Climate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigation

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cg.authorship.typesCGIAR and advanced research institute
cg.contributor.affiliationUniversity of Florida
cg.contributor.affiliationUniversity of Exeter
cg.contributor.affiliationCornell University
cg.contributor.affiliationInternational Center for Tropical Agriculture
cg.identifier.doihttps://doi.org/10.1146/annurev-phyto-021021-042636
cg.isijournalISI Journal
cg.issn0066-4286
cg.issue1
cg.journalAnnual Review of Phytopathology
cg.reviewStatusPeer Review
cg.subject.alliancebiovciatCLIMATE CHANGE
cg.subject.alliancebiovciatINFORMATION SYSTEMS
cg.subject.impactAreaClimate adaptation and mitigation
cg.subject.sdgSDG 13 - Climate action
cg.subject.sdgSDG 15 - Life on land
cg.volume60
dc.contributor.authorGarrett, K.A.
dc.contributor.authorBebber, D.P.
dc.contributor.authorEtherton, B.A.
dc.contributor.authorGold, K.M.
dc.contributor.authorPlex Sulá, A.I.
dc.contributor.authorSelvaraj, Michael G.
dc.date.accessioned2022-06-08T13:25:50Zen
dc.date.available2022-06-08T13:25:50Zen
dc.identifier.urihttps://hdl.handle.net/10568/119779
dc.titleClimate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigationen
dcterms.abstractPlant pathology has developed a wide range of concepts and tools for improving plant disease management, including models for understanding and responding to new risks from climate change. Most of these tools can be improved using new advances in artificial intelligence (AI), such as machine learning to integrate massive data sets in predictive models. There is the potential to develop automated analyses of risk that alert decision-makers, from farm managers to national plant protection organizations, to the likely need for action and provide decision support for targeting responses. We review machine-learning applications in plant pathology and synthesize ideas for the next steps to make the most of these tools in digital agriculture. Global projects, such as the proposed global surveillance system for plant disease, will be strengthened by the integration of the wide range of new data, including data from tools like remote sensors, that are used to evaluate the risk ofplant disease. There is exciting potential for the use of AI to strengthen global capacity building as well, from image analysis for disease diagnostics and associated management recommendations on farmers’ phones to future training methodologies for plant pathologists that are customized in real-time for management needs in response to the current risks. International cooperation in integrating data and models will help develop the most effective responses to new challenges from climate change.en
dcterms.accessRightsLimited Access
dcterms.audienceScientists
dcterms.bibliographicCitationGarrett, K.A.; Bebber, D.P.; Etherton, B.A.; Gold, K.M.; Plex Sulá, A.I.; Selvaraj, M.G. (2022) Climate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigation. Annual Review of Phytopathology, Online first paper (01 June 2022). ISSN: 0066-4286en
dcterms.extentpp. 357-378
dcterms.issued2022-08-26
dcterms.languageen
dcterms.licenseCopyrighted; all rights reserved
dcterms.publisherAnnual Reviews
dcterms.subjectclimate change mitigationen
dcterms.subjectpathogensen
dcterms.subjectartificial intelligenceen
dcterms.subjectaccess to informationen
dcterms.subjectmitigación del cambio climáticoen
dcterms.subjectorganismos patógenosen
dcterms.subjectinteligencia artificialen
dcterms.typeJournal Article

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