Shelf-life prediction of processed milk by solid-phase microextraction, mass spectrometry, and multivariate analysis

Area of Science:

• Analytical Chemistry
• Food Science
• Microbiology

Background:

• Accurate shelf-life prediction is crucial for maintaining milk quality and safety.
• Traditional methods for assessing milk spoilage can be time-consuming and labor-intensive.
• Volatile compounds produced by microbial activity offer potential indicators of milk spoilage.

Purpose of the Study:

• To develop and validate a rapid analytical method for predicting the shelf life of milk.
• To assess the capability of the SPME-MS-MVA technique in differentiating between microbial spoilage and non-microbial contamination.
• To evaluate the method's effectiveness for both reduced-fat and whole-fat chocolate milk.

Main Methods:

• Solid-phase microextraction (SPME) using Carboxen-PDMS fiber for volatile metabolite extraction from milk.
• Gas chromatography-mass spectrometry (GC-MS) for analyzing volatile compounds.
• Multivariate analysis (MVA), including partial least-squares regression and principal component analysis, for data interpretation.

Main Results:

• The SPME-MS-MVA technique accurately predicted milk shelf life with correlation coefficients greater than 0.98 (±1 day accuracy).
• The method successfully classified milk samples spoiled by microbial activity.
• Principal component analysis effectively distinguished between samples with microbial spoilage and those contaminated by non-microbial sources like copper and sanitizer.

Conclusions:

• SPME-MS-MVA serves as a powerful, rapid, and accurate tool for predicting milk shelf life.
• This mass spectrometry-based electronic-nose approach can identify spoilage and contamination, aiding in quality control.
• The technique holds promise for routine application in the dairy industry to ensure product safety and quality.