Infrared Spectroscopy Applications in Milk Composition Analysis
Infrared spectroscopy analysis of milk components presents unique measurement challenges due to the complex, heterogeneous nature of dairy matrices. Traditional methods require sample preparation and homogenization steps that can introduce variability, while flowing samples exhibit particle distribution effects that impact measurement accuracy. Current systems achieve precision within ±0.1% for major components like fat and protein, but struggle with trace components and adulterant detection at concentrations below 1%.
The fundamental challenge lies in obtaining accurate, reproducible spectral measurements from heterogeneous flowing samples while maintaining the sensitivity needed to detect subtle compositional changes and adulterations.
This page brings together solutions from recent research—including attenuation-based analysis of flowing samples, protein-specific spectral fingerprinting techniques, and advanced statistical methods for detecting compositional deviations. These and other approaches focus on practical implementation in dairy processing environments while maintaining measurement accuracy and adulterant detection capabilities.
1. Mid-Infrared Spectroscopy for Flowing Heterogeneous Samples with Attenuation-Based Component Analysis
FOSS ANALITIKAL AS, FOSS ANALYTICAL AS, FOSS Analytical A/S, 2019
Quantitative analysis of components in flowing, heterogeneous samples using mid-infrared (MIR) spectroscopy without homogenization. The method involves measuring attenuation of MIR radiation as the sample flows through the measurement area. This allows determining component concentrations without requiring homogenization. It improves reproducibility compared to stationary measurements because particles move during flow, averaging out effects from particle size. The technique involves flowing the heterogeneous sample through a cuvette while simultaneously measuring MIR attenuation. The attenuation at specific wavelengths is used to calculate component concentrations without homogenization.
2. Spectral Analysis Method for Detecting Adulteration in Milk Proteins Using Infrared Absorption Characteristics
NIKODIMOS AE AVATIS AE OE, 2019
Detection of adulteration in milk products by analyzing the spectral characteristics of milk proteins. The method employs a novel approach that utilizes the specific absorption spectra of protein functional groups to identify deviations from the expected spectral patterns of pure milk proteins. By analyzing the position of characteristic peaks in the milk protein's infrared spectrum, deviations beyond three standard deviations from the mean position indicate potential adulteration. This approach can be applied to detect mixtures of milk proteins, such as between cow's, sheep's, and goat's milk, and is particularly useful for detecting cross-contamination during freeze-drying processes.
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