ATR–FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS FOR RAPID CLASSIFICATION OF EXTRA VIRGIN OLIVE OILS AND EDIBLE OILS FROM DIFFERENT CULTIVARS AVAILABLE ON THE TURKISH MARKETS

Fatma Nur ARSLAN

doi:https://doi.org/10.18038/aubtda.425374

Article Details

ATR–FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS FOR RAPID CLASSIFICATION OF EXTRA VIRGIN OLIVE OILS AND EDIBLE OILS FROM DIFFERENT CULTIVARS AVAILABLE ON THE TURKISH MARKETS

Authors:

Fatma Nur ARSLAN

Publisher:

Eskisehir Technical University

Main Topics:

Applied physics

Journal:

Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2018 Vol.19 Issue 4, pp.926-947

Document Type:

Article

Publication Date:

12/2018

Document Language:

English

Document ID (Org No.):

2000417026

pISSN:

2667-4211

DOI:

https://doi.org/10.18038/aubtda.425374

Abstract:

 

A combination of attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy and chemometric techniques was used to classify different trademarks of edible oils available on the Turkish markets. A total of 144 spectra of edible oil samples, including extra virgin olive oil (VOO), hazelnut oil (HNO), cottonseed oil (CSO), sunflower oil (SFO) and soybean oil (SBO), was recorded. The feasibility of ATR–FTIR with multivariate data analysis for discrimination of extra VOOs from other edible oils was also evaluated. Classification of edible oils was performed using principal components analysis (PCA), hierarchical cluster analysis (HCA), linear discriminant analysis (LDA) and soft independent modeling of class analogies (SIMCA). The spectra collected from wavelength region of 4000–650 cm-1 and 28 different wavelength ranges selected from full spectra were evaluated for optimal classification models. All multivariate analysis provided excellent discriminations between the edible oil classes with low classification error. LDA models constructed with five predictors, and a total of 100% of edible oil samples from different trademarks were correctly classified. Furthermore, no misclassification was reported for the discriminant analysis in supervised SIMCA models with an accuracy of 95%. Consequently, ATR–FTIR spectroscopy combined with multivariate data analyses provides excellent illustrations of the relative positions of the different brands of commercial edible oils according to their quality and purity.

Article Details

ATR–FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS FOR RAPID CLASSIFICATION OF EXTRA VIRGIN OLIVE OILS AND EDIBLE OILS FROM DIFFERENT CULTIVARS AVAILABLE ON THE TURKISH MARKETS

Authors: Fatma Nur ARSLAN

Publisher: Eskisehir Technical University

Main Topics: Applied physics

Journal: Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2018 Vol.19 Issue 4, pp.926-947

Document Type: Article

Publication Date: 12/2018

Document Language: English

Document ID (Org No.): 2000417026

pISSN: 2667-4211

DOI: https://doi.org/10.18038/aubtda.425374

Issues

Authors:

Fatma Nur ARSLAN

Publisher:

Eskisehir Technical University

Main Topics:

Applied physics

Journal:

Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2018 Vol.19 Issue 4, pp.926-947

Document Type:

Article

Publication Date:

12/2018

Document Language:

English

Document ID (Org No.):

2000417026

pISSN:

2667-4211

DOI:

https://doi.org/10.18038/aubtda.425374