Triticeae Genomics and Genetics, 2024, Vol.15, No.5, 277-286 http://cropscipublisher.com/index.php/tgg 284 Genome editing offers the ability to make targeted modifications to genes responsible for stress tolerance, yield, and quality traits without introducing foreign DNA, which could help address public and regulatory concerns over genetically modified organisms (GMOs) (Nerkar et al., 2022). Furthermore, advances in phenotyping technologies, including remote sensing and UAV-based data collection, combined with genomic information, are expected to accelerate breeding cycles and improve the accuracy of trait selection (Bentley et al., 2022). These tools will enhance breeders' capacity to develop high-yielding, stress-resilient triticale varieties that meet the demands of future agricultural systems. 10 Concluding Remarks The current state of genetic research and methodologies in triticale breeding highlights remarkable advancements in both traditional and modern approaches to enhance the crop’s adaptability to stress-prone environments. Significant progress has been made in the identification of key genetic loci associated with abiotic and biotic stress tolerance, aided by advanced tools such as genome-wide association studies (GWAS), marker-assisted selection (MAS), and genomic selection (GS). Additionally, the incorporation of biotechnological tools like CRISPR/Cas9 has accelerated the ability to precisely edit genes related to stress adaptation, enabling faster and more targeted breeding strategies. However, challenges such as genetic bottlenecks and balancing trade-offs between yield, quality, and stress tolerance remain areas where further research is needed. Triticale’s role in ensuring food security, especially in stress-prone environments, is increasingly significant as the effects of climate change continue to intensify. Its unique genomic composition, which combines the stress tolerance of rye and the high yield potential of wheat, positions it as a crucial crop for marginal lands and regions susceptible to drought, salinity, and extreme temperatures. This hybrid crop offers a sustainable solution for improving food production while reducing reliance on high-input agricultural practices. To address future challenges, continuous research and innovation are imperative. New breeding technologies, including genome editing, high-throughput phenotyping, and multi-omics integration, offer promising pathways to develop triticale varieties that can thrive in increasingly hostile environments. Moreover, the integration of data-driven approaches, such as machine learning and big data analytics, with field-based phenotyping will enhance precision breeding, ensuring the development of resilient, high-yielding varieties that meet global food demands. As agricultural pressures continue to rise, investing in these cutting-edge technologies and interdisciplinary research will be critical for the future of triticale breeding and its contribution to global food security. Acknowledgments Thank you to the two anonymous reviewers for their suggested revisions. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Abdelrahman M., Al-Sadi A., Pour-Aboughadareh, A., Burritt D., and Tran L., 2018, Genome editing using CRISPR/Cas9-targeted mutagenesis: an opportunity for yield improvements of crop plants grown under environmental stresses, Plant Physiology and Biochemistry, 131: 31-36. https://doi.org/10.1016/j.plaphy.2018.03.012 Bakala H.S., Mandahal K.S., Ankita Sarao L., and Srivastava P., 2021, Breeding wheat for biotic stress resistance: achievements, challenges and prospects, IntechOpen, 12: 11-34. https://doi.org/10.5772/intechopen.97359. Bentley A., Chen C.B., and D’ Agostino N., 2022, Genome-wide association studies and genomic selection for crop improvement in the era of big data, Frontiers in Genetics, 13: 873060. https://doi.org/10.3389/fgene.2022.873060 Bhandari A., Bartholomé J., Cao T., Kumari N., Frouin J., Kumar A., and Ahmadi N., 2018, Selection of trait-specific markers and multi-environment models improve genomic predictive ability in rice, PLoS ONE, 14(5): e0208871. https://doi.org/10.1371/journal.pone.0208871
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