Independent components analysis applied to 3D-front-face fluorescence spectra of edible oils to study the antioxidant effect of Nigella sativa L. extract on the thermal stability of heated oils

被引:27
作者
Ammari, Faten [1 ,2 ]
Cordella, Christophe B. Y. [1 ]
Boughanmi, Neziha [2 ]
Rutledge, Douglas N. [1 ]
机构
[1] INRA AgroParisTech UMR1145 Genial, Chim Analyt Lab, F-75005 Paris, France
[2] Univ 7 Novembre Carthage, Fac Sci Bizerte Jarzouna 7021, Tunis, Tunisia
关键词
Independent Components Analysis; Durbin Watson statistic; 30-front-face fluorescence spectroscopy; Nigella sativa L; BHT; Corn oil; Thermal stability; NATURAL ANTIOXIDANTS; SPECTROSCOPY; PARAFAC; NUMBER; SIGNAL;
D O I
10.1016/j.chemolab.2011.06.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Independent Components Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to facilitate the analysis of 3D- front face fluorescence spectra and to evaluate the efficiency of Nigella seed extract as a natural antioxidant compared with butylated hydroxytoluene (BHT) during accelerated oxidation of edible vegetable oils at 120 degrees C, 140 degrees C, 170 degrees C and 190 degrees C. ICA has demonstrated its power to extract the most informative signals and thus to allow the interpretation of the differences observed in the corresponding IC scores between Control, BHT-spiked and Nigella-spiked samples. The results of the study clearly indicate that the natural seed extract at a level of 800 ppm exhibited antioxidant effects similar to those of the synthetic antioxidant BHT at a level of 200 ppm and thus contributes to an increase in the oxidative stability of the oil. (c) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:32 / 42
页数:11
相关论文
共 38 条
[1]   Practical aspects of PARAFAC modeling of fluorescence excitation-emission data [J].
Andersen, CM ;
Bro, R .
JOURNAL OF CHEMOMETRICS, 2003, 17 (04) :200-215
[2]   A first application of independent component analysis to extracting structure from stock returns [J].
Back, AD ;
Weigend, AS .
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 1997, 8 (04) :473-484
[3]   Independent component analysis as a pretreatment method for parallel factor analysis to eliminate artefacts from multiway data [J].
Bouveresse, Delphine Jouan-Rimbaud ;
Benabid, Hamida ;
Rutledge, Douglas N. .
ANALYTICA CHIMICA ACTA, 2007, 589 (02) :216-224
[4]   PARAFAC. Tutorial and applications [J].
Bro, R .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1997, 38 (02) :149-171
[5]   Independent component analysis at the neural cocktail party [J].
Brown, GD ;
Yamada, S ;
Sejnowski, TJ .
TRENDS IN NEUROSCIENCES, 2001, 24 (01) :54-63
[6]   High-order contrasts for independent component analysis [J].
Cardoso, JF .
NEURAL COMPUTATION, 1999, 11 (01) :157-192
[7]   A new approach to near-infrared spectral data analysis using independent component analysis [J].
Chen, J ;
Wang, XZ .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2001, 41 (04) :992-1001
[8]   EFFECTS OF ROSEMARY EXTRACTS AND MAJOR CONSTITUENTS ON LIPID OXIDATION AND SOYBEAN LIPOXYGENASE ACTIVITY [J].
CHEN, QY ;
SHI, H ;
HO, CT .
JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY, 1992, 69 (10) :999-1002
[9]   Fluorescence spectroscopy and PARAFAC in the analysis of yogurt [J].
Christensen, J ;
Becker, EM ;
Frederiksen, CS .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2005, 75 (02) :201-208
[10]   Multivariate autofluorescence of intact food systems [J].
Christensen, Jakob ;
Norgaard, Lars ;
Bro, Rasmus ;
Engelsen, Soren Balling .
CHEMICAL REVIEWS, 2006, 106 (06) :1979-1994