OpenAlex:
Artificial Intelligence in Plant Sciences
OpenAlex:
Artificial Intelligence in Plant Sciences
OpenAlex:
sRNA_seq_clean_thrips_leafdiscs_timeseries
OpenAlex:
sRNA_seq_clean_thrips_leafdiscs_timeseries
OpenAlex:
Color phenotyping and genome-wide association studies of ...
OpenAlex:
FUNCTIONAL STUDIES ON SIEVE ELEMENT-SPECIFIC PROTEINS
OpenAlex:
Understanding the control of perpetual flowering and cont...
OpenAlex:
Nuclear dynamics in Sclerotinia sclerotiorum
OpenAlex:
Artificial Intelligence in Plant Sciences
OpenAlex:
Artificial Intelligence in Plant Sciences
OpenAlex:
sRNA_seq_clean_thrips_leafdiscs_timeseries
OpenAlex:
sRNA_seq_clean_thrips_leafdiscs_timeseries
Better breeding leveraging more biology.
PubMed · 2026-06-26
Scientists are building smarter crop breeding tools that combine plant biology with predictive models, helping breeders develop crops that perform reliably even as climate patterns grow more erratic and unpredictable.
1
Climate variability is measurably reducing the ability to predict crop performance across different growing environments, slowing genetic improvement.
2
Integrating mechanistic plant biology into predictive breeding models improves accuracy, precision, and interpretability of breeding decisions.
3
Hierarchical genome-to-phenome frameworks offer a path to sustain long-term genetic gain under changing environmental conditions.