Potential of Raman spectroscopy for in-line measurement of raw milk composition

Abstract

A method for the in-line measurement of raw milk composition is beneficial for the dairy industry as it allows processors to make timely decisions, i.e., standardization, prior to the milk entering a process. It facilitates more enhanced operational control and offers the potential for improved process efficiencies. One such technology of potential commercial value is Raman spectroscopy due to its ability to measure macromolecules in an aqueous environment and compatibility with in-line measurements. This study investigated the suitability of Raman spectroscopy to measure macro components (fat, protein, and lactose) in raw milk. 80 raw milk samples were analysed using a Raman spectroscopy instrument coupled with an optical fibre probe. Variations in process variables such as temperature and the effect of agitation on Raman spectral features (intensity, shape, and wavelength shift) were considered prior to model development. Due to the overlapping response of fat, protein, and lactose in the Raman spectrum of raw milk, multivariate regression models were developed for their quantification. The developed partial least squares (PLS) regression models predicted the percentage of fat, protein, and lactose in raw milk with a root mean square error of prediction (RMSEP) of 0.15, 0.11 and 0.04, coefficient of determination for prediction (R2p) 0.96, 0.89 and 0.89, and the ratio of prediction error to deviation (RPD) of 8.16, 3.16, and 2.89.