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 project was conducted at IRDA’S Organic Agriculture Innovation Platform. Strawberries (Cleary cultivar) were produced in beds covered with black plastic mulch.
Researcher: Carl Boivin
Design and validation of a new generation of high tunnels with automatic retractable roofs, new roofing materials, and screens that will extend the harvest season.
Researcher: Annabelle Firlej
The aim of this project is to determine the combined impact on fungicide efficacy of rain and the appearance of new leaves to more accurately identify how long treatments remain effective.
Researcher: Vincent Philion