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

Genomic prediction tools support crop breeding based on statistical methods, such as the
genomic best linear unbiased prediction (GBLUP). However, these tools are not designed to …

The potential to add significant value to the rapid advances in plant breeding technologies
associated with statistical whole-genome prediction methods is a new frontier for crop …

The diverse consequences of genotype-by-environment (GxE) interactions determine trait
phenotypes across levels of biological organization for crops, challenging our ambition to …

Plant geneticists and breeders have used marker technology since the 1980s in quantitative
trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but …

Quantitative genetics states that phenotypic variation is a consequence of the interaction
between genetic and environmental factors. Predictive breeding is based on this statement …

Some of the biological knowledge obtained from fundamental research will be implemented
in applied plant breeding. To bridge basic research and breeding practice, machine learning …

Breeding crops for high yield and superior adaptability to new and variable climates is
imperative to ensure continued food security, biomass production, and ecosystem services …

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement
in plants. Traditional methods typically use linear regression models with clear assumptions; …

Highlights•High throughput phenotyping with genomic association.•Rapidly identifies
candidate genes.•Enables separation of pleiotropy and linkage to overcome …