Research & Development Excellence
Bridging traditional plant breeding with cutting-edge genomic technologies across tea, canola, ornamentals, and bioenergy crops
Genomic Selection Strategy
Help breeding programs optimize trait selection using predictive models (linear mixed models and machine learning models).
Sparse Testing
Optimize resources by reducing the cost of multi-environment breeding trials through efficient experimental designs.
Trait Heritability Analysis
Offer statistical insights into breeding value, genetic variance, and environmental influence on traits.
Genotype by Environment (GxE) Analysis
Identify and interpret interactions between genotypes and environments to guide variety recommendations and adaptive breeding decisions.
Breeding Program Design
Advise on crossing schemes, trial design, selection intensity, and data analysis pipelines for improved genetic gain.
Genome-Wide Association Study (GWAS) and QTL Mapping
Detect genomic regions associated with important traits to accelerate marker-assisted and genomic selection strategies.