Expeditious and accurate detection of palm oil adulteration in virgin coconut oil by utilizing ATR-FTIR spectroscopy along with chemometrics and regression models

Abstract

Virgin coconut oil (VCO), being one of the most treasured and healthy edible oil, is at great risk of blending with cheaper oils like palm oil (PO). Fourier transform infrared (FTIR) spectroscopy with an Attenuated total reflection (ATR) accessory was used together with multivariate chemometrics for the classification and evaluation of numerous concentrations of PO (0.5–30% v/v) in VCO. Linear Discriminant Analysis (LDA) showed a 100% correct classification for both the initial and cross-validation groups for all the subsets of PO blends. Principal components regression (PCR) and Partial least squares regression (PLS-R) calibration models were generated and compared for normal, 1st, and 2nd derivatives of the combined informational spectral domain (3010–2800 cm−1 & 1800–700 cm−1) and separate informational domains of the spectra 3010–2800 cm−1 and 1800–700 cm−1 to get the best-fitting models. Regression models for the 2nd derivatives of 1800–700 cm−1 informational spectral domain gave exquisite outcomes of prediction with immense accuracy and precision with the highest R2 of 0.998, and the root mean square error of prediction (RMSEP) of 0.375% v/v for PLS-R and R2 of 0.998 and RMSEP of 0.441% v/v for PCR respectively. The lowest detectable limit of PO in VCO was estimated as 0.5% v/v. Hence, it has been concluded that PO adulteration of up to 0.5% with VCO can be quickly determined by using ATR-FTIR spectroscopy fitted with multivariate chemometrics.

Keywords

• ATR-FTIR spectroscopy
• Virgin coconut oil
• Palm oil
• Adulteration
• Detection
• Multivariate chemometrics