Crop production systems need to expand their outputs sustainably to feed a burgeoning
human population. Advances in genome sequencing technologies combined with efficient …

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 …

Rice is considered one the most important plants globally because it is a source of food for
over half the world's population. Like other plants, rice is susceptible to diseases that may …

Food safety has emerged as a high-urgency matter for sustainable agricultural production.
Toxic metal contamination of soil and water significantly affects agricultural productivity …

Abstract Background Maize (Zea mays L.) is at the vanguard facing the upcoming breeding
challenges. However, both a super pan-genome for the Zea genus and a comprehensive …

Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …

Advances in high‐throughput omics technologies are leading plant biology research into the
era of big data. Machine learning (ML) performs an important role in plant systems biology …

In recent years, generation of large‐scale data from genome, transcriptome, proteome,
metabolome, epigenome, and others, has become routine in several plant species. Most of …

The green revolution successfully increased agricultural output in the early 1960s by relying
primarily on three pillars: plant breeding, irrigation, and chemical fertilization. Today, the …

Predicting phenotype with genomic and environmental information is critically needed and
challenging. Machine learning methods have emerged as powerful tools to make accurate …