Biometric approach applied to soybean genotypes cultivated in Rio Grande do Sul, Brazil

  • Ivan Ricardo Carvalho Universidade Regional do Noroeste do Estado do Rio Grande do Sul
  • Márcio Peter Universidade Federal de Pelotas
  • Gustavo Henrique Demari Universidade Federal de Pelotas
  • Danieli Jacoboski Hutra Universidade Regional do Noroeste do Estado do Rio Grande do Sul
  • Giordano Gelain Conte Universidade Federal de Pelotas
  • Christian Szambelam Zimmermann Universidade Regional do Noroeste do Estado do Rio Grande do Sul
  • José Gonzalez da Silva Universidade Regional do Noroeste do Estado do Rio Grande do Sul
  • Jaqueline Piesanti Sangiovo Universidade Regional do Noroeste do Estado do Rio Grande do Sul
Keywords: Biometric procedures, experimentation multivariate, Glycine max L, phenotypic plasticity, statistical models, selection

Abstract

The study had the purpose to evidence the agronomic performance, inter-relations of characters and the multivariate differentiation of soybean genotypes cultivated in the preferential season, in the state of Rio Grande do Sul, Brazil. In the crops season of 2017/2018, The experimental design was the completely randomized blocks, being 25 genotypes with three replicates. The data obtained was submitted to presuppositions based on normality and homogeneity of residual variances, variance analysis, Tocher method, Euclidian algorithm, linear correlations, relative contribution of characters by Singh and artificial neural networks. The agronomic performance of the genotypes presents superior seeds yield per plant through the elevated magnitude of reproductive nodes, legumes and seeds per plant. The plant height of the soybean is positively associated with the number of total nodes and reproductive nodes in the main stem and branches, where they are directly linked with the soybean productive potential. The most polymorphic characters correspond to the number and mass of thousand seeds, being possible to differentiate in a multivariate way the soybean genotypes though the similarity profiles.

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Published
2021-03-31
How to Cite
Carvalho, I. R., Peter, M., Demari, G. H., Hutra, D. J., Conte , G. G., Zimmermann, C. S., Silva, J. G. da, & Sangiovo, J. P. (2021). Biometric approach applied to soybean genotypes cultivated in Rio Grande do Sul, Brazil. Agronomy Science and Biotechnology, 7, 1-10. https://doi.org/10.33158/ASB.r118.v7.2021

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