Bioscience Method 2024, Vol.15, No.2, 58-65 http://bioscipublisher.com/index.php/bm 65 Meena M., Appunu C., Kumar R., Manimekalai R., Vasantha S., Krishnappa G., Kumar R., Pandey S., and Hemaprabha G., 2022, Recent advances in sugarcane genomics, physiology, and phenomics for superior agronomic traits, Frontiers in Genetics, 13: 854936. https://doi.org/10.3389/fgene.2022.854936 PMid:35991570 PMCid:PMC9382102 Murugeswari R., Anwar Z., Dhananjeyan V., and Karthik C., 2022, Automated sugarcane disease detection using faster RCNN with an android application, 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), IEEE, pp.1-7. https://doi.org/10.1109/ICOEI53556.2022.9776685 Narmilan A., Gonzalez F., Salgadoe A., Sandino J., and Powell K., 2022, Detection of white leaf disease in sugarcane using machine learning techniques over UAV multispectral images, Drones, 6(9): 230. https://doi.org/10.3390/drones6090230 Racedo J., Noguera A., Castagnaro A., and Perera M., 2023, Biotechnological strategies adopted for sugarcane disease management in Tucumán, Argentina, Plants, 12(23): 3994. https://doi.org/10.3390/plants12233994 PMid:38068629 PMCid:PMC10707952 Srivastava S., Kumar P., Mohd N., Singh A., and Gill F., 2020, A novel deep learning framework approach for sugarcane disease detection, SN Computer Science, 1: 1-7. https://doi.org/10.1007/s42979-020-0094-9 Thangadurai N., Vinay Kumar S.B, Gayathri K.M., and Dhanashekaran R., 2020, Detection of disease in sugarcane leaf using IoT, International Journal of Scientific & Technology Research, 9: 1790-1795. Wang Y.M., Ostendorf B., Gautam D., Habili N., and Pagay V., 2022, Plant viral disease detection: from molecular diagnosis to optical sensing technology-a multidisciplinary review, Remote Sensing, 14(7): 1542. https://doi.org/10.3390/rs14071542
RkJQdWJsaXNoZXIy MjQ4ODY0NQ==