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Plant Disease
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DIGITAL.CSIC
Article . 2020 . Peer-reviewed
Data sources: DIGITAL.CSIC
Plant Disease
Article . 2020 . Peer-reviewed
Data sources: Crossref
Plant Disease
Article . 2020
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Droplet Digital PCR Technology for Detection of Ilyonectria liriodendri from Grapevine Environmental Samples

Authors: María del Pilar Martínez-Diz; Marcos Andrés-Sodupe; Mónica Berbegal; Rebeca Bujanda; Emilia Díaz-Losada; David Gramaje;

Droplet Digital PCR Technology for Detection of Ilyonectria liriodendri from Grapevine Environmental Samples

Abstract

Black-foot disease is one of the most important soilborne diseases affecting planting material in grapevine nurseries and young vineyards. Accurate, early, and specific detection and quantification of black-foot disease causing fungi are essential to alert growers and nurseries to the presence of the pathogens in soil, and to prevent the spread of these pathogens through grapevines using certified pathogen-free planting material and development of resistance. We comparatively assessed the accuracy, efficiency, and specificity of droplet digital PCR (ddPCR) and real-time PCR (qPCR) techniques for the detection and quantification of Ilyonectria liriodendri in bulk and rhizosphere soils, as well as grapevine endorhizosphere. Fungal abundance was not affected by soil-plant fractions. Both techniques showed a high degree of correlation across the samples assessed (R2 = 0.95) with ddPCR being more sensitive to lower target concentrations. Roots of asymptomatic vines were found to be a microbial niche that is inhabited by black-foot disease fungi.

Country
Spain
Keywords

Tree fruits, BOTANICA, Fungi, Pathogen detection, Plant Roots, Fuit, Soil, Fruit, Hypocreales, Rhizosphere, Plant Diseases

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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19
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88
187
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