Understanding of Yield Stability in Jack Bean (Canavalia ensiformis L.) Genotypes using AMMI and GGE bi-plot Models

Abstract

Background: Jack bean is an under-exploited legume species, a source of food, medicine and cover crop. By virtue of its adaptive nature to low fertility soils, it is one of the few pulses that grow well on highly leached, nutrient depleted, lowland tropical soils. But, in India, crop improvement work is very little done. Stability of yield is a major criterion for farmer’s acceptability of any variety and there are several methods to estimate the stability and G x E interaction effects of a genotype across seasons. Among these, AMMI analysis is the most recent and widely exploited in different crops for the identification of stable genotypes. In this context, yield stability of 10 accessions of jack bean is studied to identify the stable genotypes.Methods: The experiment was conducted with 10 Jack bean genotypes in RCBD with two replications under rain fed conditions during 2017-2020 in Kharif for four seasons. The data was subjected to analysis of variance and then taken for AMMI and GGE analysis for identification of stable genotypes.Result: The combined analysis of variance revealed that there was highly significant variation (p less than 0.01) in grain yield and environments and genotype interaction among the genotypes. The average bean yield of the genotypes was 533.1 grams per plant. The highest and the lowest mean yield was recorded in PSR-12202 and CHMJB-02 respectively which was corroborated by the AMMI bi-plot as well. Similar to the AMMI bi-plot, the GGE bi-plot also confirmed that PSR-12202 was the stable genotype across the environments, whereas, G1, G2, G3, G4, G6, G7 and G8 were the other genotypes with low yields in some or all the environments. Kharif, 2018 and Kharif, 2020 are discriminating environments and are declared as the most representative than Kharif, 2017 and Kharif, 2019. Generally, PSR-12202 was the ideal genotype with higher mean yield and relatively good stability; G5 was the moderately good yielding genotype and the most unstable genotype; Whereas, G1, G2, G3, G4, G6, G7 and G8 were the poorly yielding and unstable genotypes. Both AMMI and GGE bi-plot are able to establish the genotypic stability and these models can be exploited for judging the genotypes for their GEI in other crops as well.

Studies on the Effect of Water Stress on Root Traits in Green Gram Cultivars

“…The screening followed by selections of desirable genotypes is important for successful breeding to develop the elite lines having drought tolerance capacity (Feller, 2006, Saidaiah et al, 2021. Different morphological, physiological and biochemical parameters have been established for drought stress tolerance assessment in plants based on proline accumulation, leaf area index, yield component etc (Alderfasi et al, 2017;Swathi et al, 2017).…”

Analysis of Genetic Variability, Heritability and Genetic Advance for Yield and Yield Related Traits in Chilli (Capsicum annuum L.)

“…Improvement of any crop depends on magnitude of genetic variability and the extent of heritability of economically important characters, though the part played by environment in the expression of such character also needs to be taken into account. Plant breeding programs focus on increasing crop yield in a wide range of growing conditions (Saidaiah et al, 2021a). Hence new genotypes must be characterized to assess the variability and identify promising genotypes which can be used in further breeding programmes (Munshi et al, 2000;Sarma and Roy, 1995, Sreelathakumary and Rajamony, 2004, Pidigam et al, 2021.…”

“…Generally, genotypic coefficient of variability (GCV) and phenotypic coefficient of variability (PCV) are measured to study the variability. Heritability estimates give a measure of transmission of characters from one generation to another (Sabri et al, 2020, Saidaiah et al, 2021a. After all, the trait improvements that can be made through direct selection are estimated by the availability of heritable variation (Khan et al, 2020).…”