Abstract
This study aimed to determine the best auxiliary trait for indirect selection of soybean grain yield, through path analysis and in avoidance of the adverse effects of multicollinearity and expected response. Seventy-nine F5 soybean genotypes from the cross FT-Cometa x Bossier were used. The populations were distributed on the field was the families inserted with replicated controls. Primary and secondary traits of grain yield were evaluated in four phenotypically superior plants per family. The traits number of pods, height and number of nodes were considered as the most important, showing the best combination of direct effect and genotypic correlation. The number of pods achieved the highest expected gain through the estimation method based on the selection differential. On the other hand, plant height, by the method based on selection intensity, was not a good indicator of the most productive plants.
Highlights
In an improvement program it is essential to know the magnitude of association between traits, so breeders can understand how the selection of one trait can cause alterations in others (Johnson et al 1955, Vencovsky and Barriga 1992)
It is possible to achieve an indirect improvement of a trait with complex inheritance and low heritability through the selection of another trait, with a more simple inheritance or higher heritability
Four phenotipically superior plants were picked from each family for an evaluation of the following agronomic traits considered primary for yield (GY): number of pods per plant (NP), number of seeds per pod (NS) and weight of one seed in g/seed (W1S) and as secondary traits: number of days to flowering (NDF), number of days to maturation (NDM), plant height at maturation (PHM), insertion height of the first pod (IHP) and number of nodes (NN)
Summary
In an improvement program it is essential to know the magnitude of association between traits, so breeders can understand how the selection of one trait can cause alterations in others (Johnson et al 1955, Vencovsky and Barriga 1992). To deepen the understanding on the reasons of the association between traits, Wright (1921) proposed a method called path analysis that partitions the estimated correlations in direct and indirect effects of traits on a basic variable. This method has recently been studied in some crops by Santos et al (1995), Carvalho et al (1999), Reis et al (2001), Kurek et al (2001), Carvalho et al (2002) and others. Bandeirantes, 2419, 14.030-670, Ribeirão Preto, SP, Brasil 4 Embrapa Algodão, Rua Oswaldo Cruz, 1143, Centenário, C.P. 174, 58.107-720, Campina Grande, PB, Brasil
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