Rapid Monitoring and Quantification of Primary and Secondary Oxidative Markers in Edible Oils During Deep Frying...

Oxidative degradation during deep frying negatively affects the nutritional quality and stability of edible oils. Rapid, non-destructive methods to monitor oxidation, particularly in antioxidant-enriched oils, are therefore of growing interest.

This study investigates the potential of near-infrared (NIR) spectroscopy combined with chemometric modeling-specifically the Stepwise Decorrelation of Variables (SELECT) algorithm and Ordinary Least Squares (OLS) regression-to quantitatively assess oxidation dynamics in edible oils enriched with hydroxytyrosol extract from olive fruit during deep frying. Extra virgin olive oil, virgin olive oil, refined olive oil, refined sunflower oil, and high-oleic sunflower oil were evaluated under controlled thermal degradation conditions.

Variable selection identified key NIR spectral regions related to acidity, conjugated dienes (K₂₃₂), secondary oxidation indices (K₂₇₀ and ΔK), peroxide value (PV), anisidine value (AnV), and the total oxidation (TOTOX) index. From 700 measured wavelengths, a limited number were sufficient for robust prediction (16-30 wavelengths depending on the parameter), with critical sensitivity observed around 1792 nm and 1392 nm. The optimized NIR-SELECT-OLS models showed strong predictive performance across oil types (R² > 0.90; explained variance > 85%).

The results demonstrate that hydroxytyrosol enrichment enhances the oxidative and nutritional stability of edible oils during deep frying. Moreover, the integration of NIR spectroscopy with chemometric modeling provides an effective, non-destructive tool for real-time monitoring of oil oxidation, supporting sustainable quality control, process optimization, and antioxidant fortification in functional edible oils.