Direct determination of polymerised triacylglycerides in deep-frying vegetable oil by near infrared spectroscopy using Partial Least Squares regression

Abstract A green method for the determination of polymerised triacylglyceride (PTG) in deep-frying vegetable oils of different botanic origin has been developed employing near infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression. Four different types of oil were heated during several hours, with and without the addition of foodstuff. NIR transmission spectra were obtained directly from sample aliquots stored in glass vials, thus avoiding the consumption of solvents and minimising waste generation. Variables employed for building the PLS models were selected applying interval PLS (iPLS) as well as Uninformative Variable Elimination-PLS (UVE-PLS). A global PLS model using spectra of all four types of oils was compared to PLS models established for each oil type. Due to the small differences observed in the NIR spectra that can be related to the different botanic origin and results obtained from the PLS model comparison, the use of a global PLS model is recommended leading to prediction errors of 2.28% (w/w) for the determination of PTG in oils employed for frying different kinds of foods.

[1]  Joseph Irudayaraj,et al.  Discriminant analysis of edible oils and fats by FTIR, FT-NIR and FT-Raman spectroscopy , 2005 .

[2]  Nathalie Dupuy,et al.  Automated principal component-based orthogonal signal correction applied to fused near infrared-mid-infrared spectra of French olive oils. , 2009, Analytical chemistry.

[3]  G. Downey,et al.  Detecting and quantifying sunflower oil adulteration in extra virgin olive oils from the eastern mediterranean by visible and near-infrared spectroscopy. , 2002, Journal of agricultural and food chemistry.

[4]  Christopher D. Brown,et al.  Critical factors limiting the interpretation of regression vectors in multivariate calibration , 2009 .

[5]  Paul Geladi,et al.  Principles of Proper Validation: use and abuse of re‐sampling for validation , 2010 .

[6]  A. Hautfenne Standard methods for the analysis of oils, fats and derivatives, 6th Edition. 1st Supplement: Part 5 (1982) Section III, Glycerines. Section IV, Alkaline soaps , 1982 .

[7]  R. Romvári,et al.  Quality alterations of four frying fats during long-term heating (conventional analysis and NIRS calibration). , 2010 .

[8]  Christian Gertz,et al.  Chemical and physical parameters as quality indicators of used frying fats , 2000 .

[9]  Yukihiro Ozaki,et al.  The Detection and Quantification of Adulteration in Olive Oil by Near-Infrared Spectroscopy and Chemometrics , 2004, Analytical sciences : the international journal of the Japan Society for Analytical Chemistry.

[10]  S. Garrigues,et al.  Monitoring of Polymerized Triglycerides in Deep-Frying Oil by On-Line GPC-FTIR Spectrometry Using the Science Based Calibration Multivariate Approach , 2010 .

[11]  S. Garrigues,et al.  New cut-off criterion for uninformative variable elimination in multivariate calibration of near-infrared spectra for the determination of heroin in illicit street drugs. , 2008, Analytica chimica acta.

[12]  N. Dupuy,et al.  Comparison between NIR, MIR, concatenated NIR and MIR analysis and hierarchical PLS model. Application to virgin olive oil analysis. , 2010, Analytica chimica acta.

[13]  M. Dobarganes,et al.  Determination of polar compounds, polymerized and oxidized triacylglycerols, and diacylglycerols in oils and fats: results of collaborative studies and the standardized method (Technical report) , 2000 .

[14]  Roberto Kawakami Harrop Galvão,et al.  NIR spectrometric determination of quality parameters in vegetable oils using iPLS and variable selection , 2008 .

[15]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[16]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[17]  R. Marbach A New Method for Multivariate Calibration , 2005 .

[18]  S. Garrigues,et al.  Direct determination of polymerized triglycerides in deep-frying olive oil by attenuated total reflectance–Fourier transform infrared spectroscopy using partial least squares regression , 2010, Analytical and bioanalytical chemistry.

[19]  Thomas Wenzl,et al.  Chemometrical classification of pumpkin seed oils using UV-Vis, NIR and FTIR spectra. , 2004, Journal of biochemical and biophysical methods.

[20]  R. Romvári,et al.  NIR based quality control of frying fat samples by means of Polar Qualification System , 2010 .

[21]  Miguel de la Guardia,et al.  Vibrational spectroscopy provides a green tool for multi-component analysis , 2010 .

[22]  S. Kehraus,et al.  Application of near infrared spectroscopy (NIRS) in the analysis of frying fats , 2000 .

[23]  Susana Marmesat,et al.  Quality of used frying fats and oils : comparison of rapid tests based on chemical and physical oil properties , 2007 .

[24]  S. Garrigues,et al.  Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy , 2011, Analytical and bioanalytical chemistry.

[25]  J. Kister,et al.  Geographic origins and compositions of virgin olive oils determinated by chemometric analysis of NIR spectra. , 2007, Analytica chimica acta.

[26]  Monica Casale,et al.  The potential of coupling information using three analytical techniques for identifying the geographical origin of Liguria extra virgin olive oil , 2010 .