ArticleJournal of analytical methods in chemistry2020
Rapid Analytical Method to Characterize the Freshness of Olive Oils Using Fluorescence Spectroscopy and Chemometric Algorithms.
Article in Journal of analytical methods in chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 34 citations in OpenAlex.
- Investigating the effect of changing the substrate material analyzed by laser-induced breakdown spectroscopy on the antenna performance.Scientific reports · 2024Article
- Vegetable and fruit freshness detection based on deep features and principal component analysis.Current research in food science · 2024Article
- Nanotechnology and E-Sensing for Food Chain Quality and Safety.Sensors (Basel, Switzerland) · 2023Review
- Post-heating Fluorescence-based Alteration and Adulteration Detection of Extra Virgin Olive Oil.Journal of fluorescence · 2023Article
- The effect of data fusion on improving the accuracy of olive oil quality measurement.Food chemistry: X · 2023Article
- Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques.Foods (Basel, Switzerland) · 2021Article
- Chemometric Analysis of UV-Visible Spectral Fingerprints for the Discrimination and Quantification of Clinical Anthracycline Drug Preparation Used in Oncology.BioMed research international · 2021Article
- Near UV-Vis and NMR Spectroscopic Methods for Rapid Screening of Antioxidant Molecules in Extra-Virgin Olive Oil.Antioxidants (Basel, Switzerland) · 2020Article
- Development of Fast Analytical Method for the Detection and Quantification of Honey Adulteration Using Vibrational Spectroscopy and Chemometrics Tools.Journal of analytical methods in chemistry · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the most important issues in the field of quality assurance of olive oils is the detection of the freshness of olive oil. In this study, 400 nm laser-induced fluorescence spectroscopy was used with supervised and unsupervised multivariate analysis methods to develop a rapid method able to discriminate between freshly produced olive oils and oil that has been stored for a period of time ranging from 12 to 24 months. The fluorescence spectral data were firstly processed by the PCA. This method shows strong discrimination of the three oil classes using the first three components which present 96% of the total variability of the initial data, and then supervised classification models were constructed using the discriminant partial least square regression PLS-DA, support vector machine SVM, and linear discriminant analysis LDA. These methods show a high capacity in the classification of the three classes of olive oil. The validation of these classification models by external samples shows a high capacity of classification of the samples in their class with an accuracy of 100%. This study demonstrated the feasibility of the fluorescence spectroscopy fingerprint (routine technique) for the classification of olive oils according to their freshness and storage time.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.