Strategy for early selection for grain yield in soybean using BLUPIS.

Area of Science:

• Plant breeding and genetics
• Quantitative genetics
• Agricultural science

Background:

• Traditional soybean breeding relies heavily on individual plant selection in early generations, which is time-consuming.
• Developing efficient selection methods for early generations is crucial for accelerating breeding programs.

Purpose of the Study:

• To evaluate the efficiency of Simulated Individual BLUP (BLUPIS) for early-stage soybean breeding.
• To assess the viability of dividing experimental plot areas for genotypic effect estimation and plant selection.
• To compare BLUPIS with traditional Individual BLUP (BLUPI) for selecting soybean plants.

Main Methods:

• Utilized 84 segregating soybean populations and 15 parent lines across F2 and F3 generations.
• Collected yield data over two cropping seasons (2019/2020 and 2020/2021).
• Compared BLUPIS and BLUPI methods, incorporating strategies like plot area division and off-season generation advancement.

Main Results:

• BLUPIS and BLUPI demonstrated high concordance in selecting superior plants.
• Dividing plot areas proved effective for selecting populations and individual plants in the F3 generation.
• Achieved genetic gains of approximately 1.56 g per plant through this selection strategy.

Conclusions:

• BLUPIS is a powerful statistical tool for early selection of soybean based on grain yield.
• The combined strategy of BLUPIS and plot area division accelerates the breeding process and increases homozygosity.
• This approach significantly reduces the time required for soybean breeding programs.