Correlations and canonical variables applied to the distinction of soybean cultivars in a tropical environment

Abstract

The objective of this study was to evaluate the performance of soybean cultivars through their correlations and canonical variables in a tropical environment. The study was conducted in the municipality of Mineiros, GO, Brazil. The soil was classified as Quartzarenic Neosol (Entisol). The experimental design used was in randomized blocks consisting of 10 soybean cultivars (Bônus, Desafio, Flecha, Foco, ICS7019, M5917, M7110, Power, ST721 and ST797) in four replications. Before planting, pre-planting desiccation was performed. The fertilizer used was 450 kg ha-1 of fertilizer 05-25-15 applied in the furrow and in a single dose next to the seeding. During the conduct of the experiment, pest control was carried out respecting good practices and integrated management. At the end of the cycle of each cultivar, 10 plants were collected at random and then the agronomic attributes were taken. The data obtained were submitted to the assumptions of the statistical model, verifying the normality and homogeneity of the residual variances, as well as the additivity of the model. Univariate and multivariate models were used. The analyzes were performed on the Rbio and R interface, in addition to the Software Genes. According to the summary of analysis of variance, it was observed that all cultivars differed for all characteristics. It was concluded that the soybean cultivars Flecha and M5917 presented the highest yields among the others in a tropical environment; the cultivars differed, showing a strong correlation between the number of grains per plant and yield, with the other variables analyzed; the univariate and multivariate tools were efficient and complementary in data analysis.

Soybean seedling performance in diferente seed treatments

“…Soybean (Glycine max (L.) Merrill) is a legume originating in China and one of the main agricultural commodities in Brazil and in the world (Bernardeli et al, 2020;Ferreira et al, 2022). Its high importance is due to the fact that it has high levels of oil (20%) and, mainly, protein (40%) (Lopes, Vello, Pandini, Rocha, & Tsutsumi, 2002), as well as nutrients such as nitrogen (51.9 g Kg-1), phosphorus (3.7 g kg-1) and potassium (17 g kg-1) (Loro et al, 2021), which justifies its economic importance, as it is used for the manufacture of animal feed (Ministério da Agricultura, Pecuária e Abastecimento [MAPA], 2018).…”