Apple growing requires annual pesticide sprays against insects, mites, diseases, weeds, etc. Many of the products used have major environmental impacts and/or are costly. Proven methods for detecting, monitoring, and controlling pests and thereby reducing these risks are used to varying degrees by growers. Wider use of these new approaches would reduce the ecological footprint of Québec agriculture. A demonstration plot will be run for four years in five of Québec’s biggest apple growing regions: Laurentides, Montérégie Est, Montérégie Ouest, Estrie, and Capitale-Nationale. On each site a low-risk pest management program will be compared to the farm’s current program. The low-risk program will consist of a set of techniques targeting the full range of apple pests, specifically apple maggots, the codling moths, fire blight, apple scab, spider mites, and weeds. Yield, monitoring, economic, and risk data will be collected and compared annually for both types of program on each site. Apple growers will be informed of the results through communiques from RAP (Réseau d’avertissements phytosanitaires), demo days, talks, videos, training sessions, and so on.
From 2018 to 2022
Pest, weed, and disease control
These preventive methods to control apple pests will lead to reduced pesticide use, reducing the industry’s environmental footprint while signalling its innovative approach.
Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec - Prime-Vert Programme | Producteurs de pommes du Québec | Technical support clubs
Validation and adaptation of pest and disease monitoring and decision support tools.
Researcher: Annabelle Firlej
The aim of this project was to test the general hypothesis that exclusion nets, when properly used, can prevent attacks by most apple pests and reduce disease incidence with no major adverse effects on fruit quality.
Researcher: Gérald Chouinard
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