Overcoming collinearity in path analysis of soybean [Glycine max (L.) Merr.] grain oil content

Path analysis allows understanding the direct and indirect effects among traits. Multicollinearity in correlation matrices may cause a bias in path analysis estimates. This study aimed to: a) understand the correlation among soybean traits and estimate their direct and indirect effects on gain oil c...

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Bibliographic Details
Published in:PloS one 2020-05, Vol.15 (5), p.e0233290-e0233290
Main Authors: Viotto Del Conte, Murilo, Carneiro, Pedro Crescêncio Souza, Vilela de Resende, Marcos Deon, Lopes da Silva, Felipe, Peternelli, Luiz Alexandre
Format: Article
Language:English
Subjects:
Agricultural productivity
Biology and Life Sciences
Collinearity
Correlation
Correlation analysis
Culling
Edible Grain - genetics
Genetic aspects
Genetic research
Glycine max - genetics
Methods
Natural history
Path analysis
Phenotype
Plant Breeding
Plant selection
Prejudice
Proteins
Quantitative Trait Loci
Soybean Oil
Soybeans
Statistical analysis
Variables
Vegetable oils
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Summary:Path analysis allows understanding the direct and indirect effects among traits. Multicollinearity in correlation matrices may cause a bias in path analysis estimates. This study aimed to: a) understand the correlation among soybean traits and estimate their direct and indirect effects on gain oil content; b) verify the efficiency of ridge path analysis and trait culling to overcome colinearity. Three different matrices with different levels of collinearity were obtained by trait culling. Ridge path analysis was performed on matrices with strong collinearity; otherwise, a traditional path analysis was performed. The same analyses were run on a simulated dataset. Trait culling was applied to matrix R originating the matrices R1 and R2. Path analysis for matrices R1 and R2 presented a high determination coefficient (0.856 and 0.832, respectively) and low effect of the residual variable (0.379 and 0.410 respectively). Ridge path analysis presented low determination coefficient (0.657) and no direct effects greater than the effects of the residual variable (0.585). Trait culling was more effective to overcome collinearity. Mass of grains, number of nodes, and number of pods are promising for indirect selection for oil content.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0233290