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

Summary Genotype‐by‐environment‐by‐management (G× E× M) interactions for crop
productivity represent both challenges and opportunities for long‐term crop improvement …

Key message Training sets produced by maximizing the number of parent lines, each
involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 …

Key message Sparse testing using genomic prediction can be efficiently used to increase
the number of testing environments while maintaining selection intensity in the early yield …

Genomic selection is a well-investigated approach that facilitates and supports selection
decisions for complex traits and has meanwhile become a standard tool in modern plant …

Key message Mating designs determine the realized additive genetic variance in a
population sample. Deflated or inflated variances can lead to reduced or overly optimistic …

Despite efforts to collect genomics and phenomics ('omics') and environmental data,
spatiotemporal availability and access to digital resources still limit our ability to predict …

Genome sequences indicate a wide variety of characteristics, which include species and
sub-species type, genotype, diseases, growth indicators, yield quality, etc. To analyze and …

Genome-assisted prediction of complex (eg, quantitative) traits is an ingredient of “Genomic
Selection,” a paradigm adopted successfully in animals and plants of agricultural …

Discovery and enrichment of favorable alleles in landraces are key to making them
accessible for crop improvement. Here, we present two fundamentally different concepts for …