Modeling Illustrates That Genomic Selection Provides New Opportunities for Intercrop Breeding

Area of Science:

• Agricultural Science
• Plant Breeding
• Genetics

Background:

• Intercropping involves growing multiple crops together, improving soil health, pest control, and farm profitability, especially in subsistence farming.
• Breeding crops for intercropping is complex due to the need to simultaneously improve multiple crop varieties for optimal field performance.
• Genomic selection (GS) offers a potential solution to simplify and accelerate breeding programs for intercropping.

Purpose of the Study:

• To compare the effectiveness of genomic selection (GS) strategies against phenotypic selection (PS) in intercrop breeding programs.
• To evaluate the impact of genetic correlation between monocrop and intercrop yield on the performance of different breeding strategies.
• To propose an optimized GS strategy for enhancing intercropping ability and selection accuracy.

Main Methods:

• Stochastic simulation was used to model and compare four intercrop breeding programs utilizing GS with one program based on PS.
• Three distinct levels of genetic correlation between monocrop grain yield and intercrop grain yield were simulated.
• The simulations assessed the genetic gain achieved by each breeding strategy under varying genetic correlation scenarios.

Main Results:

• All four simulated GS breeding programs demonstrated significantly greater intercrop genetic gain compared to the PS program.
• The superiority of GS was consistent across all tested levels of genetic correlation between monocrop and intercrop yield.
• GS programs showed improved selection accuracy and reduced generation intervals, particularly when combining monocrop and intercrop trait data.

Conclusions:

• Genomic selection is a more effective approach than phenotypic selection for accelerating genetic gain in intercrop breeding.
• The proposed GS strategy, integrating monocrop and intercrop trait information, enhances prediction of general intercropping ability.
• Optimizing GS strategies can significantly improve selection accuracy and efficiency in developing superior intercrop varieties.