Literature DB >> 31404874

Laser-based classification of olive oils assisted by machine learning.

Odhisea Gazeli1, Elli Bellou1, Dimitrios Stefas1, Stelios Couris2.   

Abstract

Olive oil is an essential diet component in all Mediterranean countries having a considerable impact on the local economies, which are producing almost 90% of the world production. Therefore, the quality assessment of olive oil in terms of its acidity and its authentication in terms of PDO (Protected Designation of Origin) and PGI (Protected Geographical Indications) characterizations are nowadays necessary and of great importance for the market of olive oil and the related economic activities. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) is used assisted by machine learning algorithms for retrieving of the information contained in the LIBS spectra to provide a simple, reliable, and ultrafast methodology for olive oils classification in terms of the degree of acidity and geographical origin. The combination of LIBS technique with machine learning statistical analysis approaches constitute a very powerful tool for the fast, in-situ and remote quality control of olive oil.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Acidity; Chemometrics; LDA, SVM and RFC algorithmic models; Laser-induced breakdown spectroscopy (LIBS); Olive oil

Mesh:

Substances:

Year:  2019        PMID: 31404874     DOI: 10.1016/j.foodchem.2019.125329

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  4 in total

Review 1.  Integration of Innovative Technologies in the Agri-Food Sector: The Fundamentals and Practical Case of DNA-Based Traceability of Olives from Fruit to Oil.

Authors:  Rayda Ben Ayed; Mohsen Hanana; Sezai Ercisli; Rohini Karunakaran; Ahmed Rebai; Fabienne Moreau
Journal:  Plants (Basel)       Date:  2022-05-02

2.  Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy.

Authors:  Nikolaos Gyftokostas; Eleni Nanou; Dimitrios Stefas; Vasileios Kokkinos; Christos Bouras; Stelios Couris
Journal:  Molecules       Date:  2021-02-25       Impact factor: 4.411

3.  Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination.

Authors:  Nikolaos Gyftokostas; Dimitrios Stefas; Vasileios Kokkinos; Christos Bouras; Stelios Couris
Journal:  Sci Rep       Date:  2021-03-08       Impact factor: 4.379

4.  Distinguishing between Decaffeinated and Regular Coffee by HS-SPME-GC×GC-TOFMS, Chemometrics, and Machine Learning.

Authors:  Yun Zou; Meriem Gaida; Flavio A Franchina; Pierre-Hugues Stefanuto; Jean-François Focant
Journal:  Molecules       Date:  2022-03-10       Impact factor: 4.411

  4 in total

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