Revista: | Scientia Agricola |
Base de datos: | PERIÓDICA |
Número de sistema: | 000456223 |
ISSN: | 0103-9016 |
Autores: | Silva, Flavia Alves da1 Correa, Caio Cezar Guedes1 Carvalho, Beatriz Murizini1 Viana, Alexandre Pio1 Preisigke, Sandra da Costa1 Amaral-Junior, Antônio Teixeira do1 |
Instituciones: | 1Universidade Estadual do Norte Fluminense, Laboratorio de Melhoramento Genetico Vegetal, Campos dos Goytacazes, Rio de Janeiro. Brasil |
Año: | 2021 |
Volumen: | 78 |
Número: | 2 |
País: | Brasil |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Experimental, analítico |
Resumen en inglés | Multicollinearity is a very common problem in studies that employ path analysis in agronomic crops, which generates unrealistic results and erroneous interpretations. This study was aimed at assessing the path analysis in data obtained from guava tree full-sib based on modelling multiple regressions applying latent variables to neutralize the effects of multicollinearity. Seven explanatory variables were measured – fruit mass (FM), fruit length (FL), fruit diameter (FD), mesocarp thickness (MT), peel thickness (PT), pulp mass (PM), total number of fruits (NTF) –, plus the main dependent variable, total yield per plant (YIELD). In accordance with the multicollinearity scenario, eleven values were tested with the addition of the constant K to the diagonal of the correlation matrix X’X. Path analysis was applied in two models: all the explanatory variables with direct effect on the dependent one and another model with multiple regression with more than one chain and the presence of latent variables. The path analysis in the multivariate methodology of structural equation modelling (SEM), which uses latent variable prediction, provided better results than the traditional and ridge path analyses |
Disciplinas: | Agrociencias |
Palabras clave: | Frutales, Guayaba, Psidium guajava, Genotipos |
Keyword: | Fruit trees, Genotypes, Guava, Psidium guajava |
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