Field Crop 2025, Vol.8, No.2, 61-71 http://cropscipublisher.com/index.php/fc 69 Furthermore, environmental changes can alter the effectiveness of existing wheat varieties, necessitating continuous adaptation and breeding efforts. For example, changes in temperature and precipitation patterns can affect the growth cycle of wheat, requiring breeders to focus on traits such as drought resistance and heat tolerance (Asseng et al., 2020). These environmental pressures necessitate a shift in breeding priorities, often requiring a balance between traditional yield-focused goals and the need for resilience to changing climatic conditions (Dalrymple, 1985; Ying et al., 2019). 9 Future and prospects The integration of artificial intelligence (AI) and big data into wheat breeding holds significant promise for enhancing the efficiency and effectiveness of developing new wheat varieties. Advanced technologies such as genome editing, high-throughput genotyping, and phenotyping are already being utilized to improve wheat's genetic traits, which can be further optimized through AI-driven data analysis. AI can facilitate the identification of beneficial genetic traits and predict the performance of new cultivars under various environmental conditions, thereby accelerating the breeding process and improving yield potential. The use of AI in conjunction with big data analytics can also help in managing the vast amounts of genetic and phenotypic data generated, enabling more precise and targeted breeding strategies. Global collaboration is essential to advance the development of wheat varieties suitable for mechanized farming. Collaborative efforts can lead to the sharing of genetic resources, breeding technologies, and best practices across different regions, enhancing the overall capacity to develop high-yielding and resilient wheat varieties. International projects like BREEDWHEAT have demonstrated the benefits of pooling resources and expertise to tackle global challenges such as climate change and food security. By fostering partnerships between public and private sectors, as well as among countries, the global wheat community can accelerate the development of varieties that are not only high-yielding but also adaptable to mechanized farming systems. The future of wheat breeding must balance the need for increased productivity with ecological preservation. Sustainable intensification, which involves improving crop resistance to diseases and pests, adapting to climate change, and reducing inputs like water and fertilizers, is crucial for meeting future food demands without compromising environmental health. Breeding programs are increasingly focusing on developing varieties that require fewer agrochemical inputs while maintaining high yields, thus reducing the environmental footprint of wheat production. Innovations in breeding, such as the use of hybrid wheat and genome editing, offer opportunities to enhance both productivity and sustainability by creating varieties that are more resilient to environmental stresses and more efficient in resource use. Acknowledgments We would like to thank Mrs. Xu continuous support throughout the development of this study. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Abdelmageed K., Chang X., Wang D., Wang Y., Yang Y., Zhao G., and Tao Z., 2019, Evolution of varieties and development of production technology in Egypt wheat: a review, Journal of Integrative Agriculture, 18(3): 483-495. https://doi.org/10.1016/S2095-3119(18)62053-2 Ahmad J., Zulkiffal M., Anwar J., Ahsan A., Tanveer M., Ajmal S., Sarwar M., Shair H., Javaid M., Makhdoom M., Saleem M., Nadeem M., and Shahzad R., 2023, 'MH-21,' a novel high-yielding and rusts resistant bread wheat variety for irrigated areas of Punjab, Pakistan, SABRAO Journal of Breeding and Genetics, 55(3): 749-759. https://doi.org/10.54910/sabrao2023.55.3.13 Alotaibi F., Alharbi S., Alotaibi M., Mosallam M., Motawei M., and Alrajhi A., 2020, Wheat omics: classical breeding to new breeding technologies, Saudi Journal of Biological Sciences, 28(2): 1433-1444. https://doi.org/10.1016/j.sjbs.2020.11.083 Asseng S., Guarin J., Raman M., Monje O., Kiss G., Despommier D., Meggers F., and Gauthier P., 2020, Wheat yield potential in controlled-environment vertical farms, Proceedings of the National Academy of Sciences, 117(32): 19131-19135. https://doi.org/10.1073/pnas.2002655117
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