Main conclusion Orphan crops can contribute to building resilience of marginal crop**
systems as a climate chnage adaptation strategy. Orphan crops play an important role in …

Machine learning techniques for crop genomic selections, especially for single-environment
plants, are well-developed. These machine learning models, which use dense genome …

Genomic selection is revolutionizing plant breeding and therefore methods that improve
prediction accuracy are useful. For this reason, active research is being conducted to build …

In plant and animal breeding, genomic prediction models are established to select new lines
based on genomic data, without the need for laborious phenoty**. Prediction models can …

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 …

Genomic and phenomic prediction (GP and PP, respectively) are innovative methods that
allow plant breeders to increase the productivity of crops. Traditional methods for conducting …

The oil palm, originating from Africa, is the most productive oil crop species. Palm oil is an
important source of edible oil. Its current global plantation area is over 23 million ha. The …

Macadamia breeding is in its infancy with most cultivars only two generations removed from
their wild progenitors. Two active breeding programs have released cultivars in the past …

Background Improving yield prediction and selection efficiency is critical for tree breeding.
This is vital for macadamia trees with the time from crossing to production of new cultivars …

To overcome the multiple challenges currently faced by agriculture, such as climate change
and soil deterioration, more efficient plant breeding strategies are required. Genomic …