Rice is one of the world’s most important crops. The search for genotypes that are more productive and have wide adaptation to different environments is paramount. One of the major breeder’s obstacles faced is identification of superior strains is the presence of Genotype × Environment Interaction (GEI), which motivated the development of countless statistical procedures aiming to offer more efficient studies. In this work we analysed adaptability and stability of 13 upland rice lineages as part of a genetic improvement program in nine different environments, resulting from local combination and years of agriculture. The experiment was conducted in a completely randomized block design, with three replicates. The main variable is the grain storage in kg/ha. The model applied is the Bayesian Main Additive Effects and Multiplicative Interaction (Bayesian-AMMI). Our implementation implies an extra assumption of random effects from genotypes coming from a single population as opposed to previous works in the literature. Credibility regions with maximum posteriori density allowed identification of cultivars with higher average yield. Stable genotypes showed an initial evidence of adaptation to an environment in this rice breeding program. Bayesian-AMMI is flexible, and starts to be more widely used, but our suggestion is promising in making it a more powerful tool
The evaluation of breeding lines for prior recommendation in different environments is a step that requires a high level of investment. This evaluation is extremely important, especially when the objective of breeding is to select lines with high homeostasis, adaptability associated with high yield, and stability. Thus, this paper aimed to study the phenotypic plasticity of thirteen upland rice lines for grain yield in multiple environments of Minas Gerais State, Brazil. The experiments were installed in nine different environments corresponding to the combination of locations and agricultural years. Thirteen elite lines were used, originating from a partnership between UFLA (Federal University of Lavras), Epamig (Agricultural Research Company of Minas Gerais) and Embrapa (Brazilian Company of Agricultural Research) Rice and Beans. The experiments were conducted in a complete randomized block design with three replicates. Culture treatments used for conducting were the same as those recommended for culture. The evaluated character was grain yield (kg.ha-1). Adaptability and stability were estimated by the methods Wricke, Annicchiarico, and Lin and Binns. All experiments showed average productivities above average in the state of Minas Gerais. The methods by Anniccchiarico and Lin Binns were efficient for the lines identification with phenotypic plasticity, emphasis on the lines CMG 2097, CMG 1896 and CMG 2089, which obtained superior average performance with productivities higher than 5 t.ha-1. Thus, these lines are promising for the Minas Gerais state recommendation, as well as in similar environments under low fertility natural soil, ferralsol (latosols), with tropical semi-humid and tropical altitude.
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