01843nas a2200193   4500008004100000245015500041210006900196300000800265490000800273520105400281100002101335700002201356700002601378700002601404700001701430700002401447700002001471856015801491       2021                        eng d00aDiscrimination of olive oils based on the olive cultivar origin by machine learning employing the fusion of emission and absorption spectroscopic data0 aDiscrimination of olive oils based on the olive cultivar origin   a1-80 v1303 aIn this work Laser-Induced Breakdown Spectroscopy (LIBS) and absorption spectroscopy aided by machine learning are employed for discriminating some extra virgin Greek olive oils of different olive cultivars for the first
time. LIBS and absorption spectra of extra virgin olive oils belonging to Kolovi and Koroneiki cultivars, as well as mixtures of them, were collected, analyzed, and used to develop classification schemes employing Linear
Discriminant Analysis and Gradient Boosting, the latter allowing the determination of the most important spectral features. Both algorithms were found to provide efficient classification of the olive oil spectra with
accuracies exceeding 90%. Furthermore, for the first time, the emission spectra of LIBS were fused with the absorption spectra to create predictive models and their accuracies were found to be significantly improved. This
work demonstrates the enhanced capabilities of LIBS and absorption spectroscopy and the potential of their combination for olive oil quality monitoring and control.1 aBouras, Christos1 aStefas, Dimitrios1 aGyftokostas, Nikolaos1 aKourelias, Panagiotis1 aNanou, Eleni1 aKokkinos, Vasileios1 aCouris, Stelios  uhttp://telematics.upatras.gr/telematics/publications/discrimination-olive-oils-based-olive-cultivar-origin-machine-learning-employing-fusion-emission-and