A Computational Procedure in Detecting Adulterated Oleochemical Products

Abstract

Vegetable oils can be used as feedstock for the production of a large class of oleochemical products. Unfortunately, price disparities among different kinds of vegetables oils provide an incentive for adulteration by using cheaper substitutes while still claiming otherwise. In this paper, a chemical forensics method for detecting whether or not such an adulteration has been committed is proposed and demonstrated in two case studies, each involving a batch of soap products supposedly produced using 100 % coconut oil and from 75 % coconut oil with 25 % palm oil. The concentration profiles of the fatty acids from soap samples were cross-referenced against known fatty acid concentration fingerprints for coconut oil and for palm oil from the Lipid Handbook through a linear programming model. Executing the model on the sample concentration profiles yielded the back-calculated concentrations of coconut oil and of palm oil used as feedstock with excellent agreement in both cases. The confirmation exhibited in these hypothetical case studies indicates that the procedure can be used in detecting adulteration in other oleochemical products of similar nature, and that the model can be used as a basis in the development of other adulteration detection methods.