The aim of this project is to use high-throughput sequencing (HTS) techniques to develop a process for detecting and identifying viruses (PDIV). The process will combine HTS with innovative bioinformatic analysis tools so that, using a single analysis, plant pathologists will be able to receive, via a user-friendly interface, a quantitative verdict regarding the presence and identity of all viruses infecting the sample.
To ensure the accurate detection and identification of all raspberry and strawberry viruses, the project will develop
A database with all the HTS sequences will be linked to a database of the agronomic, environmental, and diagnostic parameters for each sample. During trials, these sequence collections and databases will be used to demonstrate the superior diagnostic efficacy of the PDIV compared to reference protocols used by Laboratoire d’expertise et de diagnostic en phytoprotection (LEDP).
An economic analysis will compare the costs of implementing and utilizing the LEDP and PDIV tests, and the benefits derived from using the PDIV.
From 2019 to 2023
Soil health, Pest, weed, and disease control
With high-throughput sequencing, users can identify all viruses infecting a sample with a single analysis.
Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec | Centre de recherche du CHU de Québec-Université Laval | Ferme Onésime Pouliot | Phytoclone
The data generated by this project was used to develop a new NPK fertilization chart that reflects technical, agronomic, and environmental issues.
Researcher: Christine Landry
This project will evaluate the efficiency of the initial releases of sterile spotted wing drosophilas on fall raspberry plots.
Researcher: Annabelle Firlej
The main aim of this project is to test a bacterial detection technique developed in Austria that consists of quantifying inoculum carried by bees.
Researcher: Vincent Philion