Ailian Zhou

A Two-Step Hybrid Statistical and Machine-Learning Framework with Full Genetic Effects for Multi-Environment Genomic Prediction in Maize

Accurate genomic prediction across environments remains challenging because phenotypic variation is jointly influenced by environmental conditions, genetic effects, and genotype-by-environment interactions. We developed a two-step hybrid statistical and machine-learning framework...

Structured Multi-Kernel Heteroscedastic Gaussian Process for Crop Straw-to-Grain Ratio Prediction and Uncertainty Quantification

Crop straw-to-grain ratio (SGR) estimation underpins regional straw resource assessment, yet national inventories rely on fixed coefficients that ignore structured variation across variety, environment, and phenotype. We introduce a Structured Multi-Kernel Heteroscedastic Gaussia...