Selection of S0:2 maize progenies using a mixed-model approach

Abstract

In breeding programs, obtaining breeding lines was important, and first selfing selection generations is common. In addition, an analytic approach through mixed models can lead to more success in genotype selection because it lends flexibility in analysis of unbalanced data and provides more precise genotypic values in regard to progenies evaluated. The goal of this study was to make early selection (in the S 2 generation) of progenies evaluated in top crosses, using a mixed-model approach. Five hundred S 2 progenies were plant derived from three populations using selection intensity (40%), which were crossbreeding with three testers. The hybrids obtained, together with control treatments, were set up in five experiments in Brazil: three in Minas Gerais, one in Santa Catarina, and one in Paraná, which evaluated grain yield. The REML method was used for calculation of variance components, and means were predicted through BLUP. The BLUPs of general combining ability (GCA) and specific combining ability (SCA) were also predicted, and the Spearman correlation coefficients among BLUPs were estimated. The dominance effects had a bigger influence on yield expression, as seen from wider amplitude in SCA values. There was an 86% coincidence considering strategy in which selection index was carried out within three populations, in relation to selection by the overall value of GCA. Considering superior hybrids, the progenies of population C exceeded the quantity of hybrids expected by 24.6%, whereas there was a reduction of 30.8% for A and 20% for B. The hybrids that exhibited the highest BLUP means were derived from crosses between progenies of population C together with the tester LE84. The low correlation among testers, both for SCA and for BLUPs, indicates that there is progeny per tester interaction.