Populus VariantDB v3.2 is a searchable database that catalogs sequence polymorphisms across heterozygous poplar genomes, enabling precise design of guide RNAs and primers for CRISPR genome editing in outcrossing tree species. The tool accepts short sequence inputs, supports multiple Populus genomes (including hybrids), and provides customizable search parameters to improve gRNA/primer design accuracy. Its platform‑agnostic and expandable architecture makes it broadly applicable to sequence‑sensitive functional genomics studies.

The study evaluated 11 intermediate phenotypes linked to stalk lodging resistance in a diverse panel of 566 maize (Zea mays L.) inbred lines across four environments, preserving individual stalk identity to capture plant-level variation. This high-density phenotypic dataset enabled statistical genomics, predictive modeling, and machine learning to uncover genetic factors underlying lodging resistance, offering insights applicable to other grass species.

The study utilizes explainable artificial intelligence (XAI) combined with machine learning to assess how inter‑annual weather variability influences oilseed sunflower yields across the United States from 1976 to 2022. Key climate predictors, especially summer maximum temperature and total precipitation, were identified, and predictive models were projected under various Shared Socioeconomic Pathways to 2080, revealing region‑specific yield declines.