From detection to protection: The role of optical sensors, robots, and artificial intelligence in modern plant disease management

Authors: MAHLEIN, ANNE-KATRIN - International Institute For Sugar Beet Research; ARNAL BARBEDO, JAYME - Embrapa; CHIANG, KUO-SZU - Chung Hsing University; DEL PONTE, EMERSON - Universidade Federal De Vicosa; Bock, Clive

Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/22/2024
Publication Date: 8/1/2024
Citation: Mahlein, A., Arnal Barbedo, J.G., Chiang, K., Del Ponte, E.M., Bock, C.H. From detection to protection: The role of optical sensors, robots, and artificial intelligence in modern plant disease management. Phytopathology. 114:1733-1741. 2024. https://doi.org/10.1094/PHYTO-01-24-0009-PER.
DOI: https://doi.org/10.1094/PHYTO-01-24-0009-PER

Interpretive Summary: There is a need for new and innovative methods for measuring and managing plant diseases to address forthcoming challenges and trends in agricultural production that demand greater precision. Progress has been achieved in the last 15 years for detecting and monitoring plant diseases based on innovative technology. Optical sensors, artificial intelligence, micro sensor networks, and autonomous driving platforms which are leading to new approaches in the context of precision agriculture. New cropping systems with locally targeted management becomes possible. The research is usually highly collaborative, an interdisciplinary effort that integrates plant pathologists, computer scientists, statisticians, engineers, and agronomists. Despite the progress, various challenges remain, including knowledge-transfer to agricultural practice and extension, accuracy, specificity and earliness of disease detection, and data-driven artificial intelligence systems need to be developed. The novel technologies need to be developed as part of integrated pest management (IPM) strategies. Current and future potentials and limits of the technologies must be understood and expressed. The needs emphasize that further research, knowledge transfer, and education in the use of digital technologies for disease management are required and is discussed.

Technical Abstract: Some years ago, the need for new and innovative methods for measuring and managing plant diseases was envisioned to address forthcoming challenges and trends in agricultural production that demand greater precision. Substantial progress in research has been achieved in the last 15 years for detecting and monitoring plant diseases, mainly boosted by innovative technology. These include the use of sophisticated optical sensors, artificial intelligence, micro sensor networks, and autonomous driving platforms which are leading to new approaches in the context of precision agriculture. Also, novel cropping systems with new cultivation patterns with targeted management becomes possible, in contrast to current, field wide applications to large, uniform crop areas. The research is usually highly collaborative, an interdisciplinary effort that integrates plant pathologists, computer scientists, statisticians, engineers, and agronomists. Despite the progress, various challenges remain. In particular, the knowledge-transfer to agricultural practice and extension. Accuracy, specificity and earliness of disease detection need to be improved further, and data driven artificial intelligence systems will likely play a key role. The novel technologies must not be considered and developed separately but as part of integrated pest management (IPM) strategies. Questions regarding control thresholds for localized, spot applications have yet to be explored. Harnessing and developing appropriate digital technologies to optimize pesticide application needs to be considered in registration routines. Current and future potentials and limits of the technologies must be understood and expressed. The needs emphasize that further research, knowledge transfer, and education in the use of digital technologies for disease management are required.