Repeatability coefficient for fruit quality and selection of mango hybrids using REML/BLUP analysis

Abstract

Abstract Mango is a tropical fruit of significant economic, social, and nutritional importance. However, the low diversity of commercial mango orchards in Brazil highlights the need to broaden the genetic base of this crop. From this perspective, this study aimed to select mango genotypes for cultivation under semi-arid conditions using the mixed model methodology: restricted maximum likelihood/best linear unbiased prediction (REML/BLUP). Two hundred and ninety-two plants were evaluated over two crop seasons using fifteen traits related to fruit quality. The statistical analyses were performed with the software Selegen. The repeatability coefficient estimates (r) ranged from 0.06 to 0.97, and were considered high for most variables. The selective accuracy predicted by REML for the evaluated parameters ranged from 0.25 to 0.98, revealing a good degree of confidence in the inferences. For all evaluated traits there was a genetic gain with selection. Twelve genotypes were selected as the most promising using the minimum selection indices proposed in this study, showing higher mean values for all evaluated traits. These genotypes can be selected for new stages of the mango breeding program in the Brazilian semi-arid region.