Average molecular weight, degree of hydrolysis and dry-film FTIR fingerprint of milk protein hydrolysates: Intercorrelation and application in process monitoring. (25th April 2020)

• Record Type: Journal Article
• Authors: Kristoffersen, Kenneth Aase; Afseth, Nils Kristian; Böcker, Ulrike; Lindberg, Diana; de Vogel-van den Bosch, Heleen; Ruud, Mari Linnéa; Wubshet, Sileshi Gizachew
• Is Part Of: Food chemistry. Volume 310(2020)
• Publication Date: 2020-04-25
• Subjects: Fourier-transform infrared spectroscopy -- Enzymatic protein hydrolysis -- Degree of hydrolysis -- Average molecular weight -- Partial least squares regression; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2019.125800
• Languages: English
• ISSNs: 0308-8146

Abstract

Graphical abstract: Highlights: DH% and M w were monitored during enzymatic protein hydrolysis of dairy proteins. Intercorrelation of DH% vs M w were studied for 60 milk protein hydrolysates. A PLSR model was developed for prediction of DH% based on molecular weight distribution profiles. A multivariate model based on dry-film FTIR was developed for dual prediction of DH% and M w . Abstract: Fourier-transform infrared (FTIR) spectroscopy was applied to predict the degree of hydrolysis (DH%) and weight-average molecular weight ( M w ) in milk protein hydrolysates. Both DH% and M w are important quality parameters of protein hydrolysates. Measuring these parameters and following their development during proteolytic reactions is therefore essential for process control and optimization in industry. In the present study the intercorrelation and the complimentary nature of these parameters were investigated and a partial least squares regression (PLSR) model was developed for the prediction of DH% from molecular weight distributions. Finally, we developed PLSR models based on dry-film FTIR spectroscopy for the prediction of both DH% and M w . Here spectral changes in the amide region were found to be important for the two calibration models, underlining the advantage of dry-film FTIR measurement. This shows that dry-film infrared spectroscopy is a promising tool for dual prediction of DH% and M w .