Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis
Publication details
Journal : Journal of Biophotonics , vol. 15 , p. 1–18 , 2022
International Standard Numbers
:
Printed
:
1864-063X
Electronic
:
1864-0648
Publication type : Academic article
Issue : 9
Links
:
DOI
:
doi.org/10.1002/jbio.202200097
ARKIV
:
hdl.handle.net/11250/3022853
Research areas
Bioprocessing
Quality and measurement methods
If you have questions about the publication, you may contact Nofima’s Chief Librarian.
Kjetil Aune
Chief Librarian
kjetil.aune@nofima.no
Summary
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.
