Fourier transform infrared spectroscopy and chemometrics for chemical property prediction of chemically interesterified lipids with butterfat and vegetable oils during storage

The storage stability of structured lipids has a great importance for food industry and should be defined clearly. The aim of the study is to manufacture structured lipids by chemical interesterification of butter-fat with different vegetable oils, to determine some chemical properties of interesterified lipids through-out storage and to predict free fatty acid, peroxide value, malondialdehyde and mono-di-triacylglycerol contents of these lipids by using middle infrared spectroscopy (FT-MIR). Prediction models were con-structed by using partial least square (PLS) regression with an external cross-validation. The PLS model for TAG with FT-MIR data showed an excellent predictive potential with higher R 2 cal = 0.98, R2 cv= 0.99 and lower RMSE values. The model for monoacylglycerol content (MAG) showed a good predictive ability with higher R 2 cal = 0.88, R2 cv= 0.90 and lower RMSE values. The PLS model constructed with FT-IR spectra for diacylglycerol (DAG) content have good capability of prediction due to higher R 2 and lower RMSE values. For the prediction of malondialdehyde (MAD) of interesterified lipids by FT-MIR spectra, regression co-efficient of calibration set was found as 0.84. For the prediction of peroxide value (PV) of interesterified lipids with FT-MIR spectra, R2 CV= 0.76 and RMSEC = 1.52 and RMSECV = 1.15. Infrared spectroscopy tech-nique could be used for analyzing the chemical changes of fats during storage and also suggests a rapid and non-destructive techniques as good alternatives to the traditional analytical methods.