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

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction
methods have been proposed including the standard additive genetic effect model for which …

LightGBM is an ensemble model of decision trees for classification and regression
prediction. We demonstrate its utility in genomic selection-assisted breeding with a large …

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 …

Technological developments have revolutionized measurements on plant genotypes and
phenotypes, leading to routine production of large, complex data sets. This has led to …

Warming and drought are reducing global crop production with a potential to substantially
worsen global malnutrition. As with the green revolution in the last century, plant genetics …

Artificial intelligence (AI) has ena-bled recent step changes in some fields, most notably in
predicting three-dimensional structures of proteins and producing generative text on diverse …

Key message Safeguarding crop yields in a changing climate requires bioinformatics
advances in harnessing data from vast phenomics and genomics datasets to translate …

Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates
are predicted using genome wide marker information. Although numerous examples of GP …

The advancements in genomics and biomedical technologies have generated vast amounts
of biological and physiological data, which present opportunities for understanding human …