Contribution of morphological traits for grain yield in common bean
DOI:
https://doi.org/10.14393/BJ-v34n2a2018-39701Keywords:
Path analysis, Genetic improvement, Phaseolus vulgaris L.Abstract
In Brazil, the common bean crop has representative agricultural exploitation, not only because of its production economic value, but also because there is a large cultivation area. This research aimed to investigate the direct and indirect relationship of morphological components on grain yield in common bean plants. This study was carried out in a Quartzarenic Neosol in the municipality of Cassilândia, Mato Grosso do Sul State, Brazil, in the agricultural year of 2016/2017. The evaluated traits were: grains yield (GY) with its primary components; mass of one hundred grains (HG); number of grains per plant (GP); number of grains per pod (GPP); dry weight of aerial parts (DWA); number of pod per plant (PP); plant dry mass (DM); plant high (PH); and stem diameter (SD). Initially, the Pearson's correlation among these traits was estimated and the correlation network was used to graphically express the obtained results. Analysis of these data through the statistical techniques of multicollinearity diagnosis followed by path analysis enabled to verify that the number of pod per plant, the mass of one hundred grains, and the number of grains per plant, among the primary components of grain yield, are the traits of greater potential to select and identify superior genotypes for grain productivity yield, and that dry matter and stem diameter traits showed a negative correlation with grain yield in common bean grains.Downloads
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Published
2018-03-26
How to Cite
DE OLIVEIRA, J.T., RIBEIRO, I. da S., ROQUE, C.G., MONTANARI, R., GAVA, R. and TEODORO, P.E., 2018. Contribution of morphological traits for grain yield in common bean . Bioscience Journal [online], vol. 34, no. 2, pp. 351–356. [Accessed22 November 2024]. DOI 10.14393/BJ-v34n2a2018-39701. Available from: https://seer.ufu.br/index.php/biosciencejournal/article/view/39701.
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Agricultural Sciences
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Copyright (c) 2018 Job Teixeira de Oliveira, Isabela da Silva Ribeiro, Cassiano Garcia Roque, Rafael Montanari, Ricardo Gava, Paulo Eduardo Teodoro
This work is licensed under a Creative Commons Attribution 4.0 International License.