Bayesian estimation of adaptability and stability parameters in watermelon genotypes using the Toler model
Carla Caroline Alves Pereira, Maxsuel Marcos Fernandes de Lima, Adriano Ferreira Martins, Francismária Freitas de Lima, Nynyve Thaynar Brito de Almeida, Edicleide Macedo da Silva, Lindomar Maria da Silveira and Glauber Henrique de Sousa Nunes
Abstract: The objective of this study was to evaluate the adaptability and phenotypic stability of watermelon hybrids across diverse environments in the semiarid region of Rio Grande do Norte, Brazil, using Toler’s simple linear and piecewise linear models under both frequentist and Bayesian frameworks. The Bayesian analysis employed noninformative uniform priors and yielded classifications consistent with the frequentist results, reinforcing the robustness of the classification results. Genotypes in group A (WM-5, WM-6, WM-9, and WM-10) exhibited low sensitivity to adverse environmental conditions and high responsiveness in favorable environments, along with high phenotypic stability. The results demonstrate that Bayesian approaches are a reliable complement
to conventional analyses, thereby supporting breeding strategies and cultivar recommendations for semiarid regions while enhancing the robustness of frequentist inference through explicit quantification of uncertainty.