Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Feasibility Assessment of Synchronous Fluorescence Spectral Fusion by Application to Argan Oil for Adulteration Analysis
Δημιουργός/Συγγραφέας:	Stokes T.D. Foteini M. Brownfield B. Kalivas J.H. [EL] Μούσδης, Γεώργιος Α.[EN] Mousdis, George A. Amine A. Georgiou C.
Εκδότης:	SAGE Publications Inc.
Ημερομηνία:	2018
Γλώσσα:	Αγγλικά
ISSN:	0003-7028
DOI:	10.1177/0003702817749232
Άλλο:	PubMed ID: 29199851
Περίληψη:	Synchronous fluorescence spectroscopy (SFS) is used for quantitative analysis as well as for qualitative analysis, such as with classification methods. With SFS, determination of a useful wavelength interval between the excitation and emission wavelengths (Δλ) is required. There are a multitude of Δλ intervals that can be evaluated and optimization of the best one is complex. Presented here is a fusion approach for combining Δλ intervals, thereby negating the need to perform the selection by a skilled operator. To demonstrate the feasibility of omitting selection of the best Δλ interval, adulterated argan oil samples are studied. Argan oil is made from the argan tree, endemic to southwestern Morocco, and is well-known for its cosmetic, pharmaceutical, and nutritional applications. It is considered a luxury product and exported from Morocco around the world. Consequently, detection of argan oil adulteration followed by quantitative analysis of the adulterant concentration is important. This study uses fusion of SFS spectra obtained at ten Δλ intervals to first detect adulteration of argan oil by corn oil and then determination of the corn oil content. For detection of adulteration, 15 one-class classification methods were used simultaneously over the ten Δλ sets of SFS spectra. For tuning parameter dependent classifiers such as Mahalanobis distance, non-optimized classifiers are used. Raw classification values are used, removing the need to set classifier-dependent threshold values, albeit, ultimately, a fusion decision rule is needed for classification. For quantitative analysis, two calibration approaches are evaluated with fusion of these ten Δλ SFS spectral data sets. One is multivariate calibration by partial least squares (PLS). The second approach is a univariate calibration process where the SFS spectra are summed over respective SFS spectral ranges, also known as the area under the curve (AUC). For adulteration detection and quantitation of the corn oil, prediction errors decrease with fusion compared to individually using the ten Δλ interval SFS specific data sets. For this argan oil data set, the AUC method generally provides equivalent prediction errors to PLS.
Τίτλος πηγής δημοσίευσης:	Applied Spectroscopy
Τόμος/Κεφάλαιο:	72
Τεύχος:	3
Σελίδες:	432-441
Θεματική Κατηγορία:	[EL] Φυσική και θεωρητική χημεία[EN] Physical and theoretical chemistry [EL] Φασματοσκοπία[EN] Spectroscopy
Λέξεις-Κλειδιά:	adulteration area under the curve argan oil Fusion multivariate calibration SFS synchronous fluorescence spectroscopy
Αξιολόγηση από ομότιμους (peer reviewed):	Ναι
Κάτοχος πνευματικών δικαιωμάτων:	© The Author(s) 2018.
Όροι και προϋποθέσεις δικαιωμάτων:	All Open Access, Bronze
Σημειώσεις:	National Science Foundation; Idaho State University; Agricultural University of Athens This material is based upon work supported by the National Science Foundation under Grant No. CHE-1506417 (co-funded by CDS&E) and is gratefully acknowledged by the authors.
Εμφανίζεται στις συλλογές:	Ινστιτούτο Θεωρητικής και Φυσικής Χημείας (ΙΘΦΧ) - Επιστημονικό έργο