Improved genetic parameter estimations in zoysiagrass by implementing post hoc blocking

Abstract

Randomized complete block (RCB) design is the most widely used experimental design in biological sciences. As number of treatments increases, the block size become larger and it looses the capacity to control the variance within block, which is its original purpose. A method known as post hoc blocking could be used in these cases to improve the genetic parameter estimation and thus obtain an unbiased assessment of the performance of a given treatment. In trufgrass breeding, as other breeding program, this is a common challenge. The goal of this study was to test the capacity of different post hoc blocking designs to improve the genetic parameter estimation of zoysiagrass (Zoysia spp.). We evaluated two post hoc blocking designs; row–column (R–C) and incomplete block (IB) designs on five genotype trials located in Florida. The results showed that post hoc R–C design had superior model fitting than both the original RCB and the post hoc IB designs when studied at the single measurement level and at the site level. The narrow-sense heritability (0.24–0.40) and the genotype-by-measurement correlation (0.57–0.99) did not change significantly when R–C was compared to the original RCB design. The ranking of the top performing genotypes changed considerably when comparing RCB to R–C design, but the degree depended on the location analyzed. We conclude that the change in the ranking of the top (potentially select individuals) is coming from the better control of intra-block environmental variation, and this could potentially have a significant impact on the breeding selection process.