Predicting and assessing protein crop quality
Process Augmentation
Consortium Contribution
$2,471,269
Cluster Contribution
$2,021,948
Ground Truth Agriculture
Parametrics.Ag
Cas-Grain Farms
C-Merak Innovations
Goal
To improve the consistency of Canada's food value chain by developing new AI technologies that predict and assess the quality of protein crops in the field during the growing season and harvest.
Project Summary
Ground Truth Agriculture, Parametrics.Ag, Cas-Grain Farms and C-Merak Innovations are combining their expertise in the areas of software development, ingredient processing and agronomics to design an in-season protein prediction model and on-combine grain grading and quality system that can be used to assess crop quality in real time during the growing season and harvest.
In-field validation of grain quality will provide farmers with an earlier indication of their crop’s yield, protein content and overall quality to improve their decision making and sale opportunities.
This information will also provide buyers like ingredient manufacturers with a more consistent supply of feedstock for uniform ingredient formulations leading to improved food and beverage products on grocery store shelves.
