a higher dose of EMS (0.5%) and a lower yield was obtained with a lower dose of EMS (0.1%). Khan et al. [44] reported that high doses of SA (2.5%) decreased the yield and lower doses of SA (2%) increased the yield of barley plants. According to Etther et al. [45], Cajanus cajan plants treated with EMS had an increased grain yield per plant and 100-seed weight, which might be as a result of a high amount of mutagenic frequency, mutagenic effectiveness, and mutagenic efficiency at low concentrations of the mutagen.
In our study, the protein content of the M2 seeds of SL958 increased (47.04% TSP) with the decreased dose of SA (0.4%) and decreased (40.62% TSP) with the increased dose (0.6% SA). Jephter et al. [11] reported that there was an increase in the percentage of protein with lower doses of EMS (0.1%) and a decrease with higher doses of EMS (0.5%) in soybean seeds. The highest crude lipid content was observed (22.34%) with 0.4% SA, while lowest was recorded (19.87%) with 0.6% SA. Our findings are similar to that of Olorunmaiye et al. [46], who reported that high doses of EMS (1.2%) decreased the lipid content and lower doses (0.25%) increased the lipid content. In our study, the highest fibre content (18.23%) was observed with 0.4% SA, while the lowest (16.90%) was observed with 0.2% MMS. Olorunmaiye et al. [46] reported that high doses of EMS (1.25%) decreased the fibre content and lower doses (0.25%) increased the fibre content in groundnut seeds. Thus, the response to mutagens depends on the dose, plant type, and geographical location of the study. Therefore, the evaluation and elicitation of mutagens could be considered as an alternative method for the production of low-cost functional foods to diversify the soybean market. Moreover, it is important to identify elicitors that stimulate sprout growth and yield so as to improve plants’ nutritional properties.

5. Conclusions

The results obtained in the present study with regard to the application of chemical mutagens on soybean varieties have shown it is a simple and inexpensive method for improving agronomic characteristics. Their mutagenic effects manifest shortly after sowing seeds and are observable. Thus, chemical mutagens have been used in various crops to improve their yield and quality traits. The findings of this research have shown positive effects of SA treatment in SL958, which proved to be efficient in generating the highest leaf area (the tetrafoliate leaves were broad, but the pentafoliate leaves were narrow), and the highest number of pods/plants and protein content were recorded for the M1 plants. Furthermore, SL744 showed positive effects from the EMS treatment in terms of yield and quality traits, which indicates the potential of EMS and SA to induce useful mutations in soybean. The potential mutants generated should be selected for further evaluation (for assessing the transfer of trait(s) in subsequent generations) in a soybean breeding programme.

Author Contributions

A.H.: Conceptualization, methodology, formal analysis, and investigation. B.K., M.F.R., A.P.A. and S.A.N.: conceptualization, manuscript writing—original draft preparation, supervision and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Tertiary Education Trust Fund (TETFUND), Nigeria and Researchers Supporting Project (number RSPD2024R989), King Saud University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data will be made available on request.

Acknowledgments

We express our gratitude to Lovely Professional University (LPU), Punjab, India for the infrastructural support.

Conflicts of Interest

There are no competing interests relevant to the contents of this manuscript to declare.

References

  1. Chopra, V.L. Mutagenesis: Investigating the process and processing the outcome for crop improvement. Curr. Sci. 2005, 89, 353–359. [Google Scholar]
  2. Beyaz, R.; Yildiz, M. The Use of Gamma Irradiation in Plant Mutation Breeding. In Plant Engineering; Jurić, S., Ed.; IntechOpen: Rijeka, Croatia, 2017; p. Ch. 3. ISBN 978-953-51-3608-8. [Google Scholar]
  3. Bado, S.; Forster, B.P.; Nielen, S.; Ali, A.M.; Lagoda, P.J.L.; Till, B.J.; Laimer, M. Plant Mutation Breeding: Current Progress and Future Assessment. In Plant Breeding Reviews: Volume 39; John Wiley & Sons: Hoboken, NJ, USA, 2015; pp. 23–88. ISBN 9781119107743. [Google Scholar]
  4. Patil, A.M.; Wagh, S.G.; Janvale, G.B.; Pawar, B.D.; Daspute, A.A. Viral delivery of CRISPR/Cas9 genome editing for rapid crop improvement: A promising approach to enhance crop resilience against biotic and abiotic stresses. Int. J. Adv. Biochem. Res. 2024, 8, 782–796. [Google Scholar] [CrossRef]
  5. Tamilzharasi, M.; Dharmalingam, K.; Venkatesan, T.; Jegadeesan, S.; Palaniappan, J. Mutagenic effectiveness and efficiency of gamma rays and combinations with EMS in the induction of macro mutations in blackgram (Vigna mungo (L.) Hepper). Appl. Radiat. Isot. 2022, 188, 110382. [Google Scholar] [CrossRef] [PubMed]
  6. Amoanimaa-Dede, H.; Su, C.; Yeboah, A.; Zhou, H.; Zheng, D.; Zhu, H. Growth regulators promote soybean productivity: A review. PeerJ 2022, 10, e12556. [Google Scholar] [CrossRef] [PubMed]
  7. Bakshi, S.; Jambhulkar, S.J.; Kumar, U.; Bhati, P. Induced mutagenesis to sustain wheat production under changing climate. In Woodhead Publishing Series in Food Science, Technology and Nutrition, Improving Cereal Productivity through Climate Smart Practices; Elsevier: Amsterdam, The Netherlands, 2020; pp. 37–63. [Google Scholar] [CrossRef]
  8. Lu, W.H.; Wang, X.Z.; Zheng, Q.; Guan, S.H.; Xin, P.; Sun, Y.Q. Diversity and Stability Study on Rice Mutants Induced in Space Environment. Genom. Proteom. Bioinforma 2008, 6, 51–60. [Google Scholar] [CrossRef] [PubMed]
  9. Kurata, N.; Miyoshi, K.; Nonomura, K.I.; Yamazaki, Y.; Ito, Y. Rice mutants and genes related to organ development, morphogenesis and physiological traits. Plant Cell Physiol. 2005, 46, 48–62. [Google Scholar] [CrossRef] [PubMed]
  10. Bouma, J. The spring barley mutant cultivar’Diamant’, its economic importance and breeding value. Mutation Breeding Newsletter 1976, 7, 2–3. [Google Scholar]
  11. Jephter, B.F.M.; Peter, M.; Bokosi, J.M. Assessment of the agronomic productivity and protein content in 16 soybean genotypes. Afr. J. Food Agric. Nutr. Dev. 2017, 17, 12600–12613. [Google Scholar] [CrossRef]
  12. Kharkwal, M.C.; Nagar, J.P.; Kala, Y.K. BGM 547—A high yielding chickpea (Cicer arietinum L.) mutant variety for late sown condition in north western plain zone of India. Indian J. Genet. Plant Breed. 2005, 65, 229–230. [Google Scholar]
  13. Song, M.; Fan, S.; Pang, C.; Wei, H.; Liu, J.; Yu, S. Genetic analysis of fiber quality traits in short season cotton (Gossypium hirsutum L.). Euphytica 2015, 202, 97–108. [Google Scholar] [CrossRef]
  14. Ram, B.; Hemaprabha, G. The sugarcane variety Co 0238—A reward to farmers and elixir to India’s sugar sector. Curr. Sci. 2020, 118, 1643–1646. [Google Scholar]
  15. Yang, Y.J.; Yang, S.J.; Yang, Y.H.; Zeng, J.M. The breeding of an early sprouting and high quality new clone suitable for fine green tea. J. China Tea 2003, 25, 13–15. [Google Scholar]
  16. SriDevi, A.; Mullainathan, L. Physical and chemical mutagenesis for improvement of Chilli (Capsicum annuum L.). World Appl. Sci. J. 2011, 15, 108–113. [Google Scholar]
  17. Devi, J.; Sagar, V.; Kaswan, V.; Ranjan, J.K.; Kumar, R.; Mishra, G.P.; Dubey, R.K.; Verma, R.K. Advances in Breeding Strategies of Bell PepperBell peppers (Capsicum annuum L. var. grossum Sendt.). In Advances in Plant Breeding Strategies: Vegetable Crops: Volume 9: Fruits and Young Shoots; Al-Khayri, J.M., Jain, S.M., Johnson, D.V., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 3–58. ISBN 978-3-030-66961-4. [Google Scholar]
  18. Alghamdi, S.S.; Khan, M.A.; El-Harty, E.H.; Ammar, M.H.; Farooq, M.; Migdadi, H.M. Comparative phytochemical profiling of different soybean (Glycine max (L.) Merr) genotypes using GC–MS. Saudi J. Biol. Sci. 2018, 25, 15–21. [Google Scholar] [CrossRef]
  19. Sedibe, M.M.; Mofokeng, A.M.; Masvodza, D.R. Soybean Production, Constraints, and Future Prospects in Poorer Countries: A Review. In Production and Utilization of Legumes—Progress and Prospects; Hasanuzzaman, M., Ed.; IntechOpen: Rijeka, Croatia, 2023; p. Ch. 4. ISBN 978-1-83768-647-6. [Google Scholar]
  20. Nuthalapati, C.S.; Kumar, A.; Birthal, P.S.; Sonkar, V.K. Demand-side and supply-side factors for accelerating varietal turnover in smallholder soybean farms. J. Clean. Prod. 2024, 447, 141372. [Google Scholar] [CrossRef]
  21. Chandirakala, R.; Subbaraman, N. Character association and path analysis for yield attributes in full sib progenies in Pigeonpea (Cajanus cajan (L.) Mill Sp.). Electron. J. Plant Breed. 2010, 1, 824–827. [Google Scholar]
  22. Gill, B.; Kumar, A.; Dhillon, S.; Singh, T. SL 958: A New high yielding and yellow mosaic resistant variety of soybean. Agric. Res. J. 2015, 52, 124. [Google Scholar] [CrossRef]
  23. Pandey, A.; Malik, P.; Kumar, A.; Kaur, N.; Saini, D.K.; Gill, R.K.; Kashyap, S.; Kaur, S. Multi-GWAS reveals significant genomic regions for Mungbean yellow mosaic India virus resistance in urdbean (Vigna mungo (L.) across multiple environments. Plant Cell Rep. 2024, 43, 166. [Google Scholar] [CrossRef] [PubMed]
  24. Gulati, A. Challenges to Punjab Agriculture in a Globalizing World; IFPRI: Washington, DC, USA, 2002. [Google Scholar]
  25. Jabeen, N.; Mirza, B. Ethyl Methane Sulfonate induces morphological mutations in Capsicum annuum. Int. J. Agric. Biol. 2004, 6, 340–345. [Google Scholar]
  26. Association of Official Analytical Chemists. International, Official Methods of Analysis, 16th ed.; AOAC International: Arlington, VA, USA, 1995; pp. 23–27. [Google Scholar]
  27. Aishatu, G.A. Sodium azide: A chemical mutagen for enhancement of yield traits of sesame. J. Bacteriol. Parasitol. 2015, 5, 1–21. [Google Scholar] [CrossRef]
  28. Apparao, B.J. Effect of sodium azide on peroxidase isozyme profiles in Vigna unguiculata (L.) Walp. Adv.Plant Sci. 2005, 18, 44–50. [Google Scholar]
  29. Mensah, J.K.; Obadoni, B.O.; Akomeah, P.A.; Ikhajiagbe, B.; Ajibolu, J. The effects of sodium azide and colchicine treatments on morphological and yield traits of sesame seed (Sesame indicum L.). Afr. J. Biotechnol. 2007, 6, 534–538. [Google Scholar]
  30. Aliyu, R.E.; Aliyu, A.; Adamu, A.K. Induction of genetic variability in sesame (Sesamum indicum L.) with sodium azide. FUW Trends Sci. Technol. J. 2018, 3, 96–100. [Google Scholar]
  31. Markeen Effect of mutagenesis on M1 population in urdbean. J. Food Legum. 2007, 20, 109–110.
  32. OlaOlorun, B.M.; Shimelis, H.; Laing, M.; Mathew, I. Morphological variations of wheat (Triticum aestivum L. em. Thell.) under variable ethyl methanesulphonate mutagenesis. Cereal Res. Commun. 2021, 49, 301–310. [Google Scholar] [CrossRef]
  33. Gupta, S.; Kumawat, G.; Agrawal, N.; Tripathi, R.; Rajesh, V.; Nataraj, V.; Maranna, S.; Satpute, G.K.; Chandra, S.; Ratnaparkhe, M.B. Photoperiod trait: Insight in molecular mechanism for growth and maturity adaptation of soybean (Glycine max) to different latitudes. Plant Breed. 2022, 141, 483–500. [Google Scholar] [CrossRef]
  34. Habib, S.H.; Akanda, M.A.L.; Roy, P.; Kausar, H. Effect of different dosage of EMS on germination, survivability and morpho-physiological characteristics of sunflower seedling. Helia 2021, 44, 167–180. [Google Scholar] [CrossRef]
  35. Al-Qurainy, F. Effects of Sodium Azide on Growth and Yield Traits of Eruca sativa (L.). World Appl. Sci. J. 2009, 7, 220–226. [Google Scholar]
  36. Khursheed, S.; Raina, A.; Parveen, K.; Khan, S. Induced phenotypic diversity in the mutagenized populations of faba bean using physical and chemical mutagenesis. J. Saudi Soc. Agric. Sci. 2019, 18, 113–119. [Google Scholar] [CrossRef]
  37. Ahire, D.D.; Thengane, R.J.; Manjaya, J.G.; George, M.; Bhide, S. V Induced mutations in soybean [Glycine max.(L.) Merr.] Cv.‘MACS 450’. Soybean Res. 2005, 3, 1–8. [Google Scholar]
  38. Espina, M.J.; Ahmed, C.M.S.; Bernardini, A.; Adeleke, E.; Yadegari, Z.; Arelli, P.; Pantalone, V.; Taheri, A. Development and phenotypic screening of an ethyl methane sulfonate mutant population in Soybean. Front. Plant Sci. 2018, 9, 394. [Google Scholar] [CrossRef]
  39. Kumar, G.; Pandey, A. Ethyl methane sulphonate induced changes in cyto-morphological and biochemical aspects of Coriandrum sativum L. J. Saudi Soc. Agric. Sci. 2019, 18, 469–475. [Google Scholar] [CrossRef]
  40. Siddique, M.I.; Back, S.; Lee, J.H.; Jo, J.; Jang, S.; Han, K.; Venkatesh, J.; Kwon, J.K.; Jo, Y.D.; Kang, B.C. Development and characterization of an ethyl methane sulfonate (Ems) induced mutant population in Capsicum annuum L. Plants 2020, 9, 396. [Google Scholar] [CrossRef] [PubMed]
  41. Dinkar, V.; Kumar Verma, B.; Sanjay, G.; Arora, A.; Panwar, R.; Verma, S. Mutagenesis induced variability through gamma rays, EMS and combination treatments in chickpea genotypes. J. Pharmacogn. Phytochem. 2020, 9, 1139–1144. [Google Scholar] [CrossRef]
  42. Ramchander, S. Effectiveness and efficiency of physical and chemical mutagens inducing chlorophyll mutants in Two Rice Genotypes. Madras Agric. J. 2014, 101, 212–218. [Google Scholar] [CrossRef]
  43. Ashrafi Parchin, R.; Nasrollahnezhad Ghomi, A.A.; Naghdi Badi, H.; Navabpour, S.; Mehrafarin, A.; Eskandari, A. Investigation effect of ethyl methane sulfonate (EMS) on some of morphophysiological and phytochemical traits of fenugreek (Trigonella foenum-graecum L.). Ind. Crops Prod. 2021, 162, 113239. [Google Scholar] [CrossRef]
  44. Mosisa, G.; Muthuswamy, M.; Petros, Y. Sodium Azide: A chemical mutagen for enhancement of agronomic traits in Phaseolus vulgaris (Linn). J. Theor. Exp. Biol. 2013, 10, 21–25. [Google Scholar]
  45. Etther, Y.; Sj, G.; Akhare, A.; An, P.; Sj, J.; Gawande, M. Genetic variability induced by gamma radiation and ethyl methane sulphonate on quantitative characters in pigeonpea (Cajanus cajan). J. Pharmacogn. Phytochem. 2019, 8, 1903–1907. [Google Scholar]
  46. Olorunmaiye, K.S.; Joseph, G.G.; Animasaun, D.A.; Oyedeji, S. Mutagenic components and dosage effects of ethyl methanesulphonate on Arachis hypogea (Samnut 24 VR.). Ife J. Sci. 2019, 21, 309. [Google Scholar] [CrossRef]
Figure 1. Field layout (8 × 60 m) and experimental design using RBD. V1: variety 1 (SL744), V2: variety 2 (SL958), C: control. Chemicalxx (xx = 0.2, 0.4, 0.6%), EMS: ethyl methane sulfonate, MMS: methyl methane sulfonate, SA: sodium azide.
Figure 1. Field layout (8 × 60 m) and experimental design using RBD. V1: variety 1 (SL744), V2: variety 2 (SL958), C: control. Chemicalxx (xx = 0.2, 0.4, 0.6%), EMS: ethyl methane sulfonate, MMS: methyl methane sulfonate, SA: sodium azide.
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Figure 2. Effect of chemical mutagens on seed germination percentage (%). (A) Effect on SL744 soybean varieties. (B) Effect on SL958 soybean varieties. DAS = Days after sowing.
Figure 2. Effect of chemical mutagens on seed germination percentage (%). (A) Effect on SL744 soybean varieties. (B) Effect on SL958 soybean varieties. DAS = Days after sowing.
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Figure 3. (A) Effect of different concentrations of three mutagens on the morphology of soybean (Glycine max L.) variety SL958 at 12 WAS. Mutagen I: Ethyl methane sulfonate (a) 0.2%, (b) 0.4%, (c) 0.6%. Mutagen II: Methyl methane sulfonate (d) 0.2%, (e) 0.4%, (f) 0.6%. Mutagen III: Sodium azide (g) 0.2%, (h) 0.4%, (i) 0.6%. (C1) Control: SL958 (without mutagen treatment). (B) Effect of different concentrations of three mutagens on the morphology of SL744 soybean (Glycine max L.) variety at 12 WAS. Mutagen I: Ethyl methane sulfonate (j) 0.2%, (k) 0.4%, (l) 0.6%. Mutagen II: Methyl methane sulfonate (m) 0.2%, (n) 0.4%, (o) 0.6%. Mutagen III: Sodium azide (p) 0.2%, (q) 0.4%, (r) 0.6%. (C2) Control: SL744 (without mutagen treatment).
Figure 3. (A) Effect of different concentrations of three mutagens on the morphology of soybean (Glycine max L.) variety SL958 at 12 WAS. Mutagen I: Ethyl methane sulfonate (a) 0.2%, (b) 0.4%, (c) 0.6%. Mutagen II: Methyl methane sulfonate (d) 0.2%, (e) 0.4%, (f) 0.6%. Mutagen III: Sodium azide (g) 0.2%, (h) 0.4%, (i) 0.6%. (C1) Control: SL958 (without mutagen treatment). (B) Effect of different concentrations of three mutagens on the morphology of SL744 soybean (Glycine max L.) variety at 12 WAS. Mutagen I: Ethyl methane sulfonate (j) 0.2%, (k) 0.4%, (l) 0.6%. Mutagen II: Methyl methane sulfonate (m) 0.2%, (n) 0.4%, (o) 0.6%. Mutagen III: Sodium azide (p) 0.2%, (q) 0.4%, (r) 0.6%. (C2) Control: SL744 (without mutagen treatment).
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Table 1. Effect of chemical mutagens on plant height (cm).
Table 1. Effect of chemical mutagens on plant height (cm).
TreatmentsData Collection Periods
4 WAS8 WAS12 WAS
SL744SL958SL744SL958SL744SL958
T1 (Control)13.29 ± 0.68 cd9.29 ± 1.01 a26.13 ± 0.84 a21.99 ± 1.42 d27.48 ± 0.74 a26.09 ± 0.62 e
T214.13 ± 0.96 a15.19 ± 0.89 a25.37 ± 0.52 a29.33 ± 0.63 b24.80 ± 1.07 b35.06 ± 1.42 b
T312.10 ± 0.80 bc11.87 ± 1.12 bc21.29 ± 0.57 bc22.06 ± 0.23 d21.82 ± 1.24 cd24.27 ef ± 0.73
T410.13 ± 0.54 d9.75 ± 0.82 d20.87 ± 0.78 c17.43 ± 1.09 e24.17 ± 0.87 b22.44 ± 0.51 f
T514.26 ± 1.15 a14.65 ± 0.81 a22.60 ± 0.93 b26.34 ± 0.90 c23.02 ± 0.82 bc28.40 ± 0.95 cd
T69.99 ± 0.21 d9.99 ± 0.21 cd20.97 ± 0.67 c21.22 ± 0.86 d22.21 ± 1.03 cd25.53 ± 1.71 e
T79.39 ± 0.82 d9.73 ± 0.64 d17.99 ± 0.74 d15.97 ± 1.00 e21.77 ± 0.17 cd21.90 ± 0.63 f
T813.96 ± 0.64 a13.49 ± 0.90 ab17.95 ± 0.68 d25.37 ± 1.07 c21.31 ± 0.63 cd30.54 ± 2.37 c
T914.19 ± 0.94 a14.25 ± 0.93 a19.19 ± 0.74 d36.35 ± 1.5 a23.18 ± 0.61 bc37.84 ± 1.32 a
T1011.09 ± 0.83 d10.12 ± 0.99 cd17.97 ± 0.69 d28.50 ± 0.91 b20.58 ± 0.30 d28.71 ± 0.92 cd
The same letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 2. Effect of chemical mutagens on the number of leaves per plant.
Table 2. Effect of chemical mutagens on the number of leaves per plant.
TreatmentsData Collection Periods
4 WAS8 WAS12 WAS
SL744SL958SL744SL958SL744SL958
T1 (Control)25.40 ± 0.0 bc26.47 ± 0.98 d147.33 ± 1.25 b156.77 ± 1.05 bc180.00 ± 1.63 c160.73 ± 1.05 d
T223.13 ± 0.84 cd34.44 ± 0.97 a133.00 ± 2.16 b217.80 ± 5.37 a179.33 ± 2.49 c229.00 ± 5.35 ab
T322.73 ± 0.38 cd24.78 ± 1.03 de126.00 ± 1.63 b155.87 ± 5.56 bc168.33 ± 4.99 c165.13 ± 2.11 d
T422.40 ± 0.43 cd24.18 ± 0.95 f77.87 ± 1.33 b152.20 ± 5.37 c135.53 ± 5.72 g164.80 ± 2.47 d
T531.27 ± 1.16 a28.51 ± 1.25 c178.80 ± 3.96 b218.00 ± 1.63 a190.33 ± 2.49 b227.33 ± 2.05 b
T628.33 ± 1.25 ab22.20 ± 0.59 f134.00 ± 0.82 b215.67 ± 3.68 a179.80 ± 3.84 c220.07 ± 2.37 c
T719.20 ± 1.07 d17.47 ± 0.70 g120.33 ± 1.25 b81.58 ± 4.03 d156.53 ± 3.13 e87.00 ± 0.82 f
T825.67 ± 4.78 bc25.17 ± 0.94 de120.67 ± 1.70 b102.60 ± 6.25 d142.07 ± 2.25 fg146.00 ± 2.16 e
T930.53 ± 1.84 a32.80 ± 0.75 ab200.00 ± 2.62 a193.87 ± 2.81 bc199.33 ± 2.62 a234.33 ± 3.09 a
T1028.20 ± 0.86 bc31.27 ± 0.99 b129.07 ± 11.44 b181.00 ± 1.63 b147.67 ± 0.05 fg220.33 ± 1.25 c
The common letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 3. Effect of chemical mutagens on leaf area (cm2) per plant.
Table 3. Effect of chemical mutagens on leaf area (cm2) per plant.
TreatmentsData Collection Period
4 WAS8 WAS12 WAS
SL744SL958SL744SL958SL744SL958
T1 (Control)38.1 ± 0.41 b35.2 ± 0.47 c2111.2 ± 1.25 a2226.1 ± 1.07 b 2190.6 ± 2.05 ab2256.6 ± 1.72 bc
T259.80 ± 0.47 ab45.8 ± 0.47 b1605.3 ± 1.92 bc2628.4 ± 1.16 a1738.8 ± 1.25 b2790.6 ± 1.55 ab
T338.62 ± 0.47 ab41.3 ± 0.47 ab1411.2 ± 2.18 c2069.1 ± 1.28 cd1527.4 ± 1.03 b2557.9 ± 1.51 b
T422.72 ± 0.00 b32.1 ± 0.47 cd496.0 ± 1.08 ef1578.9 ± 0.82 c12,854.6 ± 1.5 b1865.9 ± 0.86 c
T552.22 ± 0.47 ab57.2 ± 0.00 ab2042.6 ± 1.20 ab1018.6 ± 0.81 e2221.1 ± 1.27 ab2440.8 ± 0.86 c
T632.06 ± 0.00 ab34.9 ± 0.82 cd1357.4 ± 1.95 cd239.2 ± 1.04 de1947.2 ± 1.58 b1091.1 ± 0.75 d
T728.33 ± 0.82 b22.2 ± 0.00 e1070.9 ± 1.34 cd236.3 ± 1.70 bc939.1 ± 0.82 c267.9 ± 1.09 d
T825.17 ± 0.00 b32.8 ± 0.82 cd520.0 ± 0.16 e148.9 ± 0.50 f1633.8 ± 2.03 b1946.1 ± 1.25 cd
T961.06 ± 0.47 a62.5 ± 0.82 a1199.7 ± 1.02 cd2383.7 ± 2.56 ab2311.03 ± 3.65 a3625.8 ± 1.43 a
T1037.50 ± 0.40 b33.4 ± 0.67 d1987.4 ± 3.47 b998.2 ± 1.54 ef731.54 ± 1.11 c2703.4 ± 1.16 c
The same letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 4. Effect of chemical mutagens on flowering.
Table 4. Effect of chemical mutagens on flowering.
TreatmentsDays to 50% Flowering
SL744SL958
T1 (Control)68.00 ± 0.82 a63.33 ± 1.25 a
T247.67 ± 1.25 de43.00 ± 0.82 de
T351.00 ± 1.63 bc46.00 ± 0.82 c
T451.00 ± 0.83 bc45.00 ± 0.82 cd
T547.00 ± 0.82 e48.33 ± 1.70 b
T648.33 ± 1.70 cde49.00 ± 0.82 b
T748.67 ± 1.25 bcde50.33 ± 1.25 b
T851.33 ± 0.47 b41.33 ± 0.47 ef
T946.67 ± 1.70 e39.67 ± 0.94 f
T1050.00 ± 0.82 bcd42.67 ± 0.47 e
The same letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 5. Effect of chemical mutagens on days to 50% podding and pod yield.
Table 5. Effect of chemical mutagens on days to 50% podding and pod yield.
Pod YieldDays to 50% Podding
TreatmentsSL744SL958SL744SL958
T1 (Control)164.33 ± 8.58 d229.86 ± 0.96 e86.33 ± 0.94 a82.67 ± 1.25 a
T2112.22 ± 5.92 e228.44 ± 1.23 e80.33 ± 0.94 e70.67 ± 1.25 cd
T3264.11 ± 3.09 ab261.00 ± 0.82 b81.00 ± 0.47 cd74.67 ± 1.25 b
T4273.00 ± 4.55 a217.55 ± 2.20 g79.67 ± 1.41 a74.33 ± 1.25 b
T5260.44 ± 30.99 ab228.00 ± 2.67 d85.00 ± 0.47 a80.00 ± 0.82 a
T6232.22 ± 1.10 ab222.78 ± 0.82 e85.33 ± 3.56 bc80.67 ± 1.25 a
T7179.33 ± 33.07 cd270.11 ± 1.10 f84.33 ± 0.47 a72.33 ± 1.70 c
T8146.66 ± 50.87 bc269.78 ± 0.95 b85.33 ± 1.41 cd73.67 ± 2.16 d
T9206.54 ± 23.47 de277.55 ± 1.37 b77.00 ± 2.87 cd69.00 ± 0.82 a
T10216.67 ± 4.34 bc276.69 ± 1.23 a84.33 ± 0.47 bc73.67 ± 1.70 c
The same in letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 6. Effect of chemical mutagens on chlorophyll content (nmol/cm2).
Table 6. Effect of chemical mutagens on chlorophyll content (nmol/cm2).
TreatmentsData Collection Periods
4 WAS8 WAS12 WAS
SL744SL958SL744SL958SL744SL958
T1 (Control)34.58 ± 1.88 cd37.75 ± 4.29 a45.27 ± 1.61 a41.27 ± 0.55 b45.78 ± 2.10 a39.54 ± 0.55 d
T242.09 ± 1.70 a39.61 ± 0.61 a47.25 ± 3.07 a44.21 ± 0.71 ab46.43 ± 2.50 a48.10 ± 0.71 abc
T341.04 ± 0.87 ab38.71 ± 1.55 a45.04 ± 2.06 a44.09 ± 0.65 ab44.10 ± 1.63 a45.17 ± 0.65 a
T438.06 ± 3.15 abc35.95 ± 2.30 ab43.57 ± 1.65 a42.80 ± 0.65 ab44.01 ± 3.37 a44.83 ± 0.65 ab
T535.27 ± 2.28 cd37.79 ± 2.30 b45.51 ± 3.15 a44.66 ± 0.61 ab46.47 ± 3.08 a44.28 ± 0.61 abc
T632.89 ± 2.65 cd34.89 ± 0.75 a43.56 ± 1.21 a42.97 ± 1.71 ab44.35 ± 7.18 a43.61 ± 1.72 abc
T731.57 ± 1.14 d31.85 ± 1.07 b42.26 ± 6.32 a42.88 ± 3.63 ab44.32 ± 0.94 a41.33 ± 3.63 cd
T835.02 ± 3.58 cd35.63 ± 1.45 ab42.83 ± 3.38 a43.19 ± 0.61 ab43.75 ± 4.22 a44.34 c ± 0.6 ab
T935.95 ± 2.84 bcd38.77 ± 3.45 ab42.90 ± 1.48 a45.76 ± 1.02 a44.31 ± 0.74 a45.38 ± 1.02 a
T1032.87 ± 2.25 cd35.76 ± 3.19 ab41.06 ± 4.06 a40.97 ± 0.5 b41.47 ± 4.07 a41.76 ± 0.51 bcd
The same letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
Table 7. Effect of chemical mutagens on protein, lipid, and fibre content (%) in M2 seeds.
Table 7. Effect of chemical mutagens on protein, lipid, and fibre content (%) in M2 seeds.
TreatmentsProteinLipidFiber
SL744SL958SL744SL958SL744SL958
T1 (Control)36.64 ± 3.83 c39.87 ± 0.96 c21.39 ± 0.37 ab20.74 ± 0.64 abc16.99 ± 0.30 a17.71 ± 0.39 ab
T242.45 ± 0.25 b43.25 ± 0.42 b20.62 ± 0.41 bc21.20 ± 0.05 bc17.56 ± 0.27 a17.69 ± 0.26 ab
T346.01 ± 0.51 a45.46 ± 0.19 a20.76 ± 0.14 bc21.67 ± 0.71 a16.54 ± 0.39 a17.24 ± 0.22 bc
T441.36 ± 1.04 b40.34 ± 0.63 cd20.63 ± 0.31 bc21.68 ± 0.58 a16.28 ± 0.15 a17.14 ± 0.16 bc
T541.72 ± 0.44 b40.91 ± 0.19 cd20.04 ± 1.09 bcd20.32 ± 0.41 bc16.32 ± 0.27 a16.90 ± 0.19 c
T640.49 ± 0.48 b41.66 ± 0.47 c19.19 ± 0.44 de21.09 ± 0.88 abc16.23 ± 0.93 a16.73 ± 0.52 c
T739.89 ± 0.72 b38.13 ± 0.81 e18.69 ± 0.55 e20.49 ± 0.11 abc16.28 ± 0.09 a16.59 c ± 0.36
T841.00 ± 0.47 b45.93 ± 0.99 a21.74 ± 0.77 a21.73 ± 0.38 a17.89 ± 0.39 a17.18 ± 0.03 bc
T946.14 ± 0.64 a47.04 ± 0.87 a21.37 ± 0.50 ab22.34 ± 0.59 a17.43 ± 0.05 a18.23 ± 0.12 a
T1039.82 ± 1.07 b40.62 ± 0.41 cd19.95 ± 0.94 cde19.87 ± 0.47 c16.54 ± 0.53 a17.12 ± 0.23 bc
The same letters in the same column are not significantly different from each other (p < 0.05). SD = Standard deviation ±, WAS = Weeks after sowing, T = Treatment (T1 = untreated control, T2 = 0.2% EMS, T3 = 0.4% EMS, T4 = 0.6% EMS, T5 = 0.2% MMS, T6 = 0.4% MMS, T7 = 0.6% MMS, T8 = 0.2% SA, T9 = 0.4% SA, T10 = 0.6% SA).
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Hamisu, A.; Koul, B.; Arukha, A.P.; Al Nadhari, S.; Rabbee, M.F. Evaluation of the Impact of Chemical Mutagens on the Phenological and Biochemical Characteristics of Two Varieties of Soybean (Glycine max L.). Life 2024, 14, 909. https://doi.org/10.3390/life14070909

AMA Style

Hamisu A, Koul B, Arukha AP, Al Nadhari S, Rabbee MF. Evaluation of the Impact of Chemical Mutagens on the Phenological and Biochemical Characteristics of Two Varieties of Soybean (Glycine max L.). Life. 2024; 14(7):909. https://doi.org/10.3390/life14070909

Chicago/Turabian Style

Hamisu, Anas, Bhupendra Koul, Ananta Prasad Arukha, Saleh Al Nadhari, and Muhammad Fazle Rabbee. 2024. "Evaluation of the Impact of Chemical Mutagens on the Phenological and Biochemical Characteristics of Two Varieties of Soybean (Glycine max L.)" Life 14, no. 7: 909. https://doi.org/10.3390/life14070909

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