Steps toward a digital twin for functional food production with increased health benefits

Helena Mylise Sørensen; David Cunningham; Rengesh Balakrishnan; Susan Maye; George MacLeod; Dermot Brabazon; Christine Loscher; Brian Freeland

doi:10.1016/j.crfs.2023.100593

Steps toward a digital twin for functional food production with increased health benefits

Curr Res Food Sci. 2023 Sep 26:7:100593. doi: 10.1016/j.crfs.2023.100593. eCollection 2023.

Authors

Helena Mylise Sørensen^{1

2}, David Cunningham¹, Rengesh Balakrishnan¹, Susan Maye³, George MacLeod³, Dermot Brabazon², Christine Loscher¹, Brian Freeland¹

Affiliations

¹ School of Biotechnology, Dublin City University, D9 Dublin, Ireland.
² I-Form, Advanced Manufacturing Research Centre, Dublin City University, D9 Dublin, Ireland.
³ Dairygold Co-Operative Society Limited, Clonmel Road, Co. Cork, P67 DD36, Mitchelstown, Ireland.

Abstract

Lactobacillus rhamnosus (L. rhamnosus) is a commensal bacterium with health-promoting properties and with a wide range of applications within the food industry. To improve and optimize the control of L. rhamnosus biomass production in batch and fed-batch bioprocesses, this study proposes the application of artificial neural network (ANN) modelling to improve process control and monitoring, with potential future implementation as a basis for a digital twin. Three ANNs were developed using historical data from ten bioprocesses. These ANNs were designed to predict the biomass in batch bioprocesses with different media compositions, predict biomass in fed-batch bioprocesses, and predict the growth rate in fed-batch bioprocesses. The immunomodulatory effect of the L. rhamnosus samples was examined and found to elicit an anti-inflammatory response as evidenced by the inhibition of IL-6 and TNF-α secretion. Overall, the findings of this study reinforce the potential of ANN modelling for bioprocess optimization aimed at improved control for maximising the volumetric productivity of L. rhamnosus as an immunomodulatory agent with applications in the functional food industry.

Keywords: Artificial neural network; Bioprocessing; Digital twin; Process control; Process modelling.