The detection of adulterated coconut oil by using different analytical approaches

Adulteration is a fraudulent practice with the intention to cut costs and increase profits. Oils and fats frequently become subjects for food frauds since it does not require much work; the perpetrators just need to replace expensive and high quality oils with cheaper and low quality oils. Since the demand for Virgin Coconut Oils (VCO) in oils and fats market has increased, they are vulnerable to adulteration with other oils and fats. Therefore, it is essential to establish an appropriate method in detecting adulteration in VCO. The attempt to discover the most effective, simple, straight forward and most importantly chemical free method without affecting the sensitivity and specificity is needed. Thus, the objective of this research is to apply four instruments namely Gas Chromatography-Flame Ionization Detector (GC-FID), High Performance Liquid Chromatography (HPLC), Fourier Transform Infrared (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC) to detect palm olein (PO) adulteration in VCO. VCO that has been used in this research was produced by MARDI while PO used was of Buruh brand obtained from local market. In the first phase, different mixture samples (w/w %) containing 5%, 10%, 15%, 20%, 25% and 30% of PO with VCO were prepared. A set of sample containing 100% of VCO was prepared as a positive control and another set containing 100% of PO as negative control. Each sample was subjected to analysis using GC-FID, HPLC, FTIR and DSC. The analysis of fatty acid (FA) and triacylglycerol (TAG) using GC-FID and HPLC were conducted as a quantitative analysis while spectroscopic and thermal analysis by FTIR and DSC as a qualitative analysis. Based on the study, the linear regression of GC-FID demonstrated Y = -2.02E-03C14:0 + 0.19 as the best prediction model for FA. For TAG analysis, POO was assigned as a good predictive model in the prediction of PO in VCO with the equation of Y = 0.00261POO + 0.00486 with R2 value 0.857. Meanwhile, for DSC, the peak temperature was found to have good prediction ability for determination of PO % adulteration in VCO for both curves. For heating curve, the best regression model for peak 1 was temperature parameter with equation of Y = -0.161Temperature + 14.0 and R2 value of 0.993 while for peak 2 onset parameter was the best model with equation of Y = - 0.0847Onset + 17.0 and R2 value of 0.957. As for cooling curve, onset and temperature parameter were again becoming the best prediction model in which Y = -0.102Onset + 5.52 (R2 = 0.953) for peak 1 while Y = -0.253Temperature - 0.771 (R2 = 0.997) for peak 2. Lastly, FTIR spectrum can be used as a potential tool in determination of adulterant in pure oils and fats. It allows one to make a first differentiation among oils and fats because of its capability as fingerprint technique hence making the analysis process much easier. To conclude, the overall analysis showed that all four techniques could be applied in the detection of changes in the compositions and other characteristics of VCO. The findings indicate the potential use of GC-FID, HPLC, FTIR and DSC as reliable tests for PO detection