Engineering abiotic stress tolerance in cereal crops: current advances and future directions
Cereal Research Communications, vol.54, no.3, pp.1317-1344, 2026 (SCI-Expanded, Scopus)
- Publication Type: Article / Review
- Volume: 54 Issue: 3
- Publication Date: 2026
- Doi Number: 10.1007/s42976-026-00804-1
- Journal Name: Cereal Research Communications
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS
- Page Numbers: pp.1317-1344
- Keywords: Abiotic stress tolerance, Cereal crops, CRISPR/Cas9, Multi-omics, Pangenomics, Climate resileince
- Ataturk University Affiliated: Yes
Abstract
Abiotic stresses, including drought, salinity, heat, and nutrient imbalances, severely constrain cereal crop productivity and pose a growing threat to global food security under climate change. While traditional breeding has contributed to crop improvement, its limited speed and resolution necessitate the integration of advanced biotechnological approaches. Recent developments in genome editing, particularly CRISPR/Cas systems, alongside marker-assisted selection, genomic selection, and multi-omics technologies, have enabled precise manipulation of stress-responsive genes and accelerated trait discovery in major cereals such as wheat, rice, and maize. This review synthesises current advances in the physiological, molecular, and genomic mechanisms underlying abiotic stress tolerance, with a particular emphasis on integrative frameworks that combine genomics, phenomics, and computational approaches. Importantly, emerging constraints associated with genome editing, including off-target effects, delivery challenges, and mosaicism, highlight the need for complementary strategies. The integration of pangenomics, high-throughput phenotyping, artificial intelligence-assisted selection, and speed breeding represents a transformative shift toward systems-level crop improvement. Overall, this review proposes that future progress in developing climate-resilient cereals will depend not on individual technologies alone, but on their coordinated deployment within holistic, data-driven breeding pipelines capable of addressing complex and dynamic stress environments.