کاربرد روش بینایی ماشین در تشخیص بیماری‌های توت‌فرنگی با YOLO 11

Aljawasim, B. D., Samtani, J. B., & Rahman, M. (2023). New insights in the detection and management of anthracnose diseases in strawberries. Plants, 12(21), 3704. https://doi.org/10.3390/plants12213704

Bai, Y., Yu, J., Yang, S., & Ning, J. (2024). An improved YOLO algorithm for detecting flowers and fruits on strawberry seedlings. Biosystems Engineering, 237, 1–12. https://doi.org/10.1016/j.biosystemseng.2023.11.008

Carisse, O., & Fall, M. L. (2021). Decision Trees to Forecast Risks of Strawberry Powdery Mildew Caused by Podosphaera aphanis. Agriculture, 11(1). https://doi.org/10.3390/agriculture11010029

Chen, M., Zou, W., Niu, X., Fan, P., Liu, H., Li, C., & Zhai, C. (2025). Improved YOLOv8-Based Segmentation Method for Strawberry Leaf and Powdery Mildew Lesions in Natural Backgrounds. Agronomy, 15(3), 525. https://doi.org/10.3390/agronomy15030525

Dholi, P. K., Khatiwada, P., Basnet, B., & Bhandari, S. (2023). An Extensive Review of Strawberry (Fragaria× ananassa) Diseases and Integrated Management Approaches: Current Understanding and Future Directions. Fundamental and Applied Agriculture, 8(4), 655–667. https://doi.org/10.5455/faa.136385

Hernández-Martínez, N. R., Blanchard, C., Wells, D., & Salazar-Gutiérrez, M. R. (2023). Current state and future perspectives of commercial strawberry production: A review. Scientia Horticulturae, 312, 111893. https://doi.org/10.1016/j.scienta.2023.111893

Maghsoodi, F., Taheri, P., & Tarighi, S. (2025). Isolation, characterization and control of Botrytis spp. pathogenic on strawberry in Iran. Heliyon, 11(2). https://doi.org/10.1016/j.heliyon.2025.e42037

Meyers, K. J., Watkins, C. B., Pritts, M. P., & Liu, R. H. (2003). Antioxidant and antiproliferative activities of strawberries. Journal of Agricultural and Food Chemistry, 51(23), 6887–6892. https://doi.org/10.1021/jf034506n

Osdaghi, E. (2024). Xanthomonas fragariae (angular leaf spot of strawberry). https://doi.org/10.1079/cabicompendium.56934

Samtani, J. B., Rom, C. R., Friedrich, H., Fennimore, S. A., Finn, C. E., Petran, A., Wallace, R. W., Pritts, M. P., Fernandez, G., & Chase, C. A. (2019). The status and future of the strawberry industry in the United States. HortTechnology, 29(1), 11–24. https://doi.org/10.21273/HORTTECH04135-18

Shin, J., Chang, Y. K., Heung, B., Nguyen-Quang, T., Price, G. W., & Al-Mallahi, A. (2021). A deep learning approach for RGB image-based powdery mildew disease detection on strawberry leaves. Computers and Electronics in Agriculture, 183, 106042. https://doi.org/10.1016/j.compag.2021.106042

Shoaib, M., Shah, B., Ei-Sappagh, S., Ali, A., Ullah, A., Alenezi, F., Gechev, T., Hussain, T., & Ali, F. (2023). An advanced deep learning models-based plant disease detection: A review of recent research. Frontiers in Plant Science, 14, 1158933. https://doi.org/10.3389/fpls.2023.1158933

Van Tran, T., Do Ba, Q.-H., Tran, K. T., Nguyen, D. H., Dang, D. C., & Dinh, V.-L. (2024). Designing a Mobile Application for Identifying Strawberry Diseases with YOLOv8 Model Integration. International Journal of Advanced Computer Science & Applications, 15(3). https://doi.org/10.14569/ijacsa.2024.0150351

Wai, T. T., Aye, M., & Hla, T. T. (2025). Comparative Evaluation of Inception V3 and YOLOv8 for Strawberry Plant Diseases Classification Using Deep Learning Models. The Indonesian Journal of Computer Science, 14(1). https://doi.org/10.33022/ijcs.v14i1.4750

Wu, E., Ma, R., Dong, D., & Zhao, X. (2025). D-YOLO: A Lightweight Model for Strawberry Health Detection. Agriculture, 15(6). https://doi.org/10.3390/agriculture15060570