Assessing the Quality of Milk Using a Multicomponent Analytical Platform MicroNIR/Chemometric.

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Milk quality assessment is crucial for consumer safety and industry standards.
• Traditional methods for milk analysis are often time-consuming and require sample preparation.
• Developing rapid, on-site, and non-destructive methods is essential for efficient quality control.

Purpose of the Study:

• To develop and validate an innovative screening platform for on-site, contactless milk quality monitoring.
• To enable simultaneous multicomponent analysis of milk's chemical composition.
• To provide a rapid and accurate method for detecting food adulteration in milk.

Main Methods:

• Utilized a miniaturized Near-Infrared (NIR) spectrometer operating in wireless mode.
• Employed chemometric analysis, specifically Partial Least Square (PLS) regression, for spectral data processing.
• Developed prediction models using milk samples of diverse origins and compositions.
• Validated the platform by comparing results with chromatographic analysis of market-acquired samples.

Main Results:

• The platform demonstrated the ability to perform rapid and accurate, contactless, on-site milk quality assessment.
• Simultaneous multicomponent analysis provided a comprehensive characterization of milk's chemical composition.
• The system successfully differentiated milk based on fatty acid distribution.
• Validation confirmed the platform's reliability against established chromatographic methods.

Conclusions:

• The developed automated NIR platform offers a novel, efficient, and non-destructive solution for milk quality assessment.
• This technology can significantly aid in preventing food adulteration and ensuring milk integrity.
• The wireless and contactless nature of the platform enhances its applicability for real-time monitoring in various settings.