Linking phenolic composition, cultivar and ripening stage to oxidative stability and shelf-life prediction of EVOO using accelerated aging and NIR-based chemometrics modeling
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Published on: October 5, 2016
Taha Mehany1, José M González-Sáiz1, Consuelo Pizarro1
1Department of Chemistry, University of La Rioja, Logroño, 26006, Spain.
Abstract:
The reliable prediction of extra virgin olive oil (EVOO) shelf-life remains a challenge for producers and regulators. This study proposes an approach combining accelerated aging with near-infrared (NIR) spectroscopy and feature selection to monitor physicochemical and sensory stability. A total of 132 samples from Arbequina, Manzanilla, Hojiblanca, Picual, and Picudo cultivars, harvested at two ripening stages and classified by phenolic content, were stored under accelerated (40 °C, 12 h/day light) and ambient conditions for up to 12 months. Physicochemical, sensory, and spectral data were analyzed using stepwise variable selection (SELECT) and ordinary least squares (OLS) regression. The models showed high predictive performance for free acidity (R2 = 0.97), peroxide value (R2 = 0.95), rancidity (R2 = 0.94), and fruitiness (R2 = 0.96). Phenolic-rich oils, particularly early-harvest Picual and Picudo, exhibited greater oxidative stability. The results demonstrate that accelerated aging combined with NIR-based modeling enables rapid, non-destructive, cultivar-specific shelf-life prediction.
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