ArticleFoods (Basel, Switzerland)2021
Rapid Identification of Adulteration in Edible Vegetable Oils Based on Low-Field Nuclear Magnetic Resonance Relaxation Fingerprints.
Article in Foods (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Adulteration Detection and Quantification in Olive Oil Using Excitation-Emission Matrix Fluorescence Spectroscopy and Chemometrics.Journal of fluorescence · 2025Article
- Identification of Maize Kernel Varieties Using LF-NMR Combined with Image Data: An Explainable Approach Based on Machine Learning.Plants (Basel, Switzerland) · 2024Article
- Design & development of adulteration detection system by fumigation method & machine learning techniques.Scientific reports · 2024Article
- Reverse design of haptens based on antigen spatial conformation to prepare anti-capsaicinoids&gingerols antibodies for monitoring of gutter cooking oil.Food chemistry: X · 2024Article
- Adulteration in edible oil (mustard oil) and ghee; detection and their effects on human health.International journal of biochemistry and molecular biology · 2024Review
- Development of an Innovative Optoelectronic Nose for Detecting Adulteration in Quince Seed Oil.Foods (Basel, Switzerland) · 2023Article
- Comparing Different Chemometric Approaches to Detect Adulteration of Cold-Pressed Flaxseed Oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry.Foods (Basel, Switzerland) · 2023Article
- Aromatic Fingerprints: VOC Analysis with E-Nose and GC-MS for Rapid Detection of Adulteration in Sesame Oil.Sensors (Basel, Switzerland) · 2023Article
- A simple and rapid homogeneous fluorescence polarization immunoassay for rapid identification of gutter cooking oil by detecting capsaicinoids.Analytical and bioanalytical chemistry · 2022Article
- Rapid Detection of Avocado Oil Adulteration Using Low-Field Nuclear Magnetic Resonance.Foods (Basel, Switzerland) · 2022Article
- Quantitative Detection of Extra Virgin Olive Oil Adulteration, as Opposed to Peanut and Soybean Oil, Employing LED-Induced Fluorescence Spectroscopy.Sensors (Basel, Switzerland) · 2022Article
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9 authors.
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Abstract
Most current approaches applied for the essential identification of adulteration in edible vegetable oils are of limited practical benefit because they require long analysis times, professional training, and costly instrumentation. The present work addresses this issue by developing a novel simple, accurate, and rapid identification approach based on the magnetic resonance relaxation fingerprints obtained from low-field nuclear magnetic resonance spectroscopy measurements of edible vegetable oils. The relaxation fingerprints obtained for six types of edible vegetable oil, including flaxseed oil, olive oil, soybean oil, corn oil, peanut oil, and sunflower oil, are demonstrated to have sufficiently unique characteristics to enable the identification of the individual types of oil in a sample. By using principal component analysis, three characteristic regions in the fingerprints were screened out to create a novel three-dimensional characteristic coordination system for oil discrimination and adulteration identification. Univariate analysis and partial least squares regression were used to successfully quantify the oil adulteration in adulterated binary oil samples, indicating the great potential of the present approach on both identification and quantification of edible oil adulteration.
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