A new Bayesian approach to the Toler model for evaluating the adaptability and stability of genotypes

Abstract This study aimed to apply, in unprecedented depth, a Bayesian approach to the non-linear regression model developed by Toler for evaluating the stability and adaptability of genotypes. Twenty-five soybean cultivars were evaluated in twenty-one plots across the midwestern of Brazil. A complete block design was employed, with three replications. The evaluated variable was grain yield. The proposed methodology was implemented in the R program by means of the BRugs package. The methodology was capable of differentiating the effect of the environment on soybean cultivars in terms of yield in the different environments, allowing exploration of the response of each genotype to environmental variations. Cultivars 6266RSF, NS6990, GD19I435, GD19I439, GD19C443, RC0496 and IA18661 presented good stability and general adaptability, being the most recommended for future evaluations. The other cultivars presented specific adaptability and high responsiveness to unfavorable environments.

摘要 本研究旨在以空前的研究深度，将贝叶斯方法（Bayesian approach）应用于Toler开发的用于评估基因型稳定性与适应性的非线性回归模型（non-linear regression model）。本研究于巴西中西部地区的21个试验地块中，对25个大豆品种开展评价。试验采用完全区组设计，设置3次重复，评价指标为籽粒产量。本研究所提方法借助BRugs软件包在R语言中得以实现。该方法可有效区分不同环境下环境对大豆品种产量的影响，能够探究各基因型对环境变化的响应规律。品种6266RSF、NS6990、GD19I435、GD19I439、GD19C443、RC0496及IA18661表现出优异的稳定性与广泛适应性，为未来试验的首选推荐品种。其余品种则呈现特异性适应性，且对不良环境具备较高的响应能力。