メタボロミクス誘導による干ばつ耐性作物の育種：気候スマート農業のためのマルチオミクスとAIの統合

Drought stress is among the most critical threats to global food security, and its complex impact on plant physiology often exceeds the reach of traditional breeding approaches. Metabolomics has emerged as a transformative tool for dissecting drought responses, enabling dynamic, systems-level characterization of primary and secondary metabolites that mediate osmotic balance, redox homeostasis, and stress memory. Unlike earlier reviews that mainly catalog stress-associated metabolites, this article emphasizes the integration of metabolomics with cutting-edge technologies, CRISPR-based genome editing, pathway engineering, synthetic biology, and artificial intelligence, to establish a translational framework for engineering drought-resilient crops. Recent advances in analytical platforms, bioinformatics pipelines, and crop-specific case studies are critically examined to demonstrate how metabolomic signatures can be converted into predictive biomarkers and incorporated into breeding pipelines. In addition, emerging frontiers such as single-cell and spatial metabolomics, ecological metabolomics, and AI-driven predictive modeling are highlighted as powerful directions for connecting laboratory discoveries with field-scale applications. By synthesizing technological and biological advances, this review outlines how metabolomics can evolve from a diagnostic tool into a predictive and prescriptive platform, positioning it as a cornerstone of climate-smart agriculture and next-generation crop improvement.