ArticleNPJ science of food2022
Novel time-domain NMR-based traits for rapid, label-free Olive oils profiling.
Article in NPJ science of food, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Manifold-based learning for high-throughput single-peanut phenotyping.NPJ systems biology and applications · 2026Article
- Unveiling key peak features for olive oil authentication utilizing Raman spectroscopy and chemometrics.NPJ science of food · 2026Article
- The Journey of Artificial Intelligence in Food Authentication: From Label Attribute to Fraud Detection.Foods (Basel, Switzerland) · 2025Review
- Time-domain nuclear magnetic resonance for serum analysis.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2024Article
- Nutritional load in post-prandial oxidative stress and the pathogeneses of diabetes mellitus.NPJ science of food · 2024Article
- Semi-Autonomic AI LF-NMR Sensor for Industrial Prediction of Edible Oil Oxidation Status.Sensors (Basel, Switzerland) · 2023Article
- A Brief Review on Medicinal Plants-At-Arms against COVID-19.Interdisciplinary perspectives on infectious diseases · 2023Review
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Authors and funding
9 authors.
Funding
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Abstract
Olive oil is one of the oldest and essential edible oils in the market. The classification of olive oils (e.g. extra virgin, virgin, refined) is often influenced by factors ranging from its complex inherent physiochemical properties (e.g. fatty acid profiles) to the undisclosed manufacturing processes. Therefore, olive oils have been the target of adulteration due to its profitable margin. In this work, we demonstrate that multi-parametric time-domain NMR relaxometry can be used to rapidly (in minutes) identify and classify olive oils in label-free and non-destructive manner. The subtle differences in molecular microenvironment of the olive oils induce substantial changes in the relaxation mechanism in the time-domain NMR regime. We demonstrated that the proposed NMR-relaxation based detection (AUC = 0.95) is far more sensitive and specific than the current gold-standards in the field i.e. near-infrared spectroscopy (AUC = 0.84) and Ultraviolet-visible spectroscopy (AUC = 0.73), respectively. We further show that, albeit the inherent complexity of olive plant natural phenotypic variations, the proposed NMR-relaxation based traits may be a viable mean (AUC = 0.71) in tracing the regions of origin for olive trees, in agreement with their geographical orientation.
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Registered trials
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