Automated traps theoretically increase monitoring accuracy, allow for better targeting of pesticide treatments at a lower cost, reduce the number of field visits (longer monitoring intervals), and facilitate sharing of monitoring data while maintaining its accuracy. The aim of this project is to measure the potential of this technology and extrapolate it to an apple-monitoring network. The five parameters identified above will be measured for three years using a monitoring network for five species on a minimum of seven sites in Québec’s main apple-growing regions. Various types of automated attractant traps (by Spensa, Trapview, and IRDA) will be compared to standard monitoring traps for the following pests (excluding cases of incompatibility of a system with certain pests): apple sawflies, apple maggots, obliquebanded leafrollers, codling moths, and dogwood borers. The IRDA trap is a homemade assembly consisting of a trap, a camera, a modem, and commonly available accessories. The comparisons will serve to determine the recommended methods for the tested technologies on the farm and in Québec’s apple R&D and knowledge transfer network.
From 2018 to 2021
Pest, weed, and disease control
This project will help to better target pesticide treatments and improve their cost-effectiveness.
Centre de recherche sur les grains | Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec - Prime-Vert Programme | Technical Support Clubs
This project helped to determine if there is a significant correlation between the number of adult spotted wing drosophila captured and yield losses observed in the field.
Researcher: Annabelle Firlej
The project measures the nitrogen contribution of sawdust mulch.
Researcher: Christine Landry