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Chemometric analysis of combined NIR and MIR spectra to characterize French olives
Author(s) -
Dupuy Nathalie,
Galtier Oswin,
Le Dréau Yveline,
Pinatel Christian,
Kister Jacky,
Artaud Jacques
Publication year - 2010
Publication title -
european journal of lipid science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 94
eISSN - 1438-9312
pISSN - 1438-7697
DOI - 10.1002/ejlt.200900198
Subject(s) - partial least squares regression , olive oil , cultivar , chemometrics , principal component analysis , near infrared spectroscopy , linear discriminant analysis , mathematics , chemistry , horticulture , food science , biology , statistics , chromatography , neuroscience
Chemometric treatment of near‐infrared (NIR) and mid‐infrared (MIR) combined spectra was used firstly to predict oil and water contents in fresh olive fruit samples ( n = 223) and secondly to classify these samples into five principal French cultivar origins (Aglandau, Cailletier, Olivière, Salonenque, and Tanche). The study was carried out during four crop years (2005/2006 to 2008/2009) to take into account the seasonal variations. The comparison of the results obtained in the combined range (REP = 2.6% for the water content and 3.5% for the oil content) provides an obvious advantage compared to the NIR and MIR techniques used separately. Fresh olive fruit cultivars were satisfactorily classified with the partial least squares‐discriminant analysis (PLS‐DA) method in the combined range. After use of the K ‐means clustering on the PLS‐DA scores, all the samples were well classified into their five groups of origin. The use of infrared combined spectra allows a considerable improvement in estimating olive fruit quality (oil and water contents, varietal origins).