Strategy for early selection for grain yield in soybean using BLUPIS

In soybean breeding programs, a great deal of time is devoted to the use of methods that perform selection of individual plants during the initial generations. Our hypothesis is that BLUPIS (simulated individual BLUP) can be efficient when applied in the initial stages of soybean breeding programs. This study aimed to explore the potential of BLUPIS in the early generations of a soybean breeding program, as well as to assess the viability of the strategy of dividing the useful area of experimental plots for estimating genotypic effects and plant selection. The experiment involved 84 segregating populations and 15 soybean parents in the F and F generations. Yield data was collected from the 2019/2020 and 2020/2021 cropping seasons. In the F generation, different data exploration methods were applied to determine the most suitable adaptation to be used in the F generation. The individual BLUP (BLUPI) was compared with BLUPIS using information from different replications and/or equal to the information used in BLUPI. The selection conducted by BLUPIS and BLUPI showed high concordance regarding the selected plants. In the F generation, segregating populations were selected based on positive genotypic effects, and individual plants within these populations were further selected according to the number of plants determined by BLUPIS. The division of the plot area was an efficient strategy for selecting segregating populations and individual plants within superior populations in the F generation, resulting in genetic gains of approximately 1.56 g per plant. When combined with the strategy of advancing generations in the off-season, the BLUPIS approach reduces the time required to achieve a high level of homozygosity. Therefore, BLUPIS proved to be a powerful statistical tool for early selection based on grain yield in soybeans.