Abstract
The aim of this research was to evaluate the consistency of path analyses in sugarcane experiments based on genetic, phenotypic and genotypic correlations. Forty-four analyses were made with a view toward quantifying the direct and indirect effects of stalk height (SH), stalk diameter (SD) and number of stalks (NS) on sugarcane weight (SW). NS had the greatest direct effect on SW in all the analyses with the use of genetic and phenotypic correlations and in 12 analyses with use of the genotypic correlations. SD had a high direct effect on SW, going beyond NS in only one experiment, while SH had the lowest direct effect on SW in most of the experiments. The results showed greater consistency with the use of genetic and phenotypic correlations. In the balanced experiments, the phenotypic and genetic correlations showed equivalent results. NS is the main determinant of changes in sugarcane production.
Highlights
The use of correlation coefficients is relevant for quantification of the associability between two variables (Falconer and Mackay 1996)
The results showed greater consistency with the use of genetic and phenotypic correlations
The aim of this study is to evaluate the consistency of the results of path analysis in different sugarcane experiments through the use of genetic, phenotypic and genotypic correlations, as well as identifying the variable which has the greatest effect on sugarcane weight (SW), with a view toward optimizing the selection process of sugarcane families in the field
Summary
The use of correlation coefficients is relevant for quantification of the associability between two variables (Falconer and Mackay 1996). Correlation might not be a measure of cause and effect, and direct interpretation of its magnitudes may result in mistakes in selection strategy. Path analysis allows the correlation coefficients to be broken down into direct and indirect effects on a main variable (Tyagi and Lal 2007). The use of this methodology in sugarcane breeding programs is highly worthwhile in its initial stages because the methodology aims at indicating the most adequate characteristics so that indirect selection be made of the most productive families since quantifying their production is quite a slow job due to the large number of genotypes assessed in these stages (Barbosa and Silveira 2012). Knowledge of a consistent pattern of relationship between the component variables of production may present new perspectives on estimating sugarcane weight (SW), which is usually practiced in studies where the plots are not harvested and sugarcane weight is estimated in accordance with Chang and Milligan (1992)
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