Assessment of genetic variances and effects for agronomic traits in mungbean (Vigna radiata (L.) Wilczek)

Introduction

The country like India, pulses stand out as the most affordable and commonly consumed protein source 21 -30% (Singh et al. 2021) [31] and provide double amount than that of cereal crops. (Danielle et al. 2017) [9] . The protein found in mungbean, like in other pulses, is abundant in lysine, an essential amino acid indeed for the human that lacks in cereal grains. Pulses popularly referred as "rich man's vegetable" (Singh et al. 2015) [30] as well "poor man's meat" (Patil et al. 2020) [7,25] as it serves as the primary protein source for a significant portion of the global vegetarian community and has laid significant contribution to the nutritional security of the country. Among pulses, mungbean (Vigna radiata (L.) Wilczek, 2n=24) is a self-pollinated pulse crop and established itself as extravagant short duration grain legume crop grown in kharif, Rabi and Summer. (Casey and Wringley 1982) [6] and possess desirable features like wider adaptability with low inputs requirement (Kakde et al. 2019) [13] . India leads globally as the foremost producer as well as consumer of pulses, encompassing 33% of the world's cultivated area and contributing 22% to global production. (Patil et al. 2020) [7,25] . Mungbean in India is cultivated on an about 4.5 million ha area with total 2.5 million tons production (Anonymous., 2021) [2] . While, current scenario according to 1 st advance estimates of kharif 2022-23, displaying 33.37 lakh hectares cultivated area with 17.5 lakh tonnes production (agricoop.nic). Though, India has legimate pride being largest producer and consumer, but less than half of the country's productivity is being celebrated, thereby it indicates the scope for mungbean improvement in productivity potential. Currently, Inspite of high demand of growing papulation, the mungbean yield of worldwide is low (721 Kg ha) with yield gap 19.50% (Dixit et al. 2024) [11] . Therefore, to boost current crop yields, it is imperative to conduct the mungbean enhancement program by hybridization and comprehend the significance of genetic interplay in determining yield and its components. Information about gene action provides the basis for selection of traits and usually measured by the components of genetic variances (Sharma et al. 2019., Khan et al. 2020) [29,15] . This facilitates breeders in discerning the proportion both additive and non additive genetic variance in the inheritance of various characters and selecting suitable breeding method that can efficiently harness the existing genetic diversity. Among the different techniques readily upwarding the productivity in mungbean, the line × tester analysis has been suggested for early evaluation of parents, because of its clarity in experimental analysis (Dhillon, 1975) [10] . Previously, the line × tester design has been investigated for the yield and agronomic traits of mungbean (Chavan et [7,25,19] . With the considerations mentioned above, the prese study was determined to estimate the magnitude gene action for yield and its relevant traits using line × tester mating design. The findings obtained from this study will provide crucial insights for the advancement of mungbean varieties with high seed yield.

Experimental Materials and Methods

The 21-21). The parents including lines and testers employed for present study and their characteristics are presented in (Table 1). In the mungbean growing season of kharif 2021-22, the six females and the nine males were mates as per a line × tester mating system to produce 54 F 1 hybrids as suggested by Kempthorne (1957) [14] . The parents and their F 1 crosses were sown during the Kharif 2022-23. The experimental materials were sown in a Randomized Block Design with two replications. Each replication was presented in two rows each of parents and F 1 crosses. The row was 4.00 m long and planted to plant with spacing of 20 × 10 cm. The observations was recorded on each character on selected five random plants. Analysis of variance was performed as per the standard method of Panse and Sukhatme (1985) [23] . The significance of the GCA and SCA effects was evaluated using the least significant difference test at both 5% and 1% levels of significance. The GCA:SCA ratio was computed to analyze the effects and gauge the relative significance of additive and non-additive gene effects, following the methodology outlined by Singh and Chaudhary (1977) [32] .

Results and Discussion

The information of the genetic basis relating agronomic characters of interest is extremely precise for any plant breeding programmes that seek to increase crop yield in areas where there is need of explicit selection of parents by means of generating superior crosses as well as segregants.

In the present study, the analysis of variance for line × tester (Table 2) revealed significant mean square due to genotypes for all traits, revealed the existence of genetic variations in varying genotypes and justified the appropriate inclusion of genotypes for present investigation. A wide range of variation was also previously noted in different mungbean genotypes by Nath et al. (2018) [21] , Rathod et al. (2020) [27] , Vaidya et al. (2016) [34] and Bhagora et al. (2013) [4] in mungbean. Further, partitioning of mean square by genotype into parents and crosses exhibited highly significant variations for all studied characters, the comparison between the mean squares due to parents and crosses unveiled notable distinctions, indicating significant genetic variability between the parent plants and their crosses. This disparity suggests the potential for genetic enhancement through the exploitation of the mungbean diverse genetic pool. Moreover, it underscores the presence of a marked heterosis for the traits under investigation. Equivalent results for significant variation for one or more traits in mungbean was in consonance with Patil et al. (2020) [7,25] . The primary distinction between additive and non additive gene action lies in how alleles manifest themselves. Additive gene action involves both alleles expressing themselves and contributing independently to a trait, making it simpler for breeders to manage. Conversely, non additive gene action entails one allele exerting a stronger influence than the other. Jinks and Jones (1958) [12] stated greater additive variance than dominance variance depict the trait with additive gene effect while greater former of dominance variance than additive one indicate non additive gene effect. In addition, when the variance reaches zero, it signals the presence of epistasis. Various types of interactions, such as A × A, A × D, and D × D, if significant, suggest non-allelic interaction. Panse (1942) [22] proposed that the presence of additive genetic variance enhances the probability of establishing superior genotypes in initial segregating generations. Nonetheless, when dominant and epistatic interactions are prevalent, the implementation of selection should be postponed to subsequent generations. This approach allows for the utilization of appropriate breeding strategies aimed at attaining desirable genotypes. In present study, analysis of variance (Table 3) showed that the mean square due to GCA and SCA were significant for all characters. Therefore, the significant differences in GCA and SCA variances suggested that both additive and nonadditive genetic mechanisms contributed to the regulation of these traits across the mungbean genotypes (Table 3). The presence of both additive and non additive gene effects for yield and important yield component traits in mungbean has been documented by Anbumalarmathi et al. (2004) [1] ; Barad et al. (2008) [3] . However, the proportion of variances due to  2 GCA/ 2 SCA, the value stayed notably below one for all traits ranged from 0.571 to 0.997, indicated that non additive gene action was more influence in the inheritance of these characters in comparison to additive types. Cockerham (1961) [8] suggested that the presence of nonadditive genetic effects serves as the main rationale for initiating a hybrid breeding program. The predominance of non additive genetic effects in the expression of various traits in mungbean was also accordance with Anbumalarmathi et al. (2004) [1] for days to 50% flowering, Kohakade et al. (2021) [16] for days to maturity, Bhagora et al. (2013) [4] for plant height, Marappa (2008) [17] for number of primary branches/plant, Mohan and Sheeba (2019) [18] for number of clusters/plant, Purohit et al. (2016) [26] for number of pods/plant, and number of seeds/pod, Chavan et al. (2019) [7] for pod length, Pathak et al. (2019) [24] for 100 seed weight and Singh et al. (2021) [31] for seed yield/plant. From the estimates of additive and dominance variance, revealed greater part of dominance variance was predominant for all the characters except plant height, number of clusters/plant and number of seeds/pod. Further the degree of dominance less than one was observed for plant height (0.934), number of clusters/plant (0.715) and number of seeds/pod (0.936) indicated inheritance in these traits due to partial dominance while, degree of dominance displayed higher than one indicated over dominance in inheritance for days to 50% flowering (1.259), days to maturity (1.349), number of primary branches/plant (1.073), number of secondary branches/plant (1.320, number of pods/plant (1.785), pod length (1.210), 100 seed weight (1.248) and seed yield/plant (1.038). These results were accordance with the similar findings of Sujatha and Kajjidoni (2013) [33] , and Bhavani et al. (2016) [5] . A thorough examination of the results from these investigations figure out that, both additive and non additive genes governed yield and its associated traits but leveraging the potential of both types of gene actions, non additive gene effects paved a precise role in the genetic inheritance of all these investigated traits.

Conclusion:

The investigation findings indicated that most traits are influenced by additive and non-additive gene effect. However, non-additive gene action was formerly more dominated in genetic interaction of yield and its attributes. Therefore, it is suggested that, hybridization followed by selection in later generations will be pave swift progress in mungbean improvement.

References

1. Anbumalarmathi J, Rangasamy P, Babu S. Studies on combining ability and heterosis for yield and yield components in greengram (Vigna radiata (L.) Wilczek). Madras Agric J. 2004;91(1-3):79-82.
2. Anonymous. Greengram Outlook Report. [Internet]; c2021 [cited 2022 Apr 7]. Available from: https://angrau.ac.in/downloads/AMIC/GREENGRAM %20OUTLOOK%20REPORT%20January%20to%20May%202021.pdf.
3. Bhagora NB, Nizama JR, Patel SR. Combining ability studies in mungbean (Vigna radiata (L.) Wilczek). AGRES -An International e-Journal. 2013;2(4):489493.
4. Bhavani RT, Chauhan RM, Patel JR, Patel DK, Patel RA. Combining ability studies for grain yield and architectural traits in mungbean [Vigna radiata L.) Wilczek]. The BioScan. 2016;11(3):1871-1876.
5. Casey R, Wringley CW. The importance of seed protein in human nutrition. Qualitas Pl. Fds. for Human Nutrition. 1982;31:189-190.
6. Chavan SB, Patil DK, Pawar VS. Gene action studies for yield and its components in greengram (Vigna radiata (L.) Wilczek). Multilogic in Science. 2019;9(32):338-339.
7. Cockerham CC. Implication of genetic hybrids breeding programme. Crop Sci. 1961;1:47-52.
8. Danielle KT, Riviere T, Tieges Z, Greig CA. Dietary protein in older adults: Adequate daily intake but potential for improved distribution. Nutrients. 2017;9:184-194.
9. Dhillon BS. The application of partial diallel crosses in plant breeding -A review. Crop Improv. 1975;2:1-7.
10. Dixit GP, Srivastava AK, Ali H. Scenario of pulses production in India. Indian Farming. 2024;74(02):0306.
11. Jinks JL, Jones M. Estimation of components of heterosis. Genetics. 1958;43:223-234.
12. Wilczek). Int J Curr Microbial App Sci. 2019;8(2):1668-1674.
13. Kempthorne O. An Introduction to Genetic Statistics. New York: John Wiley & Sons, Inc., London: Chapman and Hall Ltd. 1957;468-470.
14. Khan R, Ranwah BR, Sharma V, Khandagale S. Combining ability analysis for grain and fodder traits in sorghum [Sorghum bicolor (L.) Moench]. Bangladesh J Bot. 2020;49:487-497.
15. Kohakade SN, Kute NS, Karvar SH, Jadhav GN, Shinde GC. Estimation of combining ability effect in mungbean [Vigna radiata (L.) Wilczek]. Int J Chem Studies. 2021;9(1):101-114.
16. Marappa N. Line × tester analysis in Mungbean (Vigna radiata (L.) Wilczek). Asian J of Bio Sci. 2008;3(2):289-294.
17. Mohan S, Sheeba A. Heterosis and combining ability analysis for yield and yield related traits in greengram (Vigna radiata L.). Electron J Plant Breeding. 2019;10(3):1255-1261.
18. Narasimhulu R, Naidu NV, Reddy KHP, Naidu MG. Combining ability and heterosis for yield and its attributes in greengram (Vigna radiata (L.) Wilczek). Ele J of Plt Breed. 2016;7(3):784-793.
19. Narasimhulu R, Naidu NV, Reddy KHP, Naidu GM. Combining ability for yield attributes in greengram (Vigna radiata (L.) Wilczek). The Bioscan. 2014;9(4):1667-1671.
20. Nath A, Maloo SR, Bharti B, Dubey RB, Verma R. Combining ability analysis in mungbean [Vigna radiata (L.) Wilczek]. Legume Res-An Int J. 2018;41:519-525.
21. Panse VG. Genetics of quantitative characters in relation to plant breeding. Indian J Genet. 1942;2:318327.
22. Pathak N, Singh DK, Kujur S, Singh MN. Combining ability studies for yield attributing traits in greengram. JNKVV Res J. 2019;53(1-3):81-86.
23. Purohit Y, Ravindrababu Y, Gami RA, Patel MP, Patel PT, Patel AM. Combining ability analysis for seed yield, its component and protein content in mungbean (Vigna radiata (L.) Wilczek). The Bioscan. 2016;11(3):1885-1889.
24. Rathod V, Pithia MS, Solanki HV. Combining ability analysis for yield and yield components in mungbean [Vigna radiata (L.) Wilczek]. Legume Research. 2020;43(1):151-154.
25. Sathya M, Jayamani P. Heterosis and combining ability studies in greengram. J of Food Legumes. 2011;24(4):282-287.
26. Sharma V, Dodiya NS, Dubey RB, Khandagale SG, Khan R. Combining ability analysis over environments in bread wheat. Electron J Plant Breed. 2019;10:13971404.
27. Singh AK, Singh SS, Prakash V, Kumar S, Dwivedi SK. Pulses Production in India: Present Status, Bottleneck and Way Forward. J of Agrisearch. 2015;2(2):75-83.
28. Singh P, Singh S, Jatav CBS, Bhargava MK, Puneet K. Combining ability and gene action for seed yield and its component traits in green gram (Vigna radiata L.). Ann of Plant and Soil Research. 2021;23(1):116-122. https://doi.org/10.47815/apsr.2021.10041.
29. Sujatha K, Kajjidoni ST. Genetic analysis involving selected powdery mildew resistant lines in mungbean (Vigna radiata (L.) Wilczek). Molecular Plant breeding. 2013;4(5):38-43.