Predicting disease occurrence of cabbage Verticillium wilt in monoculture using species distribution modeling

Kentaro Ikeda; Takeshi Osawa

doi:10.7717/peerj.10290

Predicting disease occurrence of cabbage Verticillium wilt in monoculture using species distribution modeling

PeerJ. 2020 Nov 17:8:e10290. doi: 10.7717/peerj.10290. eCollection 2020.

Authors

Kentaro Ikeda¹, Takeshi Osawa²

Affiliations

¹ Department of Agriculture, Gunma Prefectural Office, Isesaki, Gunma, Japan.
² Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, Hachioji, Tokyo, Japan.

Abstract

Background: Although 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.

Methods: A 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.

Results: Grids 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 road density at 97.1%, followed by TWI at 2.3%, and elevation at 0.5%. The highest permutation importance was road density at 93.0%, followed by TWI at 7.0%, while the variable elevation at 0.0%. This method of predicting disease probability occurrence can help with disease monitoring in areas with high probability occurrence and inform farmers about the selection of control measures.

Keywords: Cabbage; Integrated pest management; Species distribution modeling; Verticillium wilt.

Grants and funding

This work was supported by a grant from the Science and Technology Research Promotion Program for Agriculture, Forestry, Fisheries and Food Industry (25056C) from the Ministry of Agriculture, Forestry and Fisheries of Japan, Gunma New Agricultural Frontier Fund from Gunma Prefectural Government of Japan, and JSPS KAKENHI Grant Number 16H05061. There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.