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Encoder-decoder neural networks for predicting future FTIR spectra - application to enzymatic protein hydrolysis.

التفاصيل البيبلوغرافية
العنوان: Encoder-decoder neural networks for predicting future FTIR spectra - application to enzymatic protein hydrolysis.
المؤلفون: Kuchta M; Department of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway., Wubshet SG; Nofima - Norwegian Institute of Food, Fisheries and Aquaculture Research, Ås, Norway., Afseth NK; Nofima - Norwegian Institute of Food, Fisheries and Aquaculture Research, Ås, Norway., Mardal KA; Department of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway.; Department of Mathematics, University of Oslo, Oslo, Norway., Liland KH; Department of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.
المصدر: Journal of biophotonics [J Biophotonics] 2022 Sep; Vol. 15 (9), pp. e202200097. Date of Electronic Publication: 2022 Jun 22.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101318567 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1864-0648 (Electronic) Linking ISSN: 1864063X NLM ISO Abbreviation: J Biophotonics Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Weinheim : Wiley-VCH
مواضيع طبية MeSH: Neural Networks, Computer* , Proteins*, Hydrolysis ; Molecular Weight ; Spectroscopy, Fourier Transform Infrared
مستخلص: In the process of converting food-processing by-products to value-added ingredients, fine grained control of the raw materials, enzymes and process conditions ensures the best possible yield and economic return. However, when raw material batches lack good characterization and contain high batch variation, online or at-line monitoring of the enzymatic reactions would be beneficial. We investigate the potential of deep neural networks in predicting the future state of enzymatic hydrolysis as described by Fourier-transform infrared spectra of the hydrolysates. Combined with predictions of average molecular weight, this provides a flexible and transparent tool for process monitoring and control, enabling proactive adaption of process parameters.
(© 2022 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)
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فهرسة مساهمة: Keywords: FTIR; deep learning; encoder-decoder; enzymatic protein hydrolysis; process control
المشرفين على المادة: 0 (Proteins)
تواريخ الأحداث: Date Created: 20220603 Date Completed: 20220908 Latest Revision: 20221020
رمز التحديث: 20231215
DOI: 10.1002/jbio.202200097
PMID: 35656929
قاعدة البيانات: MEDLINE
الوصف
تدمد:1864-0648
DOI:10.1002/jbio.202200097