Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Early Access

Association studies for yield-contributing agronomic traits and identification of lipoxygenase-2 free genotypes for reduced off-flavour in soybean (Glycine max)

DOI
https://doi.org/10.14719/pst.10003
Submitted
12 June 2025
Published
02-07-2026
Versions

Abstract

Soybean (Glycine max) is a key legume crop that holds a pivotal position in global agriculture, especially in India, where its productivity and cultivation area are relatively low. Improving soybean yield is imperative to meet increasing demand, yet seed yield is a complex trait influenced by various environmental factors. This study aimed to evaluate the genetic variability, heritability, genetic advance and interrelationships among yield-contributing traits in 135 genotypes. Significant differences were observed in all traits, except for the number of branches per plant (NBP) and number of seeds per pod (NSP). High heritability and genetic advance were recorded for traits such as plant height, NBP and number of pods per plant (NPP), indicating the predominance of additive gene action for these traits. Correlation and path analysis revealed that the NPP had the most significant direct effect on single plant yield, followed by the number of clusters per plant (NCP) and the NSP. Furthermore, the study identified soybean genotypes free from lipoxygenase-2, an enzyme responsible for undesirable off-flavours, using SSR markers. The genotype MACS 1281 was found to be free from lipoxygenase-2, making it an ideal candidate for human consumption and for incorporation into breeding programs focused on developing new soybean varieties with reduced off-flavours. These findings provide valuable insights into soybean breeding strategies aimed at both yield enhancement and quality improvement.

References

  1. 1. Hao Y, Zhang JY, Zhang CB, Bao P, Zhang WL, Wang PN, et al. Genetic effects and plant architecture influences on outcrossing rate in soybean. J Integr Agric. 2019;18(9):1971–9. https://doi.org/10.1016/S2095-3119(18)62054-4
  2. 2. United States Department of Agriculture, Foreign Agricultural Service. Oilseeds: world markets and trade [Internet]. Washington (DC): USDA Foreign Agricultural Service; 2021 [cited 2026 May 15].
  3. 3. Humtsoe ZB, Shah PK, Chaturvedi H. Correlation and path analysis studies among soybean genotypes under foothill conditions of Nagaland. Indian Res J Genet Biotechnol. 2017;9(3):397–404.
  4. 4. Burton GW. Quantitative inheritance in grasses. Proc 6th Int Grassl Congr. 1952:277–83.
  5. 5. Doyle JJ. Isolation of plant DNA from fresh tissue. Focus. 1990;12:13–5.
  6. 6. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J. 1955;47:314–8. https://doi.org/10.2134/agronj1955.00021962004700070009x
  7. 7. Falconer DS. Introduction to quantitative genetics. 4th ed. Harlow: Pearson Education; 1996.
  8. 8. Wright S. Correlation and causation. J Agric Res. 1921;20(7):557–85.
  9. 9. Lush JL. Intra-sire correlations or regressions of offspring on dam as a method of estimating heritability of characteristics. J Anim Sci. 1940;1940(1):293–301. https://doi.org/10.2527/jas1940.19401293x
  10. 10. Dewey DR, Lu KH. A correlation and path-coefficient analysis of components of crested wheatgrass seed production. Agron J. 1959;51(9):515–8. https://doi.org/10.2134/agronj1959.00021962005100090002x
  11. 11. Lenka D, Misra B. Path-coefficient analysis of yield in rice varieties. Indian J Agric Sci. 1973;43:376–9.
  12. 12. Shilpashree N, Devi SN, Manjunathagowda DC, Muddappa A, Abdelmohsen SA, Tamam N, et al. Morphological characterization, variability and diversity among vegetable soybean (Glycine max L.) genotypes. Plants. 2021;10(4):671. https://doi.org/10.3390/plants10040671
  13. 13. Baria A, Akabari V, Gohil V. Variability studies for seed yield and its components in soybean. J Genet Genomics Plant Breed. 2022;6(2):54–9.
  14. 14. Neelima G, Mehtre S, Narkhede G. Genetic variability, heritability and genetic advance in soybean. Int J Pure Appl Biosci. 2018;6(2):1011–7. https://doi.org/10.18782/2320-7051.5982
  15. 15. Kumar S, Kumari V, Kumar V. Genetic variability and trait association studies for seed yield and component traits in soybean (Glycine max (L.) Merrill) under north-western Himalayas. Legume Res. 2020;43(4):7–11.
  16. 16. Baraskar V, Kachhadia V, Vachhani J, Barad H, Patel M, Darwankar M. Genetic variability, heritability and genetic advance in soybean (Glycine max (L.) Merrill). Electron J Plant Breed. 2014;5(4):802–6.
  17. 17. Chandrawat KS, Baig KS, Hashmi S, Sarang D, Kumar A, Dumai PK. Study on genetic variability, heritability and genetic advance in soybean. Int J Pure Appl Biosci. 2017;5(1):57–63. https://doi.org/10.18782/2320-7051.2592
  18. 18. Satpute GK, Gireesh C, Shivakumar M, Arya GK, Patel RK, Gupta R, et al. Genetic variability and association studies in new soybean germplasm accessions. Soybean Res. 2016;14(2):77–83.
  19. 19. Banerjee J. Phenotypic and yield associated trait characterization in advanced breeding lines of soybean. Electron J Plant Breed. 2022;13(2):597–607. https://doi.org/10.37992/2022.1302.075
  20. 20. Jandong E, Uguru M, Okechukwu E. Estimates of genetic variability, heritability and genetic advance for agronomic and yield traits in soybean (Glycine max L.). Afr J Biotechnol. 2020;19(4):201–6.
  21. 21. Mofokeng MA. Genetic variability, heritability and genetic advance of soybean (Glycine max) genotypes based on yield and yield-related traits. Aust J Crop Sci. 2021;15(12):1427–34. https://doi.org/10.21475/ajcs.21.15.12.p3303
  22. 22. Mahawar R, Pawar L, Koli N, Chaudhary H, Dayong D, Ali M. Assessment of genetic variability, correlation and path analysis of quantitative traits in soybean (Glycine max (L.) Merrill). Soybean Res. 2013;11:70–7.
  23. 23. Mahbub MM, Shirazy BJ. Evaluation of genetic diversity in different genotypes of soybean (Glycine max (L.) Merrill). Am J Plant Biol. 2016;1(1):24–9.
  24. 24. Machado B, Nogueira A, Hamawaki O, Rezende G, Jorge G, Silveira I, et al. Phenotypic and genotypic correlations between soybean agronomic traits and path analysis. Genet Mol Res. 2017;16(2):1–11. https://doi.org/10.4238/gmr16029696
  25. 25. Chavan B, Dahat D, Rajput H, Deshmukh M, Diwane S. Correlation and path analysis in soybean. Int Res J Multidiscip Stud. 2016;2(9):1–5.
  26. 26. Quijano A, Morandi EN. Leaf area reduction during the pod set period changes the photomorphogenic light balance and increases the pod number and yield in soybean canopies. Field Crops Res. 2023;303:109148. https://doi.org/10.1016/j.fcr.2023.109148
  27. 27. Balla MY, Ibrahim SE. Genotypic correlation and path coefficient analysis of soybean (Glycine max (L.) Merr.) for yield and its components. Agric Res Tech. 2017;7(3):1–5.
  28. 28. Sileshi Y. Estimation of variability, correlation and path analysis in soybean (Glycine max (L.) Merr.) genotypes at Jimma, south western Ethiopia. J Nat Sci Res. 2019;9(7):22–9.
  29. 29. Badaya VK, Gill BS, Meenakshi D. Diversity and association analysis for yield contributing and morphological traits in soybean (Glycine max (L.) Merrill). Bioscan. 2016;11(1):107–12.
  30. 30. Jain RK, Joshi A, Chaudhary HR, Dashora A, Khatik CL. Study on genetic variability, heritability and genetic advance in soybean (Glycine max (L.) Merrill). Legume Res. 2018;41(4):532–6. https://doi.org/10.18805/LR-3874
  31. 31. Patil S, Naik M, Patil P, Shinde D. Genetic variability, correlation and path analysis in soybean. Legume Res. 2011;34(1):36–40.

Downloads

Download data is not yet available.