Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid...

Area of Science:

• Plant breeding
• Quantitative genetics
• Agricultural science

Background:

• Genomic selection (GS) and doubled haploids (DH) can improve crop breeding efficiency.
• Optimizing breeding programs requires evaluating different strategies for parent selection and trait evaluation.

Purpose of the Study:

• To investigate optimal strategies for a sweet corn breeding program using stochastic simulations.
• To compare the effectiveness of different parental substitution ratios and genomic selection models.

Main Methods:

• Stochastic simulations over 20 years.
• Assessed parental substitution ratios (3:1, 1:1, 1:3, 0:1).
• Compared genomic selection in testcross parents (GSTC) vs. F1 individuals (GSF1), and doubled haploids with (DHGS) and without (DH) genomic selection.

Main Results:

• A 1:3 parental substitution ratio (75% new parents) maximized performance in conventional breeding.
• The GSTC model showed greater genetic gain than GSF1.
• The DHGS model reduced breeding cycle time from 5 to 4 years and enhanced hybrid gains.

Conclusions:

• Genomic selection and doubled haploids significantly improve sweet corn breeding efficiency.
• The DHGS model offers the most effective strategy for accelerated genetic gains and improved hybrid performance.