Dataset Information

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

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.

SUBMITTER: Ikeda K

PROVIDER: S-EPMC7678443 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

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

Ikeda Kentaro K Osawa Takeshi T

PeerJ 20201117

<h4>Background</h4>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 targ ...[more]

PMID: 33240630

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Project description:Knowledge of pathogen biology and genetic diversity is a cornerstone of effective disease management, and accurate identification of the pathogen is a foundation of pathogen biology. Species names provide an ideal framework for storage and retrieval of relevant information, a system that is contingent on a clear understanding of species boundaries and consistent species identification. Verticillium, a genus of ascomycete fungi, contains important plant pathogens whose species boundaries have been ill defined. Using phylogenetic analyses, morphological investigations and comparisons to herbarium material and the literature, we established a taxonomic framework for Verticillium comprising ten species, five of which are new to science. We used a collection of 74 isolates representing much of the diversity of Verticillium, and phylogenetic analyses based on the ribosomal internal transcribed spacer region (ITS), partial sequences of the protein coding genes actin (ACT), elongation factor 1-alpha (EF), glyceraldehyde-3-phosphate dehydrogenase (GPD) and tryptophan synthase (TS). Combined analyses of the ACT, EF, GPD and TS datasets recognized two major groups within Verticillium, Clade Flavexudans and Clade Flavnonexudans, reflecting the respective production and absence of yellow hyphal pigments. Clade Flavexudans comprised V. albo-atrum and V. tricorpus as well as the new species V. zaregamsianum, V. isaacii and V. klebahnii, of which the latter two were morphologically indistinguishable from V. tricorpus but may differ in pathogenicity. Clade Flavnonexudans comprised V. nubilum, V. dahliae and V. longisporum, as well as the two new species V. alfalfae and V. nonalfalfae, which resembled the distantly related V. albo-atrum in morphology. Apart from the diploid hybrid V. longisporum, each of the ten species corresponded to a single clade in the phylogenetic tree comprising just one ex-type strain, thereby establishing a direct link to a name tied to a herbarium specimen. A morphology-based key is provided for identification to species or species groups.

Dataset Information

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

Background

Methods

Results

Publications

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

Similar Datasets

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