UAV multispectral imagery for assessing tree health in tart cherry orchards with a focus on powdery mildew detection
DOI:
https://doi.org/10.71318/70k4mt72Keywords:
tart cherry, powdery mildew, UAV multispectral imagingAbstract
Unmanned aerial vehicle (UAV)-based multispectral imagery could provide a more efficient approach to pest scouting in tart cherry, a relatively low-input orchard crop. We evaluated whether vegetation indices derived from UAV-mounted multispectral imagery could detect powdery mildew (PM) in three commercial tart cherry orchard blocks in Utah during 2022 and 2023. Powdery mildew severity was surveyed repeatedly and compared with vegetation indices calculated from multispectral imagery collected during the same period. The optimized chlorophyll vegetation index (OCVI) showed the strongest overall relationship with PM severity, but correlations were only moderate when data were pooled across orchards and dates. Within individual orchards and sampling dates, vegetation indices were not consistently related to PM severity. Relationships were especially weak when analyses were restricted to observations below an estimated economic threshold of 20% severity, where early detection would be most useful for management decisions. Although UAV multispectral imagery was not reliable for early PM detection, it was useful for identifying broader spatial variability in tree health. Tree health, assessed using red-edge normalized difference vegetation index as an indicator of canopy chlorosis and vigor, varied substantially among orchards and was associated with canopy density and apparent soil electrical conductivity (ECa). In the most variable orchard, poorer tree health and greater chlorosis were concentrated in areas of lower canopy density and higher ECa, corresponding to finer-textured soils. These findings indicate that UAV multispectral imagery was not reliable for early detection of PM in tart cherry under commercial orchard conditions but was useful for characterizing orchard-scale variability in tree health related to canopy structure and soil properties.
References
Abood JK, Lösel DM. 2003. Changes in carbohydrate composition of cucumber leaves during the development of PM infection. Plant Pathol. 52:256-265. https://doi.org/10.1046/j.1365-3059.2003.00814.x.
Bardenhagen C, Rothwell N, Colella F, Nugent J. 2022. Michigan tart cherry cost of production study 2022. Mich Agric Ext Bull. E3474.
Calabro JM, Spotts RA, Grove GG. 2009. Effect of training system, rootstock, and cultivar on sweet cherry PM foliar infections. HortScience. 44:481-482. https://doi.org/10.21273/HORTSCI.44.2.481.
Calderón R, Montes-Borrego M, Landa BB, Navas-Cortés JA, Zarco-Tejada PJ. 2014. Detection of downy mildew of opium poppy using high-resolution multispectral and thermal imagery acquired with an unmanned aerial vehicle. Precision Agric. 15:639-661. https://doi.org/10.1007/s11119-014-9360-y.
Chandel AK, Khot LR, Sallato B. 2020. Towards rapid detection and mapping of PM in apple orchards, p 288-292. In: 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). https://doi.org/10.1109/MetroAgriFor50201.2020.9277544.
Chandel AK, Khot LR, Sallato B. 2021. Apple PM infestation detection and mapping using high-resolution visible and multispectral aerial imaging technique. Sci Hortic. 287:110228. https://doi.org/10.1016/j.scienta.2021.110228.
DadrasJavan F, Samadzadegan F, Pourazar SHS, Fazeli H. 2019. UAV-based multispectral imagery for fast citrus greening detection. J Plant Dis Prot. 126:307-318. https://doi.org/10.1007/s41348-019-00234-8.
Ellis M, Ferree D, Spring D. 1981. Photosynthesis, transpiration, and carbohydrate content of apple leaves infected by Podosphaera leucotricha. Phytopathol. 71:392-395.
Grove GG, Boal RJ. 1991a. Overwinter survival of Podosphaera clandestina in eastern Washington. Phytopathol. 81:385-391.
Grove GG, Boal RJ. 1991b. PM of sweet cherry: influence of temperature and wetness duration on release and germination of ascospores of Podosphaera clandestina. Phytopathol. 81:1271-1275.
Grove GG, Boal RJ. 1991c. Factors affecting germination of conidia of Podosphaera clandestina on leaves and fruit of sweet cherry. Phytopathol. 81:1513-1518.
Grove GG, Boal RJ, Bennett LH. 2000. Managing PM of cherry in Washington orchards and nurseries with spray oils. Plant Health Prog. 1:2. https://doi.org/10.1094/PHP-2000-0728-01-RS.
Kumar A, Lee WS, Ehsani R, Albrigo G, Yang C, Mangan RL. 2012. Citrus greening disease detection using aerial hyperspectral and multispectral imaging techniques. J Appl Remote Sens. 6:063542. https://doi.org/10.1117/1.JRS.6.063542.
Lan Y, Huang Z, Deng X, Zhu Z, Huang H, Zheng Z, Tong Z. 2020. Comparison of machine learning methods for citrus greening detection on UAV multispectral images. Comput Electron Agric. 171:105234. https://doi.org/10.1016/j.compag.2020.105234.
Lilligren C, Murray M, Black B, Torres-Rua A, Wedegaertner K, Safre A, Papenfuss K. 2023. Precision agriculture techniques for evaluating tart cherry tree health. In: II International Symposium on Precision Management of Orchards and Vineyards. Acta Hortic. 1395:197-200. https://doi.org/10.17660/ActaHortic.2024.1395.26.
Luedeling E, Hale A, Zhang M, Bentley WJ, Dharmasri CL. 2009. Remote sensing of spider mite damage in California peach orchards. Int J Appl Earth Obs Geoinf. 11:244-255. https://doi.org/10.1016/j.jag.2009.03.002
Main R, Cho MA, Mathieu R, O’Kennedy MM, Ramoelo A, Koch S. 2011. An investigation into robust spectral indices for leaf chlorophyll estimation. ISPRS J Photogrammetry Remote Sens. 66:751-761. https://doi.org/10.1016/j.isprsjprs.2011.08.001
Murray M, Lilligren C, Kast M. 2025. Cherry powdery mildew in Utah. Utah State University Extension Plant Health. https://extension.usu.edu/planthealth/research/cherry-powdery-mildew-in-utah.
Ontario Ministry of Agriculture, Food and Agribusiness. 2026. Powdery mildew: Tart cherries. Ontario Crop Protection Hub. https://cropipm.omafra.gov.on.ca/en-ca/crops/tart-cherries/diseases/4d8c8b67-eb4a-4112-8b13-87e65d129fb8#identification. [accessed 25 Sept. 2026].
Percival GC, Fraser GA. 2002. The influence of PM infection on photosynthesis, chlorophyll fluorescence, leaf chlorophyll and carotenoid content of three woody plant species. Arboric J. 26:333-346. https://doi.org/10.1080/03071375.2002.9747348.
Schmidt-Jeffris RA, Beers EH, Duso C. 2019. Integrated management of mite pests of tree fruit, p. 425-452. In: Xu X, Fountain M (eds).Integrated management of diseases and insect pests of tree fruit. Burleigh Dodds Science Publishing, London, UK.
Schoofs H, Delalieux S, Deckers T, Bylemans D. 2020. Fire blight monitoring in pear orchards by unmanned airborne vehicles (UAV) systems carrying spectral sensors. Agron. 10:615. https://doi.org/10.3390/agronomy10050615.
Stern RE, Zentmyer GA, Kaufmann MR. 1977. The influence of matric potential, soil texture, and soil amendment on root disease caused by Phytophthora cinnamomi. Phytopathol. 67: 1495-1500.
Su J, Liu C, Coombes M, Hu X, Wang C, Xu X, Li Q, Guo L, Chen W-H. 2018. Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery. Comput Electron Agric. 155:157-166.
United States Department of Agriculture, National Agricultural Statistics Service. 2023. Noncitrus fruits and nuts 2022 summary. USDA.
87 p.
United States Department of Agriculture, National Agricultural Statistics Service. 2024. Census of Agriculture. USDA.
Utah State University. 2024. PM. USU. https://extension.usu.edu/planthealth/ipm/notes_orn/list-flowers/powdery-mildew. [accessed 9 Oct. 2024].
Wedegaertner K, Black B, Safre A, Torres-Rua A, Cardon G, Yost M. 2026. Integrating soil and canopy sensing to map and relate variability in tart cherry orchards. Precision Agric. 27:136. https://doi.org/10.1007/s11119-026-10436-4.
Xiao D, Pan Y, Feng J, Yin J, Liu Y, He L. 2022. Remote sensing detection algorithm for apple fire blight based on UAV multispectral image. Comput Electron Agric. 199:107137.
Yoder, K. S., and Hickey, K. D. 1995. Apple powdery mildew. in: Mid-Atlantic Orchard Monitoring Guide. H. W. Hogmire, eds. Northeast Regional Agricultural Engineering Department, Ithaca, NY.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Brent Black, Christina Lilligren, Marion Murray, Kurt Wedegaertner, Anderson Safre, Alfonso Torres-Rua (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The American Pomological Society and Editors cannot be held responsible for the views and opinions expressed by individual authors of articles published herein. This also applies to any supplemental materials residing on this website that are linked to these articles. The publication of advertisements does not constitute any endorsement of products by the American Pomological Society or Editors.