AMMI-Bayesian perspective in the selection of pre-cultivars of carioca beans in Agreste-Sertão of Pernambuco, Brazil.

The productivity of beans is greatly influenced by the different edaphoclimatic conditions in the Agreste-Sertão region, requiring the identification of adapted and stable genotypes to minimize the effects of the interaction between genotypes per environments (GxE). The objective of this work was to analyze the adaptability and stability of carioca bean pre-cultivars in three municipalities in the Agreste-Sertão of Pernambuco using the AMMI model in its Bayesian version BAMMI and compare the results with the frequentist approach. According to the results, the BAMMI analysis showed better predictive capacity, as well as better performance in the study of adaptability and stability. The cultivar BRS Notável stood out in terms of main effect and stability. Adaptability of genotypes to specific locations was also observed, enabling the use of the positive effect of the GxE interaction, which was more evident with the BAMMI model. From this work, the flexibility of BAMMI model to deal with data resulting from multi-environmental experiments can be seen, overcoming limitations of the standard analysis of the AMMI model.