Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression

Abstract

The aim of this study was to evaluate the relative importance of agronomic traits during the individual selection in sugarcane (Saccharum spp.), as well as evaluate the potential for using logistic regression and decision trees in identifying the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated in the first test phase (T1) and 659 clones were selected for the second (T2). Logistic regression was applied in both populations (T1 and T2). The number of stalks, bud prominence and length of the internode were the most important traits in selection the T1. Plant vigour, stalk diameter and stalk height were the most important traits in selection the T2. There were 174 individuals selected by the mass selection method in T1 and 113 individuals in T2, while logistic regression selected 153 individuals in T1 and 79 in T2. The apparent error rates of the logistic models fitted to the selections in T1 and T2 were 0.8 and 5.10%, respectively. By using a decision tree, 67 clones were selected among the most productive ones in phase T2. The formulation of decision trees is therefore highly applicable to identifying potential clones in the initial phases of genetic breeding programs.