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Phenotypic Stability Analysis in Foxtail Millet for Quality Characters

机译:谷子品质性状的表型稳定性分析。

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Twenty italian millet genotypes were evaluated for three quality characters over 16 environments (8 sowing dates with 2 fertility levels).The analysis of variance of Eberhart and Russell indicated that G X E interaction was significant for all 3 characters under study and that genotypes differed significantly. Among the AMMI component first four IPCA axis were explained most of the portion of G X E interaction than other IPCA axis for the three characters under study. The ANOVA indicated non-significant G X E interaction for carotene content and ANOVA of (Eberhart and Russell, 1966) indicated non-significant G X E (linear) interaction for calcium content, when tested against pooled deviation. As per AMMI analysis the IPCA_1 significantly contributedto protein content, calcium content and carotene content while IPCA_2 contributed significantly to G X E interaction for protein content, calcium content and carotene content. This brings out clearly the advantage of AMMI ANOVA in bringing out G X E interaction through IPCA_1 which gets combined with error in the other two ANOVA and points out the utility of AMMI models in studying the significant GxE interaction and identifying stable genotypes for characters which so undetected in the earlier analysis. According to AMMI analyses the genotypes like GS 444 and GS 480 (for protein content); most of ihe genotypes (for calcium content); GS 445, GS 450 and PRD (for carotene content) are more stable because they are having IPCA score near zero that is theyshow less interaction with environments. According to Eberhart and Russell the genotypes like GS 488 and KDR (for protein content); GS 489, GS 463 and GS 479 (for calcium content) and GS 462 and GS 479 (carotene content) showed desirable performance.
机译:在16个环​​境中评估了20个意大利小米基因型的3个品质性状(8个播种期,育性水平2).Eberhart和Russell的方差分析表明,G X E交互作用在所有研究的3个性状中均显着,并且基因型差异显着。在AMMI组件中,对于所研究的三个字符,解释了G X E交互作用的大部分(而不是其他IPCA轴)是前四个IPCA轴。当针对合并偏差进行测试时,方差分析表明胡萝卜素含量的G X E交互作用不显着,(Eberhart和Russell,1966)的方差分析表明钙含量的G X E(线性)交互作用不明显。根据AMMI分析,IPCA_1显着贡献了蛋白质含量,钙含量和胡萝卜素含量,而IPCA_2显着贡献了G X E相互作用的蛋白质含量,钙含量和胡萝卜素含量。这清楚地表明了AMMI ANOVA通过IPCA_1进行GXE交互的优势,该交互与其他两个ANOVA中的错误相结合,并指出了AMMI模型在研究重要的GxE交互作用和识别稳定基因型方面的实用性,从而可以在较早的分析。据AMMI分析,基因型如GS 444和GS 480(用于蛋白质含量)。大多数基因型(钙含量); GS 445,GS 450和PRD(针对胡萝卜素含量)更稳定,因为它们的IPCA得分接近零,这表明它们与环境的相互作用较少。根据埃伯哈特(Eberhart)和罗素(Russell)的说法,基因型如GS 488和KDR(用于蛋白质含量)。 GS 489,GS 463和GS 479(钙含量)以及GS 462和GS 479(胡萝卜素含量)表现出理想的性能。

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