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Research Article Open access CC BY 4.0

Biplot Analysis of Field Pea Genotypes by Environment Interaction and Yield Stability across Eight Environments in Arsi Zone

Gebeyaw Achenef Haile, Gizachew Yilma Kebede, Temesgen Abo Eritro

Asian Journal of Research in Crop Science · pp. 14–23 · Published 10 Aug 2022

10.9734/ajrcs/2022/v7i330142

Abstract

Plant breeding, agronomy, and genetic studies involving interactions between G x E heavily use the GGE biplot tool for data visualization. This study aims to identify robust genotypes with high yields across different environments and suitable environments based on biplot analysis. Fourteen field pea (Pisum sativum L.) advanced genotypes were evaluated at Arsi zone for two years (2014-2015) main cropping season across eight environments using randomized complete block design with four replications. There was a significant difference (P<0.001) in grain yield based on genotype, year, location, and the interaction of (G x L, Y x G). In this study, genotypes responded differently to different environments and at different times of the year. There was a range between 3509 kg/ha (G6) and 2809.5 kg/ha (G12) for the highest and the lowest mean grain yields. According to the mean and stability view of the GGE biplot, G6 followed by G1 was the most productive genotype in all environments except E5 and E6, while G5, G12, and G9 were the least productive. Based on the polygon view, five sectors were formed, and genotypes G13, G8, G6, G3, and G5 won. The G6 was an ideal choice in terms of mean yield and stability (high mean yield and adaptable). It was considered desirable to have genotypes G1, G4, and G3 closest to an ideal genotype. In most environments, G6 is a more adaptable genotype than any other genotype, making it a more suitable genotype for commercial production.

Field pea GGE biplot G x E interaction environment yield stability

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Cited by 4

Genotype × environment interaction and stability analysis of advanced field pea (Pisum sativum L.) genotypes in Southeastern Ethiopia

Gizachew Yilma Kebede, Temesgen Abo Eritro, Deressa Tesfaye Gutu · Ecological Genetics and Genomics · 2024

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