**5. Conclusions**

This study used VIs derived from UAV-based multispectral imagery and BLR to develop an identification method for detecting banana Fusarium wilt. The results showed that Fusarium wilt of banana can be identified with this method. The fitting OA of the CIgreen, CIRE, NDVI, and NDRE were all higher than 80%. Among the investigated VIs, the CIRE exhibited the best performance both for the verification dataset 1 (OA = 91.7%, Kappa = 0.83) and verification dataset 2 (OA = 80.0%, Kappa = 0.59). For the same type of VI, the VIs including a red-edge band obtained a better performance than those excluding a red-edge band. The simulation of imagery with different spatial resolutions (i.e., 0.5-m, 1-m, 2-m, 5-m, and 10-m resolutions) showed that good identification accuracy of Fusarium wilt was obtained when the resolution was higher than 2 m. As the resolution decreased, the identification accuracy of Fusarium wilt showed a decreasing trend. The results of this study indicate that UAV-based remote sensing imagery with a red-edge band is well-suited for the identification of banana Fusarium wilt disease, providing guidance for disease treatment and crop planting adjustment.

**Author Contributions:** H.Y. performed the data analysis and wrote the manuscript. W.H. guided the study and discussed the methods and results. S.H., B.C. and Y.D. provided suggestions for the study, reviewed and edited the manuscript. H.Y., A.G., Y.R. and Y.J. conducted the field experiments. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Hainan Provincial Key R&D Program of China (ZDYF2018073), Hainan Provincial Major Science and Technology Program of China (ZDKJ2019006), National Natural Science Foundation of China (41571354), Agricultural Science and Technology Innovation Program of Sanya, China (2019NK17), National Special Support Program for High-level Personnel Recruitment (Ten-thousand Talents Program) (Wenjiang Huang).

**Acknowledgments:** We gratefully acknowledge the National Meteorological Information Center of China, Guangxi Jiejiarun Technology Co., Ltd. and Guangxi Jinsui Agriculture Group Co., Ltd. for the experiments.

**Conflicts of Interest:** The authors declare no conflict of interest.
