Problems associated with the Japanese beetle, anthracnose, and grey mold will increase due to predicted climate change in Québec. They will have a major impact on berry crops because they already require numerous pesticide sprays that do not effectively control the damage. We now have new bioclimatic models for the Japanese beetle, anthracnose, and grey mold. This project will consist of validating and adapting these models to conditions in Québec to prepare for future climatic conditions, which are likely to increase crop damage.
For the Japanese beetle component, traps will be installed on six farms in five regions for two years to obtain adult population curves during the growing season. The collected data will be compared with the data generated by the model for the beginning of the adult observation period, the peak flight period, and the end of the adult observation period.
For anthracnose and grey mold, their symptoms will be monitored and weather data collected on three farms in three regions for three years. These will be compared with infection rates predicted by the models. The data collected during the project will make it possible to optimize the models used to predict activity periods for the Japanese beetle, an exotic pest that has appeared in a number of regions in Québec, and infection risks for anthracnose and grey mold on strawberries.
From 2018 to 2021
Pest, weed, and disease control
IRDA is working to provide growers with strategies to control new crop pests that are likely to emerge as a result of climate change.
Carrefour industriel et expérimental Lanaudière | Réseau de lutte intégrée Orléans | Ecolo-Max | Pierrette Lavoie, agr. | CAE | Prisme | Club Corymbe | Ministère de l’Agriculture, des Pêcheries et de l’Alimentation du Québec
Developing a new scab control strategy based on selecting the lowest-risk products that best fit the circumstances at hand, and tailoring the doses accordingly.
Researcher: Vincent Philion
Exploration of the potential of detecting water stress in lowbush blueberries using a thermal infrared imaging sensor installed on a drone.
Researcher: Carl Boivin