Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis
Kuchta, Miroslav; Wubshet, Sileshi Gizachew; Afseth, Nils Kristian; Mardal, Kent-Andre; Liland, Kristian Hovde
Peer reviewed, Journal article
Published version
Date
2022Metadata
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Abstract
In the process of converting food-processing by-products to value-addedingredients, fine grained control of the rawmaterials, enzymes and process conditionsensures the best possible yield and eco-nomic return. However, when raw mate-rial batches lack good characterization andcontain high batch variation, online or at-line monitoring of the enzymatic reac-tions would be beneficial. We investigate the potential of deep neural networks inpredicting the future state of enzymatic hydrolysis as described by Fourier-trans-form infrared spectra of the hydrolysates. Combined with predictions of averagemolecular weight, this provides a flexible and transparent tool for process moni-toring and control, enabling proactive adaption of process parameters.