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Genotype by environment interaction and stability analysis for rice genotypes under Boro condition

机译:Boro条件下水稻基因型的环境互作和稳定性分析

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摘要

Genotype (G)×Environment (E) interaction of nine rice genotypes possessing cold tolerance at seedling stage tested over four environments was analyzed to identify stable high yielding genotypes suitable for boro environments. The genotypes were grown in a randomized complete block design with three replications. The genotype × environment (G×E) interaction was studied using different stability statistics viz. Additive Main effects and Multiplicative Interaction (AMMI), AMMI stability value (ASV), rank-sum (RS) and yield stability index (YSI). Combined analysis of variance shows that genotype, environment and G×E interaction are highly significant. This indicates possibility of selection of stable genotypes across the environments. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two principal components (PC1-PC2) were highly significant (P0.05). The partitioning of TSS (total sum of squares) exhibited that the genotype effect was a predominant source of variation followed by G×E interaction and environment. The genotype effect was nine times higher than that of the G×E interaction, suggesting the possible existence of different environment groups. The first two interaction principal component axes (IPCA) cumulatively explained 92 % of the total interaction effects. The study revealed that genotypes GEN6 and GEN4 were found to be stable based on all stability statistics. Grain yield (GY) is positively and significantly correlated with rank-sum (RS) and yield stability index (YSI). The above mentioned stability statistics could be useful for identification of stable high yielding genotypes and facilitates visual comparisons of high yielding genotype across the multi-environments.
机译:分析了在四种环境下测试的9种耐寒性水稻基因型在幼苗期的基因型(G)×环境(E)相互作用,以鉴定适合于硼环境的稳定高产基因型。基因型在具有三个重复的随机完整区组设计中生长。利用不同的稳定性统计数据研究了基因型×环境(G×E)的相互作用。加性主效应和乘性相互作用(AMMI),AMMI稳定性值(ASV),秩和(RS)和产量稳定性指数(YSI)。方差的综合分析表明,基因型,环境和G×E相互作用非常显着。这表明有可能在整个环境中选择稳定的基因型。 AMMI(加性主效应和乘性相互作用)分析结果表明,前两个主要成分(PC1-PC2)高度显着(P <0.05)。 TSS的划分(总平方和)表明,基因型效应是变异的主要来源,其次是G×E相互作用和环境。基因型效应比G×E相互作用高9倍,表明可能存在不同的环境群体。前两个交互主成分轴(IPCA)累计解释了总交互效果的92%。研究表明,根据所有稳定性统计数据,发现基因型GEN6和GEN4是稳定的。谷物产量(GY)与秩和(RS)和产量稳定性指数(YSI)呈正相关且显着相关。上述稳定性统计数据可用于鉴定稳定的高产基因型,并有助于在多环境中目视比较高产基因型。

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