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Título: | A qPCR-based method for the detection and quantification of the peach powdery mildew (Podosphaera pannosa) in epidemiological studies |
Autor: | Marimon, Neus CSIC ORCID; Eduardo, Iban CSIC ORCID; León, Maela; Berbegal, Mónica; Armengol, Josep; Luque, Jordi | Fecha de publicación: | 2020 | Editor: | Springer Nature | Citación: | European Journal of Plant Pathology 158: 1005–1016 (2020) | Resumen: | A qPCR-based method was developed to detect and quantify Podosphaera pannosa, the main causal agent of peach powdery mildew. A primer pair was designed to target part of the ITS region of the fungal ribosomal DNA, which proved to be highly specific and sensitive. A minimum of 2.81 pg µL− 1 of P. pannosa DNA and 6 conidia mL− 1 in artificially-prepared conidia suspensions were found to be the limit of detection. Moreover, a quantification of conidia placed on plastic tapes commonly used in volumetric air samplers was performed. Regression equations on conidia quantification obtained either from aqueous conidia suspensions or conidia placed on plastic tapes were similar. The protocol was further validated in field conditions by estimating the number of P. pannosa conidia obtained with an air sampler, by both microscopic and molecular quantification. Both techniques detected the peaks of conidia production during a 4-month sampling period, and a significant correlation (r = 0.772) was observed between both quantification methods. Additionally, the molecular method was applied to detect latent fungal inoculum in different plant parts of peach trees. The pathogen was detected mainly on the bark of affected twigs, and to a lesser extent, in foliar buds. The method developed here can be applied in the study of P. pannosa epidemiology and can help in improving the management of this pathogen through its early detection and quantification. | Versión del editor: | https://doi.org/10.1007/s10658-020-02136-0 | URI: | http://hdl.handle.net/10261/228978 | DOI: | 10.1007/s10658-020-02136-0 | E-ISSN: | 1573-8469 |
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20TV65_Marimon_Ppan_primers_EJPP_postprint.pdf | 594,23 kB | Adobe PDF | Visualizar/Abrir |
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