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Plant Science Today (PST)

Review Articles

Vol. 13 No. sp2 (2026): Recent Advances in Agriculture

Unravelling the trait genetics in cool season legumes using generation mean analysis

DOI
https://doi.org/10.14719/pst.14058
Submitted
10 February 2026
Published
09-06-2026

Abstract

Generation mean analysis (GMA) is a biometrical technique in plant breeding, used to elucidate the non-allelic interactions (NAI) associated with polygenic traits. The GMA utilises a maximum of 6 generations of a cross: P1 and P2 (parents), F1 and F2 (first and second filial generations) and BC1 and BC2 (back cross). The GMA is a two-step process: Estimation of, (i) epistatic interaction using a scaling test and (ii) effects of genetic components. Such dissection helps a breeder to select optimal plant breeding methods for improving the crop of interest. Cool-season legumes (CSL) owe macro and micronutrient richness and thereby assume nutritional significance. The CSL warrant genetic improvements to feed the rapidly growing global population. The role of classical hybridisation techniques is particularly important. To harness the improvement, a compiled genetic information on CSL is highly essential, which is yet to be published. Therefore, this review compiles the botanical introduction, nutritional significance and breeding behaviour of CSL. In addition, the genetic studies involving the GMA in CSL from 2012 to 2025 are compiled. Many GMA studies were published in major CSL like chickpeas and in the underutilised but potential legumes like horse gram it is yet to be published. From the GMA, it is inferred that (i) the six-parameter model with combined scaling (individual and joint scale) test is predominantly utilised and (ii) both additive and non-additive gene effects govern many of the yield and its contributing traits. However, non-additive effects (dominant gene) showed high magnitude with duplicate epistatic gene interaction suggesting utilisation of biparental hybridisation or recurrent selection for improvement.

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