{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/139858"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/139858","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Advancing Sustainable Grape Downy Mildew Management: Biopesticide Trials and Risk Assessment System","abstract":"Grape downy mildew, caused by Plasmopara viticola, significantly damages grape crops (Vitis spp.), reducing yields by up to 75% in unprotected vineyards. The Eastern US faces limited fungicide options due to resistance development and potential legal restrictions on EBDC and captan. The first study evaluated various biopesticides and conventional fungicides in field and greenhouse trials from 2024 to 2025 across multiple Vitis vinifera cultivars in Virginia. Among biopesticides, the GEA 249 complex, Bacillus mycoides Isolate J, and Pseudomonas chlororaphis strain AFS009 showed results comparable to conventional fungicides such as copper octanoate, achieving up to 74% disease control. The second study focused on developing a downy mildew forecasting system using a model-based weather data approach that does not rely on physical weather stations. We also collected infection data from the field between 2022 and 2025 to evaluate two types of models we developed. The mechanistic model, which combined two published empirical models, outperformed the empirical models based on field trial data, achieving 60.3% accuracy in predicting downy mildew incidence, demonstrating its potential to reduce fungicide overapplication as part of integrated pest management.","abstract_html":"Grape downy mildew, caused by Plasmopara viticola, significantly damages grape crops (Vitis spp.), reducing yields by up to 75% in unprotected vineyards. The Eastern US faces limited fungicide options due to resistance development and potential legal restrictions on EBDC and captan. The first study evaluated various biopesticides and conventional fungicides in field and greenhouse trials from 2024 to 2025 across multiple Vitis vinifera cultivars in Virginia. Among biopesticides, the GEA 249 complex, Bacillus mycoides Isolate J, and Pseudomonas chlororaphis strain AFS009 showed results comparable to conventional fungicides such as copper octanoate, achieving up to 74% disease control. The second study focused on developing a downy mildew forecasting system using a model-based weather data approach that does not rely on physical weather stations. We also collected infection data from the field between 2022 and 2025 to evaluate two types of models we developed. The mechanistic model, which combined two published empirical models, outperformed the empirical models based on field trial data, achieving 60.3% accuracy in predicting downy mildew incidence, demonstrating its potential to reduce fungicide overapplication as part of integrated pest management.","abstract_has_math":false,"creators":["Ames, Jonathan Eugene"],"institution":"Virginia Tech","degree_name":"Master of Science in Life Sciences","degree_level":"masters","degree_discipline":"Plant Pathology, Physiology and Weed Science","degree_department":"Plant Pathology, Physiology and Weed Science","school":null,"contributors":[],"advisors":[],"committee_chairs":["Nita, Mizuho"],"committee_members":["Baudoin, Antonius B.","McCall, David Scott"],"year":2025,"date_issued":"2025-12-09","date_published":"2025-12-09","updated_at":"2026-07-22T22:20:07Z","subjects":["Biopesticides","Sustainability","Modeling","Viticulture"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45058"],"render_values":[{"text":"vt_gsexam:45058","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/139858","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Nita, Mizuho"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Baudoin, Antonius B.","McCall, David Scott"]},{"key":"dc:contributor.department","label":"Department","values":["Plant Pathology, Physiology and Weed Science"]},{"key":"dc:creator","label":"Author","values":["Ames, Jonathan Eugene"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-12-10T09:00:43Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-12-10T09:00:43Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-12-09"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Plant Pathology, Physiology and Weed Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Life Sciences"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biopesticides","Sustainability","Modeling","Viticulture"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:45058"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/139858"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Grape downy mildew, caused by Plasmopara viticola, significantly damages grape crops (Vitis spp.), reducing yields by up to 75% in unprotected vineyards. The Eastern US faces limited fungicide options due to resistance development and potential legal restrictions on EBDC and captan. The first study evaluated various biopesticides and conventional fungicides in field and greenhouse trials from 2024 to 2025 across multiple Vitis vinifera cultivars in Virginia. Among biopesticides, the GEA 249 complex, Bacillus mycoides Isolate J, and Pseudomonas chlororaphis strain AFS009 showed results comparable to conventional fungicides such as copper octanoate, achieving up to 74% disease control. The second study focused on developing a downy mildew forecasting system using a model-based weather data approach that does not rely on physical weather stations. We also collected infection data from the field between 2022 and 2025 to evaluate two types of models we developed. The mechanistic model, which combined two published empirical models, outperformed the empirical models based on field trial data, achieving 60.3% accuracy in predicting downy mildew incidence, demonstrating its potential to reduce fungicide overapplication as part of integrated pest management."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Grape downy mildew poses a serious threat to grape crops, potentially causing harvest losses of up to 75% when vines are unprotected. Traditionally, grape growers depend on chemical fungicides, but their repeated use can lead to resistance and may be restricted due to safety or environmental concerns. In Virginia during 2024 and 2025, we tested much safer biopesticides both in vineyards and greenhouses. While conventional fungicides remained the most effective, some biopesticides, such as the GEA 249 complex (product name: Kendal), Bacillus mycoides Isolate J (Lifegard), and Pseudomonas chlororaphis strain AFS009 (Hower EVO), performed nearly as well. Additionally, we developed a weather-based grape disease forecasting system to predict downy mildew outbreaks using weather data that does not require your own weather stations. When validated against downy mildew data collected from the field from 2022 to 2025, the system successfully identified high-risk periods. By using effective biopesticides and applying them based on weather predictions, grape growers can reduce chemical fungicide use and lessen the environmental impact of managing grape downy mildew."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science in Life Sciences"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Advancing Sustainable Grape Downy Mildew Management: Biopesticide Trials and Risk Assessment System"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Nita, Mizuho"],"dc:contributor.committeemember":["Baudoin, Antonius B.","McCall, David Scott"],"dc:contributor.department":["Plant Pathology, Physiology and Weed Science"],"dc:creator":["Ames, Jonathan Eugene"],"dc:date.accessioned":["2025-12-10T09:00:43Z"],"dc:date.available":["2025-12-10T09:00:43Z"],"dc:date.issued":["2025-12-09"],"dc:description.abstract":["Grape downy mildew, caused by Plasmopara viticola, significantly damages grape crops (Vitis spp.), reducing yields by up to 75% in unprotected vineyards. 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The mechanistic model, which combined two published empirical models, outperformed the empirical models based on field trial data, achieving 60.3% accuracy in predicting downy mildew incidence, demonstrating its potential to reduce fungicide overapplication as part of integrated pest management."],"dc:description.abstractgeneral":["Grape downy mildew poses a serious threat to grape crops, potentially causing harvest losses of up to 75% when vines are unprotected. Traditionally, grape growers depend on chemical fungicides, but their repeated use can lead to resistance and may be restricted due to safety or environmental concerns. In Virginia during 2024 and 2025, we tested much safer biopesticides both in vineyards and greenhouses. While conventional fungicides remained the most effective, some biopesticides, such as the GEA 249 complex (product name: Kendal), Bacillus mycoides Isolate J (Lifegard), and Pseudomonas chlororaphis strain AFS009 (Hower EVO), performed nearly as well. Additionally, we developed a weather-based grape disease forecasting system to predict downy mildew outbreaks using weather data that does not require your own weather stations. When validated against downy mildew data collected from the field from 2022 to 2025, the system successfully identified high-risk periods. By using effective biopesticides and applying them based on weather predictions, grape growers can reduce chemical fungicide use and lessen the environmental impact of managing grape downy mildew."],"dc:description.degree":["Master of Science in Life Sciences"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:45058"],"dc:identifier.uri":["https://hdl.handle.net/10919/139858"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Biopesticides","Sustainability","Modeling","Viticulture"],"dc:title":["Advancing Sustainable Grape Downy Mildew Management: Biopesticide Trials and Risk Assessment System"],"dc:type":["Thesis"],"thesis:degree_discipline":["Plant Pathology, Physiology and Weed Science"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science in Life Sciences"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:07Z"}