Improving Soybean Variety Trial Analysis with Augmented Models

  • Jixiang Wu South Dakota State University
  • Adams Appiah
  • Rebecca Helget
Keywords: Augmented experimental design, blocking design, linear mixed model approach, and soybean


Plant breeders intend to evaluate a large number of new varieties in order to select genotypes with great yield potential through various variety trials. Thus, a large experimental field may be needed. A prerequisite in most experimental designs is homogeneity among experimental plots within each block. However, it is sometimes difficult to ensure that experimental plots are uniform within each field block regarding soil fertility and soil conditions that may significantly impact yield and other important traits. In this study, a classical randomized complete block (RCB) with three field replications (row-blocking) was “augmented” based on the field plot layout in a one-year soybean variety trial. Data for yield and yield components of 12 soybean varieties were collected and analyzed with several augmented models. Results showed that variety had highly significant impacts on grain yield, 100-pod weight, and seed 100-pod weight. Soil heterogeneity existed in the row direction for yield. Further analyses showed that, soil conditions contributed to the significance impact of cultivar on grain yield but number of seeds, 100-pod weight, or 100-pod seed weight was not significantly affected.


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