dc.date.accessioned | 2022-10-10T15:22:45Z | |
dc.date.available | 2022-10-10T15:22:45Z | |
dc.date.created | 2022-07-28T13:00:50Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Kuchta, Miroslav Wubshet, Sileshi Gizachew Afseth, Nils Kristian Mardal, Kent-Andre Liland, Kristian Hovde . Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis. Journal of Biophotonics. 2022, 1-18 | |
dc.identifier.uri | http://hdl.handle.net/10852/97124 | |
dc.description.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. | |
dc.language | EN | |
dc.publisher | Wiley - VCH Verlag GmbH | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | Encoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis | |
dc.title.alternative | ENEngelskEnglishEncoder–decoder neural networks for predicting future FTIR spectra – application to enzymatic protein hydrolysis | |
dc.type | Journal article | |
dc.creator.author | Kuchta, Miroslav | |
dc.creator.author | Wubshet, Sileshi Gizachew | |
dc.creator.author | Afseth, Nils Kristian | |
dc.creator.author | Mardal, Kent-Andre | |
dc.creator.author | Liland, Kristian Hovde | |
cristin.unitcode | 185,15,13,15 | |
cristin.unitname | Mekanikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 2039937 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Biophotonics&rft.volume=&rft.spage=1&rft.date=2022 | |
dc.identifier.jtitle | Journal of Biophotonics | |
dc.identifier.volume | 15 | |
dc.identifier.issue | 9 | |
dc.identifier.doi | https://doi.org/10.1002/jbio.202200097 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 1864-063X | |
dc.type.version | PublishedVersion | |
cristin.articleid | e202200097 | |
dc.relation.project | NFR/300305 | |
dc.relation.project | NFR/309259 | |
dc.relation.project | NFR/280709 | |
dc.relation.project | NFR/303362 | |
dc.relation.project | NFR/314111 | |