Satellite-based crop identification and risk profiling for area wide management of Whitefly and tomato yellow leaf curl virus in Southwest Florida

Authors: LI, KEJI - University Of Florida; TURECHEK, WILLIAM - California Strawberry Commission; Adkins, Scott; LUO, WEIQI - North Carolina State University; MELLINGER, CHARLES - Glades Crop Care; SMITH, HUGH - University Of Florida; Kousik, Chandrasekar; ROBERTS, PAMELA - University Of Florida; PARKS, FELICIA - Glades Crop Care; LUCAS, LEON - Glades Crop Care; JOHNSON, DAVID - Glades Crop Care; MONTEMAYOR, JOSEPH - Glades Crop Care; TORO, ANA - Regrow Agriculture; SHRIVER, JOHN - Regrow Agriculture; FREY, CRAIG - University Of Florida; Bock, Clive

Submitted to: Plant Disease
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/31/2025
Publication Date: 4/2/2025
Citation: Li, K., Turechek, W.W., Adkins, S.T., Luo, W., Mellinger, C.H., Smith, H., Kousik, C.S., Roberts, P.D., Parks, F., Lucas, L., Johnson, D., Montemayor, J., Toro, A., Shriver, J., Frey, C.J., Bock, C.H. Satellite-based crop identification and risk profiling for area wide management of Whitefly and tomato yellow leaf curl virus in Southwest Florida. 2025. Plant Disease. https://doi.org/10.1094/PDIS-12-24-2634-RE.
DOI: https://doi.org/10.1094/PDIS-12-24-2634-RE

Interpretive Summary: Whitefly-transmitted viruses are a major cause of yield loss in the Southeast U.S.A. Satellite-based crop identification combined with crop disease risk profiling may provide a basis to managing whitefly and whitefly-transmitted viruses in these vegetable production systems. Using satellite imagery and artificial intelligence tools to accurately identify and monitor crop types throughout the growing season, crop distribution and type was mapped. The data was correlated with scouted whitefly populations and tomato yellow leaf curl virus (TYLCV) incidence. Both whitefly populations and TYLCV incidence were autocorrelated up to 1750 meters and the autocorrelation extended to 5000 m from January to April. This spatial autocorrelation indicates the scale for timely and focused area wide management of whitefly. Temporal analysis revealed that both whitefly populations and TYLCV incidence were influenced by temperature. The presence of surrounding vegetable fields influenced whitefly dispersal up to 9000 m during peak months. The results emphasize the need for targeted monitoring and area wide management strategies for whitefly, which will also control TYLCV.

Technical Abstract: Integrating satellite crop identification with disease risk profiling provides a robust framework for managing whitefly and virus impacts on vegetable production in Southwest Florida. Our study utilized Sentinel-2 satellite imagery and machine learning techniques to accurately identify and monitor crop types throughout the growing season. The data allowed us to correlate whitefly populations and tomato yellow leaf curl virus (TYLCV) incidence with specific crop distributions. Key findings reveal significant spatial autocorrelation up to 1750 meters for both whitefly populations and TYLCV incidence throughout the entire season. However, during specific months from January to April, the spatial autocorrelation extends up to 5000 m, highlighting the importance of timely focused area wide management practices. Temporal analysis revealed that both whitefly populations and TYLCV incidence are strongly influenced by temperature, particularly during the February to May period. Positive correlations for whitefly populations were detected at multiple lag times and window sizes, with the most significant correlations (p<0.001) observed between 30 to 85 days lag and window sizes from 20 to 50 days. Conversely, rainfall showed weaker correlations, suggesting that temperature is a more critical factor. Additionally, the presence of surrounding vegetable fields significantly influenced whitefly dispersal, with correlations extending up to 9000 m during peak months. These insights underscore the need for targeted monitoring and management strategies, focusing on temperature fluctuations and spatial crop distributions, to effectively control whitefly and TYLCV outbreaks.