The development of a decision support tool is necessary for producers to recognize the conditions that impact growth, yield and nutritional quality of alfalfa, but also to evaluate the anticipated gains after correction of problems. This project aims to develop this digital tool to improve alfalfa production. To do so, artificial intelligence, the expertise of researchers and the participation of 20 advisors specialized in forage production and 80 producers from Quebec and the Maritime provinces will be combined. The application will be easy to use. It will allow the valorization of data on the nutritional value of forages obtained on the farm (by near infrared analysis), the current analysis of soils, the evaluation of the health of a soil profile in the field and finally, the prediction of the nutritional quality and the yield of alfalfa.
This project aims to develop a digital decision support tool to improve the nutritional quality and yeld of alfalfa from analyses of the nutritional quality of forages, based on its relationship with soil fertility and health, while including the other pedoclimatic parameters that define alfalfa production conditions.
From 2020 to 2024
Field crops, Livestock production
Association canadienne pour les plantes fourragères (ACPF) | Coordination des services-conseils (CSC) | Lactanet | Agritel | Laval University | Polytechnique Montréal
The project consists of evaluating soil degradation based on representative samples taken in Québec’s main soil regions and parent materials.
Ten test sites will operate over a two-year period on farms spread over ten Québec regions to compare the performance of winter and spring cereals.
This project looks to develop decision-support tools informed by observations of “bellwether” plots and use these tools to disseminate relevant information to irrigators.
Researcher: Carl Boivin