Indexing metadata

Characterization and rapid detection of adulterations in sesame oil using FT-MIR and PCA-LDA


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document Characterization and rapid detection of adulterations in sesame oil using FT-MIR and PCA-LDA
 
2. Creator Author's name, affiliation, country W. Terouzi; Laboratory of Spectro- Chemometrics and environment, Faculty of Science and Technology of Beni Mellal, University of Sultan Moulay slimane; Morocco
 
2. Creator Author's name, affiliation, country H. Rizki
 
2. Creator Author's name, affiliation, country F. Kzaiber
 
2. Creator Author's name, affiliation, country H. Hanine
 
2. Creator Author's name, affiliation, country A. Nabloussi
 
2. Creator Author's name, affiliation, country A. Oussama
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) ATR-FTIR spectroscopy ; Sesame oil ; Adulteration ; Chemometrics.
 
4. Description Abstract

The objective of this research work was to use Attenuated total reflectance-Fourier transform mid-infrared (ATR-FTMIR) spectroscopy coupled with chemometrics for the detection of the adulteration of sesame oil. Adulteration with sunflower oil, soybean oil or  colza oil  is one of the most difficult to detect due to the similar composition of them and sesame oil. Adulterations of sesame oil with different percentages of sunflower oil, soybean oil and colza oil were measured using ATR-FTMIR spectroscopy. The spectral data were subjected to a preliminary derivative elaboration based on the Savitzky–Golay algorithm to reduce the noise and extract a largest number of analytical information from spectra. Linear discriminant analysis (LDA) was adopted as classification method, and Principle component analysis (PCA) was employed to compress the original data set into a reduced new set of variables before LDA.

The detection results indicated that the discriminant model built by PCA-LDA method could identify sesame oil adulterations in the 0–40% weight ratio range of edible oils, with an accuracy value of 94.64%. This work shows that PCA and LDA are useful chemometric tools for the multivariate characterization and discrimination of sesame oil adulteration with seed oils.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 09-10-2016
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier https://revues.imist.ma/index.php/morjchem/article/view/5167
 
10. Identifier Digital Object Identifier (DOI) https://doi.org/10.48317/IMIST.PRSM/morjchem-v4i4.5167
 
11. Source Title; vol., no. (year) Moroccan Journal of Chemistry; Vol 4, No 4 (2016)
 
12. Language English=en en
 
13. Relation Supp. Files
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions Copyright (c)