Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/182166
Title: Classification of sesame oil based on processing-originated differences in the volatile organic compound profile by a colorimetric sensor
Authors: Liu, Tianyi
Shi, Hai-Ming
Elejalde, Untzizu
Chen, Xiaodong
Keywords: Engineering
Issue Date: 2024
Source: Liu, T., Shi, H., Elejalde, U. & Chen, X. (2024). Classification of sesame oil based on processing-originated differences in the volatile organic compound profile by a colorimetric sensor. Foods, 13(20), 3230-. https://dx.doi.org/10.3390/foods13203230
Project: S18-1395-IPP-II 
Journal: Foods 
Abstract: Fragrant edible sesame oil is popular for its unique aroma. The aroma of sesame oil is determined by its volatile organic compound (VOC) profile. Sesame oils produced by different techniques could have different VOC profiles. In addition, blending fragrant sesame oil with refined oil could also alter the VOC profile of the final product. Current practices in aroma analysis, such as sensory evaluation and gas chromatography (GC), still face many restraints. Hence, there is a need for alternatives. We present a novel 14-unit multiplexed paper-based colorimetric sensor for fragrant sesame oil VOC analysis. The sensor was designed to visualize the VOC profile as a color "fingerprint". The sensor was validated with 55 branded sesame oil samples produced by two different techniques, i.e., hot pressing and small milling; the experimental results suggested a processing dependency in color VOC fingerprints. The sensor also demonstrated the potential to detect the change in sesame oil VOC profile due to blending with refined oil, with an estimated limit of detection down to 20% v/v of the refined oil. The colorimetric sensor might be used as a simple, rapid, and cost-effective analytical tool in the production and quality control of fragrant sesame oil.
URI: https://hdl.handle.net/10356/182166
ISSN: 2304-8158
DOI: 10.3390/foods13203230
Schools: School of Materials Science and Engineering 
Organisations: Wilmar Innovation Center, Singapore 
Rights: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MSE Journal Articles

Files in This Item:
File Description SizeFormat 
foods-13-03230.pdf3.87 MBAdobe PDFThumbnail
View/Open

Page view(s)

56
Updated on Mar 25, 2025

Download(s)

9
Updated on Mar 25, 2025

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.