Bioscience Methods 2025, Vol.16, No.1, 23-32 http://bioscipublisher.com/index.php/bm 29 7.2 Potential of AI and machine learning in molecular breeding Artificial intelligence (AI) and machine learning (ML) hold significant potential in revolutionizing molecular breeding. These technologies can analyze large datasets generated from genomic studies to predict the performance of breeding lines and identify optimal breeding strategies. For instance, high-throughput sequencing data combined with AI algorithms can enhance the prediction accuracy of genomic selection models, thereby accelerating the breeding process (Caruana et al., 2019). The application of AI and ML can also optimize the identification of SNP markers and their association with complex traits, leading to more efficient breeding programs (Haque et al., 2023). 7.3 Policy recommendations to support molecular breeding research To support the advancement of molecular breeding in sweet potatoes, several policy recommendations are necessary. Governments and funding agencies should prioritize investments in genomic research and the development of advanced breeding technologies. Policies should also encourage public-private partnerships to facilitate the transfer of technology and knowledge from research institutions to breeding programs. Additionally, regulatory frameworks need to be updated to accommodate the use of genome editing tools such as CRISPR-Cas9, ensuring that new cultivars can be developed and commercialized efficiently (Ahmad et al., 2022). Support for training programs in molecular breeding techniques will also be crucial to build the necessary human resource capacity. 7.4 Vision for the next generation of high-yield sweet potato cultivars The next generation of high-yield sweet potato cultivars will be characterized by enhanced nutritional content, disease resistance, and adaptability to diverse environmental conditions. By leveraging advanced molecular techniques such as genome editing, marker-assisted selection, and functional genomics, breeders can develop cultivars with optimized traits for both yield and quality (Peng, 2011; Vargas et al., 2020). The integration of AI and ML in breeding programs will further streamline the selection process, enabling the rapid development of superior cultivars. Ultimately, these advancements will contribute to global food security by providing resilient and high-yielding sweet potato varieties that can meet the demands of a growing population (Ngailo et al., 2019; Otoboni et al., 2020). 8 Concluding Remarks Recent advancements in molecular breeding have significantly contributed to the development of high-yield sweet potato cultivars. Key findings from various studies highlight the importance of integrating traditional and modern breeding techniques to enhance drought tolerance, yield, and nutritional quality. For instance, the use of molecular markers and genetic mapping has been instrumental in identifying traits associated with drought resistance and high yield. Additionally, genome editing tools such as CRISPR-Cas9 have opened new avenues for rapid and precise genetic improvements. Studies have also emphasized the need for breeding programs to be demand-driven, addressing specific market needs and socio-economic factors such as poverty, malnutrition, and gender inequality. Molecular breeding holds immense promise for enhancing global food security, particularly in the context of climate change and increasing food demand. By employing advanced genetic tools, researchers can develop sweet potato varieties that are not only high-yielding but also resilient to environmental stresses such as drought. This is crucial for smallholder farmers in developing countries who rely on sweet potato as a staple crop. Moreover, the ability to rapidly develop new cultivars through techniques like speed breeding and genome editing can significantly shorten the breeding cycle, making it possible to meet the urgent food needs of a growing global population. The integration of molecular breeding with traditional methods also ensures that the new varieties are well-adapted to local conditions and farmer preferences. Future research in sweet potato breeding should focus on several key areas to maximize the benefits of molecular breeding. First, there is a need for more comprehensive studies on the genetic basis of complex traits such as starch content and drought tolerance, which can be facilitated by polyploid genome-wide association studies (GWAS). Second, breeding programs should continue to prioritize the development of varieties that address specific socio-economic challenges, including poverty alleviation and nutritional deficiencies. Third, the adoption
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