Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques

Abstract The production of trans‐fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D‐optimal mixture design,...

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Autores principales:	Muhammad Haseeb Ahmad, Zainab Shahbaz, Muhammad Imran, Muhammad Kamran Khan, Niaz Muhammad, Sanaullah Iqbal, Waqas Ahmed, Tanvir Ahmad
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	canola D‐optimal design fourier transform infrared partial least square regression principal components analysis Nutrition. Foods and food supply TX341-641
Acceso en línea:	https://doaj.org/article/be5f18622d444fc786be0ac0b59dc2a3
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spelling	oai:doaj.org-article:be5f18622d444fc786be0ac0b59dc2a32021-11-04T13:06:43ZMonitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques2048-717710.1002/fsn3.2558https://doaj.org/article/be5f18622d444fc786be0ac0b59dc2a32021-11-01T00:00:00Zhttps://doi.org/10.1002/fsn3.2558https://doaj.org/toc/2048-7177Abstract The production of trans‐fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D‐optimal mixture design, and the best formulation (67:22:11) based on free fatty acid (FFA) content, peroxide value (PV), and iodine value (IV) as responses was selected for multiple frying process. The data on FFA, PV, and IV along with Fourier transform‐infrared (FT‐IR) spectra were taken after each frying up to ten frying. The spectral data were preprocessed with standard normal variate followed by principal component analysis which is clearly showing the differentiation for various frying. Similarly, partial least square regression was applied to predict the FFA (0.37%–1.63%), PV (4.47–13.85 meqO2/kg), and IV (111.51–51.39 I2/100 g) which demonstrated high coefficient of determination (R2) 0.84, 0.83, and 0.81, respectively. It can be summarized that FT‐IR can be used as a novel tool for fast and noninvasive quality determination of frying oils.Muhammad Haseeb AhmadZainab ShahbazMuhammad ImranMuhammad Kamran KhanNiaz MuhammadSanaullah IqbalWaqas AhmedTanvir AhmadWileyarticlecanolaD‐optimal designfourier transform infraredpartial least square regressionprincipal components analysisNutrition. Foods and food supplyTX341-641ENFood Science & Nutrition, Vol 9, Iss 11, Pp 6089-6098 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	canola D‐optimal design fourier transform infrared partial least square regression principal components analysis Nutrition. Foods and food supply TX341-641
spellingShingle	canola D‐optimal design fourier transform infrared partial least square regression principal components analysis Nutrition. Foods and food supply TX341-641 Muhammad Haseeb Ahmad Zainab Shahbaz Muhammad Imran Muhammad Kamran Khan Niaz Muhammad Sanaullah Iqbal Waqas Ahmed Tanvir Ahmad Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
description	Abstract The production of trans‐fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D‐optimal mixture design, and the best formulation (67:22:11) based on free fatty acid (FFA) content, peroxide value (PV), and iodine value (IV) as responses was selected for multiple frying process. The data on FFA, PV, and IV along with Fourier transform‐infrared (FT‐IR) spectra were taken after each frying up to ten frying. The spectral data were preprocessed with standard normal variate followed by principal component analysis which is clearly showing the differentiation for various frying. Similarly, partial least square regression was applied to predict the FFA (0.37%–1.63%), PV (4.47–13.85 meqO2/kg), and IV (111.51–51.39 I2/100 g) which demonstrated high coefficient of determination (R2) 0.84, 0.83, and 0.81, respectively. It can be summarized that FT‐IR can be used as a novel tool for fast and noninvasive quality determination of frying oils.
format	article
author	Muhammad Haseeb Ahmad Zainab Shahbaz Muhammad Imran Muhammad Kamran Khan Niaz Muhammad Sanaullah Iqbal Waqas Ahmed Tanvir Ahmad
author_facet	Muhammad Haseeb Ahmad Zainab Shahbaz Muhammad Imran Muhammad Kamran Khan Niaz Muhammad Sanaullah Iqbal Waqas Ahmed Tanvir Ahmad
author_sort	Muhammad Haseeb Ahmad
title	Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
title_short	Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
title_full	Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
title_fullStr	Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
title_full_unstemmed	Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
title_sort	monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/be5f18622d444fc786be0ac0b59dc2a3
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Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques

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