Geographical Characterization of Greek Virgin Olive Oils (Cv. Koroneiki) Using1H and31P NMR Fingerprinting with Canonical Discriminant Analysis and Classification Binary Trees

2008 ◽  
Vol 56 (9) ◽  
pp. 3200-3207 ◽  
Author(s):  
Panos V. Petrakis ◽  
Alexia Agiomyrgianaki ◽  
Stella Christophoridou ◽  
Apostolos Spyros ◽  
Photis Dais
2013 ◽  
Vol 54 (2) ◽  
pp. 1959-1964 ◽  
Author(s):  
Ibrahim M. Abu-Reidah ◽  
Majed Yasin ◽  
Stefania Urbani ◽  
Maurizio Servili ◽  
Gianfrancesco Montedoro

2018 ◽  
Vol 119 ◽  
pp. 73-85 ◽  
Author(s):  
Patricia Reboredo-Rodríguez ◽  
Carmen González-Barreiro ◽  
Beatriz Cancho-Grande ◽  
Tamara Y. Forbes-Hernández ◽  
Massimiliano Gasparrini ◽  
...  

2014 ◽  
Vol 7 (10) ◽  
pp. 2122-2136 ◽  
Author(s):  
María de los Angeles Fernandez ◽  
Mariela Assof ◽  
Viviana Jofre ◽  
María Fernanda Silva

2017 ◽  
Vol 32 (4) ◽  
pp. 294-304 ◽  
Author(s):  
Brígida Jiménez ◽  
Ana Rivas ◽  
María Luisa Lorenzo ◽  
Araceli Sánchez-Ortiz

2003 ◽  
Vol 57 (2) ◽  
pp. 158-163 ◽  
Author(s):  
Gerard Downey ◽  
Peter McIntyre ◽  
Antony N. Davies

Visible and near-infrared reflectance spectra have been examined for their ability to classify extra virgin olive oils from the eastern Mediterranean on the basis of their geographic origin. Classification strategies investigated were partial least-squares regression, factorial discriminant analysis, and k-nearest neighbors analysis. Discriminant models were developed and evaluated using spectral data in the visible (400–750 nm), near-infrared (1100–2498 nm), and combined (400–2498 nm) wavelength ranges. A variety of data pretreatments was applied. Best results were obtained using factorial discriminant analysis on raw spectral data over the combined wavelength range; a correct classification rate of 93.9% was obtained on a prediction sample set. Though the overall sample set was limited in numbers, these results demonstrate the potential of near-infrared spectroscopy to classify extra virgin olive oils on the basis of their geographic origin.


2016 ◽  
Vol 89 ◽  
pp. 1123-1133 ◽  
Author(s):  
Firdousse Laincer ◽  
Nunzia Iaccarino ◽  
Jussara Amato ◽  
Bruno Pagano ◽  
Alessia Pagano ◽  
...  
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