Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils
The intake of adulterated and unhealthy oils and trans-fats in the human diet has had negative health repercussions, including cardiovascular disease, causing millions of deaths annually. Sadly, a significant percentage of all consumable products including edible oils are neither screened nor monito...
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doaj-291869b80bd84d50954fd65bf5b5a58d2020-11-24T23:11:34ZengMDPI AGFoods2304-81582018-07-017812210.3390/foods7080122foods7080122Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) OilsShayla C. Smithson0Boluwatife D. Fakayode1Siera Henderson2John Nguyen3Sayo O. Fakayode4Department of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USADepartment of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USADepartment of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USADepartment of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USADepartment of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USAThe intake of adulterated and unhealthy oils and trans-fats in the human diet has had negative health repercussions, including cardiovascular disease, causing millions of deaths annually. Sadly, a significant percentage of all consumable products including edible oils are neither screened nor monitored for quality control for various reasons. The prospective intake of adulterated oils and the associated health impacts on consumers is a significant public health safety concern, necessitating the need for quality assurance checks of edible oils. This study reports a simple, fast, sensitive, accurate, and low-cost chemometric approach to the purity analysis of highly refined peanut oils (HRPO) that were adulterated either with vegetable oil (VO), canola oil (CO), or almond oil (AO) for food quality assurance purposes. The Fourier transform infrared spectra of the pure oils and adulterated HRPO samples were measured and subjected to a partial-least-square (PLS) regression analysis. The obtained PLS regression figures-of-merit were incredible, with remarkable linearity (R2 = 0.994191 or better). The results of the score plots of the PLS regressions illustrate pattern recognition of the adulterated HRPO samples. Importantly, the PLS regressions accurately determined percent compositions of adulterated HRPOs, with an overall root-mean-square-relative-percent-error of 5.53% and a limit-of-detection as low as 0.02% (wt/wt). The developed PLS regressions continued to predict the compositions of newly prepared adulterated HRPOs over a period of two months, with incredible accuracy without the need for re-calibration. The accuracy, sensitivity, and robustness of the protocol make it desirable and potentially adoptable by health departments and local enforcement agencies for fast screening and quality assurance of consumable products.http://www.mdpi.com/2304-8158/7/8/122peanut-oilfood-analysispeanut-oil-adulterationinfrared-spectroscopypartial-least-regression-analysisfood-quality-assurance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shayla C. Smithson Boluwatife D. Fakayode Siera Henderson John Nguyen Sayo O. Fakayode |
spellingShingle |
Shayla C. Smithson Boluwatife D. Fakayode Siera Henderson John Nguyen Sayo O. Fakayode Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils Foods peanut-oil food-analysis peanut-oil-adulteration infrared-spectroscopy partial-least-regression-analysis food-quality-assurance |
author_facet |
Shayla C. Smithson Boluwatife D. Fakayode Siera Henderson John Nguyen Sayo O. Fakayode |
author_sort |
Shayla C. Smithson |
title |
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils |
title_short |
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils |
title_full |
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils |
title_fullStr |
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils |
title_full_unstemmed |
Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils |
title_sort |
detection, purity analysis, and quality assurance of adulterated peanut (arachis hypogaea) oils |
publisher |
MDPI AG |
series |
Foods |
issn |
2304-8158 |
publishDate |
2018-07-01 |
description |
The intake of adulterated and unhealthy oils and trans-fats in the human diet has had negative health repercussions, including cardiovascular disease, causing millions of deaths annually. Sadly, a significant percentage of all consumable products including edible oils are neither screened nor monitored for quality control for various reasons. The prospective intake of adulterated oils and the associated health impacts on consumers is a significant public health safety concern, necessitating the need for quality assurance checks of edible oils. This study reports a simple, fast, sensitive, accurate, and low-cost chemometric approach to the purity analysis of highly refined peanut oils (HRPO) that were adulterated either with vegetable oil (VO), canola oil (CO), or almond oil (AO) for food quality assurance purposes. The Fourier transform infrared spectra of the pure oils and adulterated HRPO samples were measured and subjected to a partial-least-square (PLS) regression analysis. The obtained PLS regression figures-of-merit were incredible, with remarkable linearity (R2 = 0.994191 or better). The results of the score plots of the PLS regressions illustrate pattern recognition of the adulterated HRPO samples. Importantly, the PLS regressions accurately determined percent compositions of adulterated HRPOs, with an overall root-mean-square-relative-percent-error of 5.53% and a limit-of-detection as low as 0.02% (wt/wt). The developed PLS regressions continued to predict the compositions of newly prepared adulterated HRPOs over a period of two months, with incredible accuracy without the need for re-calibration. The accuracy, sensitivity, and robustness of the protocol make it desirable and potentially adoptable by health departments and local enforcement agencies for fast screening and quality assurance of consumable products. |
topic |
peanut-oil food-analysis peanut-oil-adulteration infrared-spectroscopy partial-least-regression-analysis food-quality-assurance |
url |
http://www.mdpi.com/2304-8158/7/8/122 |
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