Sugarcane is a major industrial crop cultivated in tropical and subtropical regions of the
world. It is the primary source of sugar worldwide, accounting for more than 70% of world …

Genomic Selection (GS) is a method in plant breeding to predict the genetic value of
untested lines based on genome-wide marker data. The method has been widely explored …

Modern whole-genome prediction (WGP) frameworks that focus on multi-environment trials
(MET) integrate large-scale genomics, phenomics, and envirotyping data. However, the …

Envirotyping is an essential technique used to unfold the nongenetic drivers associated with
the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package …

Technology advances have made possible the collection of a wealth of genomic,
environmental, and phenotypic data for use in plant breeding. Incorporation of …

In sunflower, molecular markers for simple traits as, eg, fertility restoration, high oleic acid
content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or …

The development of crop varieties with stable performance in future environmental
conditions represents a critical challenge in the context of climate change. Environmental …

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 …

Kernel methods are flexible and easy to interpret and have been successfully used in
genomic-enabled prediction of various plant species. Kernel methods used in genomic …

Deep learning (DL) is a promising method for genomic-enabled prediction. However, the
implementation of DL is difficult because many hyperparameters (number of hidden layers …