首页> 外文会议>Conference of the International Society of Sugar Cane Technologists >ANALYSING G x E INTERACTION IN SUGAR CANE USING THE ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) MODEL
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ANALYSING G x E INTERACTION IN SUGAR CANE USING THE ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) MODEL

机译:使用添加剂主要效应和乘法相互作用(AMMI)模型分析甘蔗中的G X E相互作用

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Variety trials are conducted with several genotypes in different environments to provide reliable information for selecting high yielding varieties. The Genotype x Environment interaction should be considered while selecting varieties for specific sites. As this interaction must be determined with accuracy, the statistical model utilised must be appropriate. In this paper, the AMMI model is applied using matrix algebra and the statistical software GENSTAT. Cumulative results of plant cane and three ratoons for the characters cane yield (TCH), Industrial Recoverable Sucrose % Cane (IRSC), and sugar yield (TSH) were analysed. The commonly used analysis of variance (ANOVA) failed to detect a significant interaction whereas AMMI analysis revealed a highly significant interaction for TCH and TSH. The mean square (MS) of the principal component analysis (PCA) axis 1 was five to seven times the MS for the residual of the three characters. The AMMI model partitioned the interaction sum of square (SS) and summarised the data quite effectively. Environments were characterised in terms of low and high yielding ones. The Biplot method grouped the genotypes and environments and displayed their response patterns where their potential and weaknesses were clearlyillustrated. Varieties for both wide and specific adaptations were depicted, e.g. variety R570 had a low principal score indicating wide adaptation. As the AMMI analysis gives a more accurate picture of the phenotypic stability of each of the varietiesgrown under different environments, this information can be very useful when recommending varieties for commercial cultivation.
机译:各种试验在不同环境中用几种基因型进行,以提供用于选择高产品种的可靠信息。应考虑基因型X环境相互作用,同时选择特定网站的品种。由于这种相互作用必须以准确性确定,所使用的统计模型必须适当。在本文中,使用矩阵代数和统计软件Genstat应用了AMMI模型。分析了植物甘蔗累积结果,为特征蔗油屈服(TCH),产业可回收蔗糖%甘蔗(IRSC)和糖产量(TSH)。常用的方差分析(ANOVA)未能检测到显着的相互作用,而AMMI分析揭示了TCH和TSH的非常显着的相互作用。主要成分分析(PCA)轴1的平均方形(MS)为三个字符的残余的5至7倍。 AMMI模型将平方(SS)的交互和分区,并非常有效地汇总了数据。环境的特征在于低屈服和高屈服。双批方法分组了基因型和环境,并显示了他们的响应模式,其中他们的潜力和缺点是明确的。描绘了广泛和特定适应的品种,例如,品种R570具有低主要评分,表明适应宽。随着AMMI分析给出了在不同环境下每个品种的表型稳定性的更准确的图像,在推荐商业栽培品种时,这些信息可能非常有用。

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