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Use of additive main effects and multiplicative interaction models to analyze multilocation rice variety trials

机译:利用加性主效应和乘性相互作用模型分析多地点水稻品种试验

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The usual additive effects model has long been used to analyze genotype and environment effects in international variety trials but it fails to offer insight into genotype-environment (GxE) interaction. Additive main effects and multiplicative interaction (AMMI) models provide insight into the environmental factors accounting for GxE interactions when analyzed in conjunction with environmental measurements. They can also improve the precision of estimation of genotype and environment effects and provide insight into stability and selection potential for the varieties. These characteristics of AMMI models is illustrated in the analysis of data from the 20th International Irrigated Rice Yield Nursery for Early maturing varieties from the International Network for Genetic Evaluation of Rice (INGER), which is coordinated by the International Rice Research Institute (IRRI). Results of the analysis indicate that sites in Southeast Asia are very similar with respect to adaptation of the test entries compared to sites in other regions. Hence, they could be reduced in favour of more discriminating sites. Genotypes tested interacted with low temperatures, nutrient status, and latitude. The latter indicating photoperiod sensitivity which was not thought to be present in these varieties. Adaptability domains are defined for the tested varieties and the AMMI model is Used to indicate the best adapted varieties for these domains.
机译:长期以来,在国际品种试验中,通常使用加性效应模型来分析基因型和环境效应,但未能提供关于基因型与环境(GxE)相互作用的见解。加性主效应和乘性交互作用(AMMI)模型可结合环境测量结果分析GxE交互作用的环境因素。它们还可以提高估计基因型和环境影响的精度,并提供有关品种稳定性和选择潜力的见识。 AMMI模型的这些特征在国际水稻研究所(IRRI)协调的国际水稻遗传评价国际网络(INGER)的第20届国际早稻品种国际灌溉水稻产量苗圃数据分析中得到了说明。分析结果表明,与其他地区的站点相比,东南亚的站点在测试条目的适应性方面非常相似。因此,可以减少它们以支持更具区分性的站点。测试的基因型与低温,营养状况和纬度相互作用。后者表明光周期敏感性,在这些品种中不存在。为测试品种定义了适应性域,AMMI模型用于指示这些域的最佳适应性品种。

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