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dc.contributor.author | Martínez Martínez, María del Pilar | es_ES |
dc.contributor.author | Andrés-Sodupe, Marcos | es_ES |
dc.contributor.author | Berbegal Martinez, Monica | es_ES |
dc.contributor.author | Bujanda, Rebeca | es_ES |
dc.contributor.author | Díaz-Losada, Emilia | es_ES |
dc.contributor.author | Gramaje Pérez, David | es_ES |
dc.date.accessioned | 2020-04-17T12:48:40Z | |
dc.date.available | 2020-04-17T12:48:40Z | |
dc.date.issued | 2020-04 | es_ES |
dc.identifier.issn | 0191-2917 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/140857 | |
dc.description | http://apsjournals.apsnet.org/feedback/show | es_ES |
dc.description.abstract | [EN] 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. | es_ES |
dc.description.sponsorship | David Gramaje was supported by the DOC-INIA program from the INIA, co-funded by the European Social Fund. María del Pilar Martínez-Diz was supported by the FPI-INIA program from the INIA. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Scientific Societies | es_ES |
dc.relation.ispartof | Plant Disease | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Fungi | es_ES |
dc.subject | Fruit | es_ES |
dc.subject | Tree fruits | es_ES |
dc.subject | Pathogen detection | es_ES |
dc.subject.classification | BOTANICA | es_ES |
dc.title | Droplet Digital PCR technology for detection of Ilyonectria liriodendri from grapevine environmental samples | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1094/PDIS-03-19-0529-RE | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Agroforestal Mediterráneo - Institut Agroforestal Mediterrani | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto de Diseño para la Fabricación y Producción Automatizada - Institut de Disseny per a la Fabricació i Producció Automatitzada | es_ES |
dc.description.bibliographicCitation | Martínez Martínez, MDP.; Andrés-Sodupe, M.; Berbegal Martinez, M.; Bujanda, R.; Díaz-Losada, E.; Gramaje Pérez, D. (2020). Droplet Digital PCR technology for detection of Ilyonectria liriodendri from grapevine environmental samples. Plant Disease. 104(4):1144-1150. https://doi.org/10.1094/PDIS-03-19-0529-RE | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1094/PDIS-03-19-0529-RE | es_ES |
dc.description.upvformatpinicio | 1144 | es_ES |
dc.description.upvformatpfin | 1150 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 104 | es_ES |
dc.description.issue | 4 | es_ES |
dc.relation.pasarela | S\401706 | es_ES |
dc.contributor.funder | Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria | es_ES |
dc.contributor.funder | European Social Fund |