Abstract

Pedigree-based best linear unbiased prediction (pBLUP) is an effective method for genetic evaluation. The objective of this study was to assess the efficacy of pBLUP to develop superior inbred lines, using field and simulated data. This study was based on the data of 30,986 plants from six S0 generations and eight inbred progeny trials (S1–S4), performed over eight years. We measured the grain yield and the expansion volume (EV). We also simulated the EV and grain yield of 5000 plants (S0–S4) in two in silico populations, assuming 300 and 400 genes distributed across 10 chromosomes of 200 cM, respectively, and 10% of pleiotropic genes. We selected selfed plants based on the predicted additive value for EV by fitting the individual model in inbred population. The use of pBLUP provided total genetic gains in EV in the range of 1 to 45%, inversely proportional to the level of improvement of the population, and indirect changes in grain yield in the range of −17 to 3%. Only from the analysis of the in silico populations, assuming selection based on the true additive value and genetic gain computed from the genotypic values, there was evidence that pBLUP is superior to phenotypic mass selection.

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