The spatial arrangement and plant population have been highlighted as fundamental tools for increasing productivity. The objective was to evaluate the vegetative and productive performance of two soybean cultivars at different plant densities. Seeds of soybean cultivars (TMG 7063 IPRO and BS 2606 IPRO), recommended for the Alto Paranaíba region in the state Minas Gerais, were used and sown at seven different densities (8, 10, 12, 14, 16, 18 and 20 plants meter-1, equivalent to 160, 200, 240, 280, 280, 320, 360 and 400 thousand plants hectare-1, where they were evaluated in the development stages R1 (plant height) and R8 (height of the insertion of the first pod, plant height, number of nodes, number of branches, productivity per plant and productivity per hectare). The experiment was set up according to a randomized block design, in the factorial scheme A x B, being factor A composed by the cultivars and factor B by plant densities with three repetitions (blocks). Increased plant population resulted in greater first pod insertion height and final plant height, fewer nodes and branches and the average yield per hectare increased linearly, with the TMG 7063 IPRO cultivar being more productive under these conditions (52.7 bags of 60 kg per hectare).
The soybean crop is prominent in national and international scenarios. A large part of the world production of soybean is cultivated in Brazil and this has been possible due to the performance of different technological areas, among them genetics and plant breeding. Soybean breeding has acted in the development and launch of new cultivars and for this it is required the studies of interaction genotypes x environments and those of adaptability and stability. Thus, the objective was to evaluate the adaptability and phenotypic stability of the grain yield of late-cycle soybean genotypes. Five experiments were conducted in the state of Minas Gerais, each of which was considered as an environment. In each, 17 soybean genotypes were evaluated in a randomized block design with three repetitions, for grain yield, in kg ha-1. The data were analyzed by means of individual (each environment) and joint analysis of variance. Subsequently, analyses of adaptability and phenotypic stability were performed using the methods of Eberhart and Russell (1966), Artificial Neural Networks (Nascimento et al., 2013) and Centroid (Rocha, Muro‑Abad, Araujo, & Cruz, 2005). The results indicated the classification of the analyzed genotypes for unfavorable, general or favorable adaptability, with high or low stability. DM-339 is indicated for favorable environments and UFV-18 (Patos de Minas), UFV91-651226, UFV99-8552093, UFV01-871375B, UFV01-66322813 and UFV99-8552099 are indicated as general adaptability, considering the three methods of adaptability and stability analysis.
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