Rapid screening for hazelnut oil and high‐oleic sunflower oil in extra virgin olive oil using low‐field nuclear magnetic resonance relaxometry and machine learning
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Study of the adulteration of olive oil with hazelnut oil by on-line coupled high performance liquid chromatographic and gas chromatographic analysis of filbertone
Tocopherol speciation as first screening for the assessment of extra virgin olive oil quality by reversed-phase high-performance liquid chromatography/fluorescence detector
MALDI-TOF mass spectrometry detection of extra-virgin olive oil adulteration with hazelnut oil by analysis of phospholipids using an ionic liquid as matrix and extraction solvent
Detection of Extra Virgin Olive Oil Adulteration with Lampante Olive Oil and Refined Olive Oil Using Nuclear Magnetic Resonance Spectroscopy and Multivariate Statistical Analysis
Potential of low frequency dielectric spectroscopy and machine learning methods for extra virgin olive oils discrimination based on the olive cultivar and ripening stage
Rapid detection of adulteration of olive oil with soybean oil combined with chemometrics by Fourier transform infrared, visible-near-infrared and excitation-emission matrix fluorescence spectroscopy: A comparative study
A classification and identification model of extra virgin olive oil adulterated with other edible oils based on pigment compositions and support vector machine
Physicochemical and sensory induced changes in olive oil (cv ‘Moroccan Picholine’) sourced from various extraction technologies and blended with refined soybean and sunflower oils. A chemometric comparative study
Digital Transformation Through Traceability: Enhancing Fraud Prevention and Economic Sustainability in the Olive Oil Industry
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