Performance of common bean genotypes as a function of growing seasons and technological input levels

Authors

  • Rodrigo Zanella Federal University of Technology - Paraná
  • Daniela Meira Federal University of Technology - Paraná
  • Andrei Daniel Zdziarski Federal University of Technology - Paraná
  • Antonio Pedro Brusamarello Federal University of Technology - Paraná
  • Paulo Henrique de Oliveira Federal University of Technology - Paraná
  • Giovani Benin Federal University of Technology - Paraná

Abstract

In Brazil, common bean (Phaseolus vulgaris L.) is cultivated in different growing seasons and environments, with different genotypes responses due to the genotype x environment interaction. This study aimed to identify common bean genotypes with a better production stability in each growing environment. The trials were conducted in a randomized block design, with three replications, involving three growing years, nine common bean genotypes and four environments (first and second growing seasons with high and low levels of technological input, such as fertilizers and pest and disease control). Biplot analyses were performed using the GGE Biplot software. The use of high levels of technological input results in an average increase of 14.4 % for yield and is more representative in the crop environments, as well as more adequate for genotype selection. IPR Campos Gerais, BRS Esplendor and BRS Campeiro showed a high stability and presented the best productive performance under both technological levels.

KEYWORDS: Phaseolus vulgaris L., genotype x environment interaction, grain yield.

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Published

2019-07-11

How to Cite

ZANELLA, R.; MEIRA, D.; ZDZIARSKI, A. D.; BRUSAMARELLO, A. P.; DE OLIVEIRA, P. H.; BENIN, G. Performance of common bean genotypes as a function of growing seasons and technological input levels. Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics], Goiânia, v. 49, p. e54989, 2019. Disponível em: https://revistas.ufg.br/pat/article/view/54989. Acesso em: 25 nov. 2024.

Issue

Vol. 49 (2019)

Section

Research Article

License

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