SVR Chemometrics to Quantify β-Lactoglobulin and α-Lactalbumin in Milk Using MIR.

ABSTRACT: Protein content variation in milk can impact the quality and consistency of dairy products, necessitating access to in-line real time monitoring. Here, we present a chemometric approach for the qualitative and quantitative monitoring of β-lactoglobulin and α-lactalbumin, using mid-infrared spectroscopy (MIR). In this study, we employed Hotelling T2 and Q-residual for outlier detection, automated preprocessing using nippy, conducted wavenumber selection with genetic algorithms, and evaluated four chemometric models, including partial least squares, support vector regression (SVR), ridge, and logistic regression to accurately predict the concentrations of β-lactoglobulin and α-lactalbumin in milk. For the quantitative analysis of these two whey proteins, SVR performed the best to interpret p

SUBMITTER: Babatunde HA 

PROVIDER: S-EPMC10778881 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature