Chemometric tools for the authentication of cod liver oil based on nuclear magnetic resonance and infrared spectroscopy data
作者： Editha Giese , Sascha Rohn , Jan Fritsche
DOI: 10.1007/S00216-019-02063-Y
关键词:
摘要: Cod liver oil is a popular dietary supplement marketed as rich source of omega-3 fatty acids well vitamins A and D. Due to its high market price, cod vulnerable adulteration with lower priced vegetable oils. In this study, 1H 13C nuclear magnetic resonance spectroscopy, Fourier transform infrared gas chromatography (coupled flame ionization detector) were used in combination multivariate statistics determine common oils (sunflower canola oils). Artificial neural networks (ANN) able differentiate levels based on spectra detection limit 0.22% root mean square error prediction (RMSEP) 0.86%. ANN models using NMR data yielded limits 3.0% 1.8% RMSEPs 2.7% 1.1%, respectively. comparison, the model acid profiles determined by achieved 0.81% an RMSEP 1.1%. The approach spectroscopic techniques can be regarded promising tool for authentication may pave way holistic quality assessment fish Graphical abstract.
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Amin Ismail, Yaakob Che Man, Abdul Rohman, Puziah Hashim, FTIR spectroscopy combined with multivariate calibration for analysis of cod liver oil in binary mixture with corn oil Faculty of Food Science and Technology, Universiti Putra Malaysia. ,(2011)
N. A. Marigheto, E. K. Kemsley, M. Defernez, R. H. Wilson, A comparison of mid-infrared and raman spectroscopies for the authentication of edible oils Journal of the American Oil Chemists' Society. ,vol. 75, pp. 987- 992 ,(1998) , 10.1007/S11746-998-0276-4
B. Tangendjaja, Quality control of feed ingredients for aquaculture Feed and Feeding Practices in Aquaculture. pp. 141- 169 ,(2015) , 10.1016/B978-0-08-100506-4.00006-4
James Franklin, The elements of statistical learning : data mining, inference,and prediction The Mathematical Intelligencer. ,vol. 27, pp. 83- 85 ,(2005) , 10.1007/BF02985802
Diego L. García-González, Luisa Mannina, Marco D’Imperio, Anna Laura Segre, Ramón Aparicio, Using 1H and 13C NMR techniques and artificial neural networks to detect the adulteration of olive oil with hazelnut oil European Food Research and Technology. ,vol. 219, pp. 545- 548 ,(2004) , 10.1007/S00217-004-0996-0
Cleiton A. Nunes, Vibrational spectroscopy and chemometrics to assess authenticity, adulteration and intrinsic quality parameters of edible oils and fats Food Research International. ,vol. 60, pp. 255- 261 ,(2014) , 10.1016/J.FOODRES.2013.08.041
F.D. Gunstone, High resolution NMR studies of fish oils Chemistry and Physics of Lipids. ,vol. 59, pp. 83- 89 ,(1991) , 10.1016/0009-3084(91)90066-K
Ying-Xu Zeng, Pedro Araujo, Zhen-Yu Du, Thu-Thao Nguyen, Livar Frøyland, Bjørn Grung, Elucidation of triacylglycerols in cod liver oil by liquid chromatography electrospray tandem ion-trap mass spectrometry. Talanta. ,vol. 82, pp. 1261- 1270 ,(2010) , 10.1016/J.TALANTA.2010.06.055
Mário César Ugulino Araújo, Teresa Cristina Bezerra Saldanha, Roberto Kawakami Harrop Galvão, Takashi Yoneyama, Henrique Caldas Chame, Valeria Visani, The successive projections algorithm for variable selection in spectroscopic multicomponent analysis Chemometrics and Intelligent Laboratory Systems. ,vol. 57, pp. 65- 73 ,(2001) , 10.1016/S0169-7439(01)00119-8
Guihua Fang, Jing Yeen Goh, Manjun Tay, Hiu Fung Lau, Sam Fong Yau Li, Characterization of oils and fats by 1H NMR and GC/MS fingerprinting: classification, prediction and detection of adulteration. Food Chemistry. ,vol. 138, pp. 1461- 1469 ,(2013) , 10.1016/J.FOODCHEM.2012.09.136