Agronomía Costarricense ISSN Impreso: 0377-9424 ISSN electrónico: 2215-2202

OAI: https://www.revistas.ucr.ac.cr/index.php/agrocost/oai
Genetic correlations in afila pea (Pisum sativum L.)
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How to Cite

Riascos Delgado, M. E., & Checa Coral, O. E. (2020). Genetic correlations in afila pea (Pisum sativum L.). Agronomía Costarricense, 44(2). https://doi.org/10.15517/rac.v44i2.43089

Abstract

Introduction. The pea is a profitable crop in Nariño-department which represents approximately 43% of pea production in Colombia and involves around 8000 farmers dedicated to its production in green pod. The farmers use varieties with high production costs, thus an improvement in profitability of this crop is neccesary. The University of Nariño’s Andean Crops research group, obtained 21 advanced pea lines with afila (af) gene. These lines present appropriate phenotypic characteristics to efficiency optimize of actual tutoring system. Objective. To determine the direct and indirect effects that are present in genetic correlations between the yield and its components, to contribute to the selection by yield of genotypes peas with afila (af) gene. Materials and methods. The 21 lines were evaluated in a splits plot design, where the main plot was the densities and the subplot were the genotypes. The results were subjected to analysis of variance and the genetic correlations between yield components were determined. To establish the direct and indirect effects of the components over yield, Path coefficient was made. Results. 73% of the genetic correlations between yield components were significant. The weight one hundred green grains (PCGV) and number of pods per plant (NVP) corresponded to the variables with the greatest direct effect. Conclusion. Genetic correlations analysis indicates that is possible to select genotypes with higher weight pod from the length of their pods. The direct effects NVP and PCGV were the most important, confirming their usefulness in selection by yield.

Keywords: Lines; system of tutoring; varieties; yield components; path coefficient.

https://doi.org/10.15517/rac.v44i2.43089
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