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首页> 外文期刊>Andhra Agricultural Journal >Phenotypic Stability Analysis in Italian Millet Utilizing Regression and AMMI Models for Yield Characters
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Phenotypic Stability Analysis in Italian Millet Utilizing Regression and AMMI Models for Yield Characters

机译:利用回归和AMMI模型对意大利小米的表型稳定性进行分析

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Twenty italian millet genotypes were evaluated for several characters over 16 environments (8 sowing dates with 2 fertility levels).The analysis of variance of Eberhart and Russell indicated that GxE interaction was significant for all 5 characters under study and that genotypes differed significantly. AMMI is a useful tool for interpreting genotype x environment interaction in multi environment trials. 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 five characters under study. The ANOVA indicated non-significant G x E interaction for 1000 grain weight and ANOVA of (Eberhart and Russell, 1966) indicated non-significant GxE (linear) interaction for productive tillersper plant, ear length, 1000 grain weight, when tested against pooled deviation. As per AMMI analysis the IPCA, significantly contributed to productive tillers per plant, ear length, ear weight, 1000 grain weightand grain yield per plant while IPCA_2 contributed significantly to G x E interaction for productive tillers per plant, ear length, ear weight and 1000 grain weight. This brings out clearly the advantage of AMMI ANOVA in bringing out G x E interaction through IPCA, 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 other analysis. According to AMMI analyses the genotypes GS 463 andGS 480 (for productive tillers plant~(-1)); GS 477, GS486 and SRL (for ear length); GS 467, GS 477, GS 479 and NSR (for ear weight); GS 440, GS 444 and NSR (for 1000 grain weight); most of the genotypes (for grainyield plant~(-1)) were more stable as the IPCA score was near zero indicating less interaction with environments. According to Eberhart and Russell the genotypes GS 480 and GS 489 (for productive tillers plant1); GS 487 and GS 444 (for ear length); GS 440 and GS 477 (for ear weight); SRL (1000 grain weight); GS 450 and GS 467 (for grain yield plant~(-1)) showed stage performance.
机译:在16个环​​境中评估了20个意大利小米基因型的几个字符(8个播种期,育性水平为2).Eberhart和Russell的方差分析表明,所研究的所有5个字符的GxE交互作用均显着,并且基因型差异显着。 AMMI是在多环境试验中解释基因型x环境相互作用的有用工具。在AMMI组件中,对于所研究的五个字符,前四个IPCA轴比其他IPCA轴解释了G x E交互作用的大部分。方差分析表示1000谷粒重量的G x E交互作用不显着(Eberhart和Russell,1966)的结果表明,当对分till性进行测试时,生产力分till植物,穗长,1000粒重的GxE(线性)交互作用不明显。根据AMMI分析,IPCA显着促进了每株植物的生产分till,穗长,穗重,1000粒重和单株籽粒产量,而IPCA_2显着促进了每株植物的生产分G,穗长,穗重和1000粒的G x E相互作用谷物重量。这清楚地表明了AMMI ANOVA通过IPCA进行G x E交互的优势,该优势与其他两个ANOVA中的错误相结合,并指出了AMMI模型在研究重要的GxE交互和识别字符的稳定基因型方面的实用性,因此在其他分析中未被发现。根据AMMI分析,基因型GS 463和GS 480(用于生产型分till植物〜(-1)); GS 477,GS486和SRL(用于耳长); GS 467,GS 477,GS 479和NSR(用于耳重); GS 440,GS 444和NSR(用于1000粒重);由于IPCA评分接近零,表明与环境的相互作用较少,大多数基因型(对于单产植物〜(-1))更为稳定。根据Eberhart和Russell的说法,基因型为GS 480和GS 489(用于生产性分till植物1); GS 487和GS 444(用于耳长); GS 440和GS 477(用于耳朵重量); SRL(1000粒重); GS 450和GS 467(用于粮食丰产工厂〜(-1))具有阶段性。

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