Scopus
YÖKSİS Eşleşti
Multivariate Modeling for Quantifying Adulteration of Sunflower Oil with Low Level of Safflower Oil Using ATR-FTIR, UV-Visible, and Fluorescence Spectroscopies: A Comparative Approach
Food Analytical Methods · Şubat 2021
YÖKSİS Kayıtları
Multivariate Modeling for Quantifying Adulteration of Sunflower Oil with Low Level of Safflower Oil Using ATR-FTIR, UV-Visible, and Fluorescence Spectroscopies: A Comparative Approach
Food Analytical Methods · 2021 SCI-Expanded
PROFESÖR HÜSEYİN KARA →
Multivariate Modeling for Quantifying Adulteration of Sunflower Oil with Low Level of Safflower Oil Using ATR-FTIR, UV-Visible, and Fluorescence Spectroscopies: A Comparative Approach
FOOD ANALYTICAL METHODS · 2021 SCI-Expanded
ARAŞTIRMA GÖREVLİSİ MUHAMMED RAŞİT BAKIR →
Multivariate Modeling for Quantifying Adulteration of Sunflower Oil with Low Level of Safflower Oil Using ATR-FTIR, UV-Visible, and Fluorescence Spectroscopies: A Comparative Approach
Springer Science and Business Media LLC · 2020 SCI-Expanded
DOÇENT İSMAİL TARHAN →
Multivariate Modeling for Quantifying Adulteration of Sunflower Oil with Low Level of Safflower Oil Using ATR-FTIR, UV-Visible, and Fluorescence Spectroscopies: A Comparative Approach
Food Analytical Methods · 2020 SCI-Expanded
ARAŞTIRMA GÖREVLİSİ MUHAMMED RAŞİT BAKIR →
Makale Bilgileri
DergiFood Analytical Methods
Yayın TarihiŞubat 2021
Cilt / Sayfa14 · 361-371
Scopus ID2-s2.0-85092732580
Özet
For the first time, a quick and simple analytical method was developed for the discrimination and the quantification of low level (< 10%) of safflower oil (SAF) in sunflower oil (SUN). Different spectroscopic techniques, such as attenuated total reflectance-Fourier transform infrared (ATR-FTIR), ultraviolet-visible (UV-Vis), and fluorescence (FL), have been used and their abilities to quantify SAF content in SUN were compared using statistical quality parameters of the developed calibration models. To quantify SAF content in SUN samples, partial least squares (PLS) regression (model 1) was used. To correlate SAF in the calibration set with their spectra, 30 multivariate calibration models were built by PLS algorithm. The performance and accuracy of PLS models were evaluated by the value of R-square, root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP). To detect SAF adulterations, several principal component analysis (PCA) models (model 2) were utilized. The performance of PCA models developed was evaluated by principal components (PC) percentages, the factor numbers reached, F-Residuals limits, and Hotelling’s T2 limits. Both for the quantify and the discrimination, the best predictions were achieved using normal spectra in FL spectroscopy with the lowest RMSEC of 0.2553, RMSEV of 0.5398, RMSEP of 0.2674, and F-Residuals limit of 0.7040 and with the highest R-square of 0.9937, PC percentages of 69%, the factor numbers of 7, and Hotelling’s T2 limit of 13.3208 in all spectral region.
Yazarlar (4)
1
İsmail Tarhan
ORCID: 0000-0003-3353-8635
2
M. Raşit Bakır
3
Oktay Kalkan
ORCID: 0000-0001-5974-8345
4
Huseyin Kara
Anahtar Kelimeler
Adulteration
Fluorescence spectroscopy
FTIR spectroscopy
Safflower oil
Sunflower oil
UV-Vis spectroscopy
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
5
Atıf
4
Yazar
6
Anahtar Kelime