A Computational Procedure in Detecting Adulterated Oleochemical Products

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...

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Autores principales:	Gian Paolo O. Bernardo, Michael Angelo B. Promentilla
Formato:	article
Lenguaje:	EN
Publicado:	AIDIC Servizi S.r.l. 2021
Materias:	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/5fbb2f804e614e8893c2f2645f62fc00
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spelling	oai:doaj.org-article:5fbb2f804e614e8893c2f2645f62fc002021-11-15T21:47:40ZA Computational Procedure in Detecting Adulterated Oleochemical Products10.3303/CET21881352283-9216https://doaj.org/article/5fbb2f804e614e8893c2f2645f62fc002021-11-01T00:00:00Zhttps://www.cetjournal.it/index.php/cet/article/view/11928https://doaj.org/toc/2283-9216Vegetable 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.Gian Paolo O. BernardoMichael Angelo B. PromentillaAIDIC Servizi S.r.l.articleChemical engineeringTP155-156Computer engineering. Computer hardwareTK7885-7895ENChemical Engineering Transactions, Vol 88 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
spellingShingle	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895 Gian Paolo O. Bernardo Michael Angelo B. Promentilla A Computational Procedure in Detecting Adulterated Oleochemical Products
description	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.
format	article
author	Gian Paolo O. Bernardo Michael Angelo B. Promentilla
author_facet	Gian Paolo O. Bernardo Michael Angelo B. Promentilla
author_sort	Gian Paolo O. Bernardo
title	A Computational Procedure in Detecting Adulterated Oleochemical Products
title_short	A Computational Procedure in Detecting Adulterated Oleochemical Products
title_full	A Computational Procedure in Detecting Adulterated Oleochemical Products
title_fullStr	A Computational Procedure in Detecting Adulterated Oleochemical Products
title_full_unstemmed	A Computational Procedure in Detecting Adulterated Oleochemical Products
title_sort	computational procedure in detecting adulterated oleochemical products
publisher	AIDIC Servizi S.r.l.
publishDate	2021
url	https://doaj.org/article/5fbb2f804e614e8893c2f2645f62fc00
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A Computational Procedure in Detecting Adulterated Oleochemical Products

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