Genotype a environment interaction and stability analysis on physicochemical traits of Malaysian rice hybrid across the environments

In the development of new varieties, physicochemical properties such as grain quality, milling, and chemical content are important. Twenty rice hybrids were tested in various environments in this study. Using multivariate and univariate models, the major goal is to identify rice hybrids with accepta...

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Bibliographic Details
Main Authors: S., Elixon, Y., Mohd Rafii, R., Asfaliza, J., Mashitah, R., Shairul Izzan
Format: Article
Published: Southern Cross Journals 2022
Online Access:http://psasir.upm.edu.my/id/eprint/101620/
https://www.cropj.com/april2022.html
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Summary:In the development of new varieties, physicochemical properties such as grain quality, milling, and chemical content are important. Twenty rice hybrids were tested in various environments in this study. Using multivariate and univariate models, the major goal is to identify rice hybrids with acceptable physicochemical properties and high stability. According to the ANOVA, variance due to season×genotype×location revealed a significant difference in length to width ratio, head rice recovery, and amylose content. Milled grain length and width varied from 6.64 to 7.32 mm and 1.78 to 2.06 mm, respectively, throughout the environments. The head rice recovery and amylose content, on the other hand, varied from 84.83 to 94.68% and 16.51 to 22.21%, respectively. The stability analysis for head rice trait using genotype superiority, static stability, Wrickie ecovelance, Nassar and Huehn, AMMI stability value, and coefficient of variation stability analysis, revealed that hybrids G2, G13, G8, G16, G7, G9, G6, G17, and G18 were the most stable. For Amylose content, hybrids G7, G4, G19, G10, G5, G17, G3, G12 and G11 were significantly stable. Except for G5, all hybrids demonstrated stable performance in the multivariate stability analysis for head rice recovery. Similarly, hybrids G3, G4, G5, and G7 responded in minimum GE interaction in multivariate analysis for amylose content. This discovery can help breeders pick potential hybrids by identifying the physicochemical attribute expression that was examined in different conditions.