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

Investment in technological research is imperative to stimulate the development of
sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and …

A major bottleneck in the crop improvement pipeline is our ability to phenotype crops quickly
and efficiently. Image-based, high-throughput phenoty** has a number of advantages …

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

Optical sensors and sensing-based phenoty** techniques have become mainstream
approaches in high-throughput phenoty** for improving trait selection and genetic gains …

Genomic prediction tools support crop breeding based on statistical methods, such as the
genomic best linear unbiased prediction (GBLUP). However, these tools are not designed to …

Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including
healthcare, finance, transportation, and education. Within healthcare, AGI is being utilized to …

Reproducible computational research (RCR) is the keystone of the scientific method for in
silico analyses, packaging the transformation of raw data to published results. In addition to …

Key message Safeguarding crop yields in a changing climate requires bioinformatics
advances in harnessing data from vast phenomics and genomics datasets to translate …

Understanding the function of genes within staple crops will accelerate crop improvement by
allowing targeted breeding approaches. Despite their importance, a lack of genomic …