Abstract
Abstract: This study aimed to evaluate the relationship between fruit traits and their direct and indirect effects on the content of ascorbic acid and ca - rotenoids in peaches and nectarines. The traits fruit mass (FM); equatorial diameter (ED); suture diameter (SD); polar diameter (PD); pulp firmness (FIR); soluble solids (SS); titratable acidity (TA); SS/TA ratio; contents of ascorbic acid (AA) and carotenoids (CT); and skin and pulp color were evaluated in 28 peach cultivars, and two nectarine cultivars. The phenotypic correlation coefficients were estimated (rf), and after multicollinearity diagnosis, unfolding was carried out in direct and indirect effects of the explanatory variables in the response variable by using path analysis. The strongest correlations were found between FM, SD, ED, and PD, and between carotenoid content and °h pulp. The traits considered in the path diagrams are not the main determinants of the ascorbic acid content. The yellow color of the pulp has the potential for indirect selection for carotenoid content.
Highlights
Correlated responses are common in breeding programs for selection of variables which are difficult to be measured, or when the measurements are expensive
The knowledge of these relationships allows obtaining a main variable of low heritability, and/or of difficult measurement to be selected based on another (s) variable (s), providing the breeder a more rapid progress than that used for direct selection
The strongest positive correlations were observed between fruit mass (FM), suture diameter (SD), equatorial diameter (ED) and polar diameter (PD)
Summary
Correlated responses are common in breeding programs for selection of variables which are difficult to be measured, or when the measurements are expensive. Understanding the relationship between variables is crucial, since obtaining genetic gains and choosing the best genotypes often rely on a set of agronomic and commercial variables The knowledge of these relationships allows obtaining a main variable of low heritability, and/or of difficult measurement to be selected based on another (s) variable (s), providing the breeder a more rapid progress than that used for direct selection. It is important, the simple correlation coefficient may create misconceptions regarding the relationship between two variables, and may not be a true cause and effect measurement. The success of the path analysis is based on the most consistent formulation of the cause-effect
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