ArticlePeerJ2020
Predicting disease occurrence of cabbage Verticillium wilt in monoculture using species distribution modeling.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prediction of the Global Potential Distribution Area ofBiology · 2026Article
- Modeling global habitat suitability of Agroathelia rolfsii causing Sclerotium wilt disease of tomato with emphasis on Ghana.Scientific reports · 2025Article
- The Causative Pathogens and Control Methods for Verticillium Wilt in Chinese Cabbage.The plant pathology journal · 2025Review
- The Involvement of Human Factors Brings New Findings for Predicting Global Suitability Habitat forEcology and evolution · 2025Article
- Risk Evaluation of Verticillium Wilt on Cabbage Grown in Soil Reused from Sediment Basins.Microbes and environments · 2025Article
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Authors and funding
2 authors.
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Abstract
backgroundAlthough integrated pest management (IPM) is essential for conservation agriculture, this method can be inadequate for severely infected fields. The ability to predict the potential occurrence of severe infestation of soil-borne disease would enable farmers to adopt suitable methods for high-risk areas, such as soil disinfestation, and apply other options for lower risk areas. Recently, researchers have used species distribution modeling (SDM) to predict the occurrence of target plant and animal species based on various environmental variables. In this study, we applied this technique to predict and map the occurrence probability of a soil-borne disease, Verticillium wilt, using cabbage as a case study.
methodsA disease survey assessing the distribution of Verticillium wilt in cabbage fields in Tsumagoi village (central Honshu, Japan) was conducted two or three times annually from 1997 to 2013. Road density, elevation and topographic wetness index (TWI) were selected as explanatory variables for disease occurrence potential. A model of occurrence probability of Verticillium wilt was constructed using the MaxEnt software for SDM analysis. As the disease survey was mainly conducted in an agricultural area, the area was weighted as "Bias Grid" and area except for the agricultural area was set as background.
resultsGrids with disease occurrence showed a high degree of coincidence with those with a high probability occurrence. The highest contribution to the prediction of disease occurrence was the variable
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