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|Title:||Multi-scale benchtop 1H NMR spectroscopy for milk analysis||Authors:||Söyler, Alper
Öztop, Mecit H.
|Keywords:||Artificial neural network (ANN)
Benchtop NMR spectroscopy
|Issue Date:||2021||Publisher:||Academic Press||Abstract:||Benchtop NMR systems offers various advantages such as being easy to use, not requiring constant maintenance and being available at affordable prices. In this study, multiple aspects of benchtop NMR spectroscopy were explored to analyze milk in an industrial context, either regarding the quality of production or regarding the differentiation of the final product. The first part focuses on the production conditions of lactose hydrolysis in milk and quantitative online NMR spectroscopy was adapted to follow lactose hydrolysis in milk in continuous flow mode. The second part focuses on differentiating milk samples having different properties. 36 milk samples from France and Turkey were analysed and glycerol, fat and sugar contents were measured from the NMR spectra. Combination of spectroscopic data with a proposed Artificial Neural Network model enabled to classify milk of different origins and different properties. This study shows that benchtop NMR spectroscopy is a versatile non-destructive control method that can help controlling milk quality both during and after production. © 2020 Elsevier Ltd||URI:||https://doi.org/10.1016/j.lwt.2020.110557
|Appears in Collections:||Food Engineering / Gıda Mühendisliği|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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