Spatial model selection and design evaluation in the Ethiopian sorghum breeding program

Abstract

In plant breeding field experiments, proper statistical design and analysis improve precision of genotype comparisons. The focus of this study was to compare the precision of different spatial techniques in estimating genotypic effects using sorghum [Sorghum bicolor (L.) Moench] breeding data from Ethiopia and to investigate alternative design strategies maintaining overall field layout of the current trials while modifying the blocking (replicate, rows, and columns) structures compared to the current practice. The current trials comprise both partially replicated and fully replicated row–column designs where the field layout has short rows and long columns. For model comparison, six partially replicated row–column trials and 10 fully replicated row–column trials of sorghum were used. Relative efficiency calculations for the designs indicate that in most of the trials, alpha designs with block sizes of five, six, 10 and 15, and the alternative row–column designs were more efficient than the current design practice. Moreover, overall model comparison showed that augmenting the baseline model by a two‐dimensional nonlinear spatial model plus nugget improves the precision, while the randomization‐based plus two‐dimensional linear variance model and the randomization based plus a two‐dimensional nonlinear spatial model are also good candidate models. If row and column coordinates are available for all plots, the post‐blocking approach used here can be used in any breeding program and crop to explore alternative design options.