The Royal Institution for the Advancement of Learning/McGill University

Published purpose

Thermal pre-treatment, specifically Radio Frequency (RF) treatment of pulses prior to protein extraction has been proven to improve fractionation efficiency and functionality of protein concentrates. Towards fully adopting these methods at industrial scale, it is necessary to establish the optimum process configuration and conditions that maximizes the overall technoeco-environmental performance. While the experimental optimization approach provides a reflective model for optimization, just a few scenarios can be carried out. Therefore, this project seeks to develop a digital twin model to reflect pilot-scale pea and faba bean flour and protein fractionation, thus providing a means for control, optimization, and productprocess performance prediction. This project will support the CSTIP goals in terms of enabling the innovation of new technologies. The dataset generated will support the design and improvement of plant protein fractionation technologies. Moreover, this will strengthen collaborations among different stakeholders in pulse protein production towards enhancing the overall Canadian bioeconomy.