The first paradigm of plant breeding involves direct selection-based phenotypic observation,
followed by predictive breeding using statistical models for quantitative traits constructed …

Predicting phenotype with genomic and environmental information is critically needed and
challenging. Machine learning methods have emerged as powerful tools to make accurate …

Enviromics refers to the characterization of micro-and macroenvironments based on large-
scale environmental datasets. By providing genotypic recommendations with predictive …

The growing global demands for agricultural goods will require accelerated crop
improvement. High-throughput genomic, phenomic, enviromic and other multi-omic data …

Phenotypic plasticity is an important topic in biology and evolution. However, how to
generate broadly applicable insights from individual studies remains a challenge. Here, with …

Maize phenotypes are plastic, determined by the complex interplay of genetics and
environmental variables. Uncovering the genes responsible and understanding how their …

The past decade has witnessed rapid developments in gene discovery, biological big data
(BBD), artificial intelligence (AI)‐aided technologies, and molecular breeding. These …

The dual challenges of global population explosion and environmental deterioration
represent major hurdles for 21st Century agriculture culminating in an unprecedented …

Genomic prediction (GP) and genome-wide association studies (GWAS) employ genetic
variants (markers) to predict phenotypic performance and identify superior genotypes. In …

With the continuous growth of the global population, insufficient food production has become
an urgent problem to be solved in most countries. At present, using artificial intelligence …