Effectiveness of Recurrent Selection in Irrigated Rice Breeding

Abstract

Plant breeding for quantitative traits is a complicated task; thus, the recurrent selection method has been used in the rice (Oryza sativa L.) breeding program at the Brazilian Agricultural Research Corporation (Embrapa). Our general objective was to assess the effectiveness of this method in achieving genetic progress, maintaining genetic variability, and increasing the potential for selection of superior lines. A genetically broad‐based population of irrigated rice, CNA12S, submitted to three selection cycles was used in this study. The dataset comprised 10 yield trials, in which 667 S1:3 progenies and six check cultivars were assessed for grain yield, plant height, and days to flowering. We measured effective population size in each cycle, using standard and linkage disequilibrium methods, and Nei's genetic diversity in the third cycle. Such analyses were performed using data of single‐nucleotide polymorphism markers from progenies of the third cycle. For estimating the genetic gain, we adapted a generalized linear regression method to the Bayesian approach. This approach was also used to estimate variance and covariance components, according to the multivariate linear mixed model. Magnitudes of genetic and relative variation coefficients, as well as Nei's genetic diversity, indicated maintenance of genetic variability over cycles. Mean genetic gain per year was 1.98% for grain yield and −1.29% for days to flowering. Genetic potential of the population for extraction of superior lines was increased, considering single‐, two‐, or three‐trait selection. Our results show the effectiveness of the recurrent selection method when applied in rice breeding, although some refinements in the selection strategy could further improve its efficiency.