New methodology for controlled testing of foaming properties of protein suspensions

Reproducing high mechanical load during industrial processing of UHT milk: Effect on frothing capacity

In this study, possible reasons for an increased level of free fatty acids (FFAs) in Ultra-High Temperature (UHT) treated full fat (3.5% wt/wt) milk and its effect on the frothing properties of milk were investigated. Lipolysis of raw milk from 2 different breeds of cattle (Holstein and Jersey) was induced by mechanical stress and kinetics of lipolysis were compared. Frothing capacity and foam stability of shelf stable milk with different concentrations of FFAs were determined, with a good to medium initial foam volume for up to 4 mEquiv FFA · (100 g fat)-1 fat and poor foam stability with >2 mEquiv FFA · (100 g fat)-1. A combination of mechanical stress and initial condition of fresh raw milk was found to trigger lipolysis and potential sources of mechanical stress during milk processing were identified.

Spectroscopic-Based Prediction of Milk Foam Properties for Barista Applications

The important quality parameters of cow’s milk for barista applications are frothability and foam stability. In the past, quality assessment was very time-consuming and could only be carried out after milk treatment had been completed. Since spectroscopy is already established in dairies, it could be advantageous to develop a spectrometer-based measurement method for quality control for barista applications. By integrating online spectroscopy to the processing of UHT (ultra-high temperature processing) milk before filling, it can be checked whether the currently processed product is suitable for barista applications. To test this hypothesis, a feasibility study was conducted. For this purpose, seasonal UHT whole milk samples were measured every 2 months over a period of more than 1 year, resulting in a total of 269 milk samples that were foamed. Samples were frothed using a self-designed laboratory frother. Frothability at the beginning and foam loss after 15 min describe the frothing characteristics of the milk and are predicted from the spectra. Near-infrared, Raman, and fluorescence spectra were recorded from each milk sample. These spectra were preprocessed using 15 different mathematical methods. For each spectrometer, 85% of the resulting spectral dataset was analyzed using partial least squares (PLS) regression and nine different variable selection (VS) algorithms. Using the remaining 15% of the spectral dataset, a prediction error was determined for each model and used to compare the models. Using spectroscopy and PLS modeling, the best results show a prediction error for milk frothability of 3% and foam stability of 2%.