Soil salinization inhibits plant growth and seriously restricts food security and agricultural
development. Excessive salt can cause ionic stress, osmotic stress, and ultimately oxidative …

Recently, Artificial intelligence (AI) has emerged as a revolutionary field, providing a great
opportunity in shaping modern crop breeding, and is extensively used indoors for plant …

Deep learning is impacting many fields of data science with often spectacular results.
However, its application to whole-genome predictions in plant and animal science or in …

Key message Transposon insertion polymorphisms can improve prediction of complex
agronomic traits in rice compared to using SNPs only, especially when accessions to be …

Crops, because of their sessile lifestyle, inevitably experience dynamic environmental
conditions, and their capacity to adapt to these changes is central to their growth, survival …

Sugarcane has a complex, highly polyploid genome with multi‐species ancestry. Additive
models for genomic prediction of clonal performance might not capture interactions between …

Estimation and prediction play a key role in breeding programs. Currently, phenotyping of
complex traits such as nitrogen use efficiency (NUE) in wheat is still expensive, requires …

Background: Many studies have demonstrated the utility of machine learning (ML) methods
for genomic prediction (GP) of various plant traits, but a clear rationale for choosing ML over …

The agriculture industry has evolved significantly over the last 50 years. Technology
developments have led to larger, quicker, and more productive farm equipment, enabling …

Providing food for the growing population is a challenging task, however, with historical
agricultural practices, we can't meet the food requirement of the world population. We are in …