Literature DB >> 21167874

A semi-automatic non-destructive method to quantify grapevine downy mildew sporulation.

Elisa Peressotti1, Eric Duchêne, Didier Merdinoglu, Pere Mestre.   

Abstract

The availability of fast, reliable and non-destructive methods for the analysis of pathogen development contributes to a better understanding of plant-pathogen interactions. This is particularly true for the genetic analysis of quantitative resistance to plant pathogens, where the availability of a method allowing a precise quantification of pathogen development allows the reliable detection of different genomic regions involved in the resistance. Grapevine downy mildew, caused by the biotrophic Oomycete Plasmopara viticola, is one of the most important diseases affecting viticulture. Here we report the development of a simple image analysis-based semi-automatic method for the quantification of grapevine downy mildew sporulation, requiring just a compact digital camera and the open source software ImageJ. We confirm the suitability of the method for the analysis of the interaction between grapevine and downy mildew by performing QTL analysis of resistance to downy mildew as well as analysis of the kinetics of downy mildew infection. The non-destructive nature of the method will enable comparison between the phenotypic and molecular data obtained from the very same sample, resulting in a more accurate description of the interaction, while its simplicity makes it easily adaptable to other plant-pathogen interactions, in particular those involving downy mildews.
Copyright © 2010 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 21167874     DOI: 10.1016/j.mimet.2010.12.009

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  5 in total

1.  Adaptation of a plant pathogen to partial host resistance: selection for greater aggressiveness in grapevine downy mildew.

Authors:  Chloé E L Delmas; Frédéric Fabre; Jérôme Jolivet; Isabelle D Mazet; Sylvie Richart Cervera; Laurent Delière; François Delmotte
Journal:  Evol Appl       Date:  2016-02-24       Impact factor: 5.183

2.  Spatial-Spectral Analysis of Hyperspectral Images Reveals Early Detection of Downy Mildew on Grapevine Leaves.

Authors:  Virginie Lacotte; Sergio Peignier; Marc Raynal; Isabelle Demeaux; François Delmotte; Pedro da Silva
Journal:  Int J Mol Sci       Date:  2022-09-02       Impact factor: 6.208

Review 3.  Phenotyping for QTL identification: A case study of resistance to Plasmopara viticola and Erysiphe necator in grapevine.

Authors:  Tyrone Possamai; Sabine Wiedemann-Merdinoglu
Journal:  Front Plant Sci       Date:  2022-08-11       Impact factor: 6.627

Review 4.  Digital image processing techniques for detecting, quantifying and classifying plant diseases.

Authors:  Jayme Garcia Arnal Barbedo
Journal:  Springerplus       Date:  2013-12-07

5.  Identification of Lipid Markers of Plasmopara viticola Infection in Grapevine Using a Non-targeted Metabolomic Approach.

Authors:  Lise Negrel; David Halter; Sabine Wiedemann-Merdinoglu; Camille Rustenholz; Didier Merdinoglu; Philippe Hugueney; Raymonde Baltenweck
Journal:  Front Plant Sci       Date:  2018-03-21       Impact factor: 5.753

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.