Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis
Publikasjonsdetaljer
Tidsskrift : Journal of Biophotonics , vol. 15 , p. 1–18 , 2022
Internasjonale standardnummer
:
Trykt
:
1864-063X
Elektronisk
:
1864-0648
Publikasjonstype : Vitenskapelig artikkel
Sak : 9
Lenker
:
DOI
:
doi.org/10.1002/jbio.202200097
ARKIV
:
hdl.handle.net/11250/3022853
Forskningsområder
Bioprosessering
Kvalitet og målemetoder
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Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no
Sammendrag
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.
