Journal of Tea Science Research, 2025, Vol.15, No.1, 12-20 http://hortherbpublisher.com/index.php/jtsr 18 Future breeding of tea would emphasize developing a modern, scientific breeding platform where traditional breeding is the basic strategy to be supplemented by molecular technology for precision improvement. This supplementary framework will not only preserve the merits of genetic stability and flexibility inherent in traditional breeding but will also address problems of dissecting complex traits, reducing breeding cycles, and climate resilience. Enhancing the synergy between conventional breeding skills and cutting-edge molecular tools is critical to sparking sustainable innovation and competitiveness in global tea industry. Acknowledgments The authors extend sincere gratitude to the research team members for their patient assistance and professional support during the data collection and literature organization for tea tree breeding studies. Their efforts laid a solid foundation for the successful completion of this paper. Additionally, the author thanks the two anonymous reviewers for their valuable feedback and suggestions, which effectively contributed to the optimization and refinement of the paper's content. 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 Chen S., Wang P., Kong W., Chai K., Zhang S., Yu J., Wang Y., Jiang M., Lei W., Chen X., Wang W., Gao Y., Qu S., Wang F., Wang Y., Zhang Q., Gu M., Fang K.C., Sun W., Ye N., Wu H., and Zhang X., 2023a, Gene mining and genomics-assisted breeding empowered by the pangenome of tea plant Camellia sinensis, Nature Plants, 9(12): 1986-1999. https://doi.org/10.1038/s41477-023-01565-z Chen Y., Niu S., Deng X., Song Q., He L., Bai D., and He Y., 2023b, Genome-wide association study of leaf-related traits in tea plant in Guizhou based on genotyping-by-sequencing, BMC Plant Biology, 23(1): 285. https://doi.org/10.1186/s12870-023-04192-0 Kong W., Kong X., Xia Z., Li X., Wang F., Shan R., Chen Z., You X., Zhao Y., Hu Y., Zheng S., Zhong S., Zhang S., Zhang Y., Fang K., Wang Y., Liu H., Zhang Y., Li X., Wu H., Chen G., Zhang X., and Chen C., 2025, Genomic analysis of 1,325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement, Nature Genetics, 57(8): 997-1007. https://doi.org/10.1038/s41588-025-02135-z Kumar R.K., Ahuja P., and Sharma R., 2016, Status and opportunities of molecular breeding approaches for genetic improvement of tea, in Advances in Plant Breeding Strategies: Nut and Beverage Crops, 101-125. https://doi.org/10.1007/978-3-319-27090-6_5 Li J.Q., 2024, From QTLs to field: mapping the genetic determinants of rice grain quality, Plant Gene and Trait, 15(2): 85-96. https://doi.org/10.5376/pgt.2024.15.0010 Li H., Song K., Zhang X., Wang D., Dong S., Liu Y., and Yang L., 2023a, Application of multi-perspectives in tea breeding and the main directions, International Journal of Molecular Sciences, 24(16): 12643. https://doi.org/10.3390/ijms241612643 Li J., Li H., Liu Z., Wang Y., Chen Y., Yang N., Hu Z., Li T., and Zhuang J., 2023b, Molecular markers in tea plant (Camellia sinensis): Applications to evolution, genetic identification, and molecular breeding, Plant Physiology and Biochemistry, 198: 107704. https://doi.org/10.1016/j.plaphy.2023.107704 Li L., Li X., Liu F., Zhao J., Zhang Y., Zheng W., and Fan L., 2023c, Preliminary investigation of essentially derived variety of tea tree and development of SNP markers, Plants, 12(8): 1643. https://doi.org/10.3390/plants12081643 Lubanga N., Massawe F., and Mayes S., 2021, Genomic and pedigree‐based predictive ability for quality traits in tea (Camellia sinensis (L.) O. Kuntze), Euphytica, 217(3): 32. https://doi.org/10.1007/s10681-021-02774-3 Lubanga N., Massawe F., Mayes S., Gorjanc G., and Bančič J., 2022, Genomic selection strategies to increase genetic gain in tea breeding programs, The Plant Genome, 16(1): e20282. https://doi.org/10.1002/tpg2.20282 Luo B., Sun H., Zhang L., Chen F., and Wu K., 2024, Advances in the tea plants phenotyping using hyperspectral imaging technology, Frontiers in Plant Science, 15: 1442225. https://doi.org/10.3389/fpls.2024.1442225 Malebe M., Koech R., Mbanjo E., Kamunya S., Myburg A., and Apostolides Z., 2021, Construction of a DArT-seq marker–based genetic linkage map and identification of QTLs for yield in tea (Camellia sinensis (L.) O. Kuntze), Tree Genetics and Genomes, 17(4): 32. https://doi.org/10.1007/s11295-021-01491-1
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