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Open AccessArticle

Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils

Department of Physical Sciences, University of Arkansas Fort Smith, 5210 Grand Avenue, P.O. Box 3649, Fort Smith, AR 72913-3649, USA
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Foods 2018, 7(8), 122; https://doi.org/10.3390/foods7080122
Received: 16 June 2018 / Revised: 25 July 2018 / Accepted: 27 July 2018 / Published: 31 July 2018
(This article belongs to the Special Issue Food Legumes: Physicochemical and Nutritional Properties)
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. View Full-Text
Keywords: peanut-oil; food-analysis; peanut-oil-adulteration; infrared-spectroscopy; partial-least-regression-analysis; food-quality-assurance peanut-oil; food-analysis; peanut-oil-adulteration; infrared-spectroscopy; partial-least-regression-analysis; food-quality-assurance
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MDPI and ACS Style

Smithson, S.C.; Fakayode, B.D.; Henderson, S.; Nguyen, J.; Fakayode, S.O. Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils. Foods 2018, 7, 122.

AMA Style

Smithson SC, Fakayode BD, Henderson S, Nguyen J, Fakayode SO. Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils. Foods. 2018; 7(8):122.

Chicago/Turabian Style

Smithson, Shayla C.; Fakayode, Boluwatife D.; Henderson, Siera; Nguyen, John; Fakayode, Sayo O. 2018. "Detection, Purity Analysis, and Quality Assurance of Adulterated Peanut (Arachis hypogaea) Oils" Foods 7, no. 8: 122.

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