Genomics, Multi-Omics, and Emerging Artificial Intelligence for Combined Drought-Heat Stress Resilience in Plants: A...

Combined drought-heat stress is not adequately described by adding the responses to drought and heat in isolation. Water limitation restricts evaporative cooling, whereas high temperature increases atmospheric demand and threatens photosynthesis, proteostasis, and reproduction. To assess what has been demonstrated rather than merely proposed, we combined a structured narrative review with a study-level evidence map spanning genomics, multi-omics, and emerging artificial intelligence (AI). The PubMed search, updated on 9 August 2026, returned 254 records; targeted and backward searches contributed eight seminal or reviewer-nominated publications. Independent screening retained 90 verified publications: 69 direct combined-stress studies, 11 genomics studies, six original AI or prediction studies, and four reviews or quantitative syntheses used for context. No conserved molecular signature emerged. Response direction varied with soil water status, vapor-pressure deficit, stress order, tissue, and developmental stage. Carbon allocation, redox and proteostasis balance, reproductive failure, and recovery recurred across omics layers, although neither their direction nor their adaptive value was consistent. Genomic loci and predictive performance were also environment dependent. Direct uses of AI remain uncommon and currently support prioritization more convincingly than causal inference. We organize this uneven evidence as a ladder extending from molecular association to functional validation, multi-environment prediction, and cultivar deployment. The main shortage is not another nominal omics layer but harmonized factorial experiments that measure recovery and reproduction, report field-relevant environmental metadata, and include external validation.