Genomic selection for genotype performance and environmental stability in Coffea canephora

Area of Science:

• Agricultural Science
• Plant Breeding
• Genetics

Background:

• Coffee sustainability is crucial, with plant breeding offering a key strategy for enhancing crop performance and meeting market needs.
• Genotype-by-environment interactions present challenges in coffee breeding due to the crop's perennial nature and long juvenile phase, impacting selection and grower satisfaction.
• Trait stability in coffee is hypothesized to be genetically controlled and predictable using molecular information.

Purpose of the Study:

• To investigate the genetic control of trait stability in coffee.
• To assess the predictability of stability metrics using genome-based methods.
• To enable the simultaneous selection of coffee genotypes with high phenotypic performance and stability.

Main Methods:

• Utilized genome-based methods for genomic prediction of stability metrics.
• Evaluated two populations of Coffea canephora across multiple years and locations.
• Computed stability metrics to guide the selection of superior coffee genotypes.

Main Results:

• Demonstrated that the number of harvest evaluations can be reduced, accelerating molecular breeding implementation.
• Confirmed that coffee trait stability metrics are predictable using genomic information.
• Showed that stable and high-performance genotypes can be simultaneously predicted and selected.

Conclusions:

• Genomic prediction is an efficient tool for selecting coffee genotypes that combine high performance and stability.
• Accelerated molecular breeding in coffee is achievable through reduced evaluation periods.
• This approach enhances the selection of robust coffee cultivars for diverse environments and production systems.