4.5 Article

Monitoring of Peronospora destructor oospores from field samples using real-time PCR

Journal

PLANT PATHOLOGY
Volume 71, Issue 8, Pages 1784-1792

Publisher

WILEY
DOI: 10.1111/ppa.13604

Keywords

COXII; downy mildew; onion; real-time PCR; soil; TaqMan probe

Funding

  1. Ministry of Agriculture, Forestry and Fisheries [17935468]

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A sensitive method for detecting onion downy mildew was developed, and significant correlations between oospore density and primary infection were observed in untreated fields.
Onion downy mildew caused by Peronospora destructor has been widespread in Japan since 2016. Soil disinfection and use of fungicides have been implemented as control measures against oospores in the soil, which are the primary source of infection. Measurements of oospore density are needed to clarify the risk of disease development and inform disease management. In this study, an experimental system capable of detecting P. destructor DNA from field samples was developed. A TaqMan probe-type primer was used to target the coxII (cytochrome c oxidase subunit II) region of the mitochondrial genome of P. destructor and no false positives were observed. Using this method, the detection limit was equivalent to 5 oospores of P. destructor/g soil in grey lowland soil and andosol. The correlation coefficient between oospore density and the primary infection rate was investigated by testing soil samples from 115 fields. Although no correlations between oospore density and the primary infection were observed in pesticide-treated fields, significant correlations were observed in untreated fields. Continuous cropping of onions increased the oospore density. The correlation between primary and secondary infection was relatively weak, and the negative predictive value of primary infection was relatively high (89.0). These results suggest that the disease-risk potential of onion downy mildew is very high, and thus it is necessary to set a low pathogen detection threshold. The system presented here provides a highly sensitive method for supporting decision-making aimed at disease control.

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