Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

Browse

Filters

20193

Settings

Scopus Q: search.filters.scopusQuartile.Q1Subject: search.filters.subject.FTIR spectroscopy

Search Results

Now showing 1 - 3 of 3
  • Article
    Citation - WoS: 61
    Citation - Scopus: 70
    Use of Ftir and Uv-Visible Spectroscopy in Determination of Chemical Characteristics of Olive Oils
    (Elsevier, 2019) Uncu, Oğuz; Özen, Banu; Tokatlı, Figen
    It was aimed to predict fatty acid ethyl ester (FAEE), wax, diacylglycerol (DAG) and color pigment contents of olive oils by using rapid and non-destructive spectroscopic techniques (FTIR and UV-vis) individually and in combination. Prediction models were constructed by using partial least squares (PLS) regression with cross and external validation. FAEEs were estimated best with FTIR + UV-Vis spectroscopy (R-cv.(2) = 0.84, R-pred(2) = 0.90, and RPD = 3.0). PLS model with R-cv.(2) = 0.79, R-pred(2) = 0.71, and RPD = 1.9 was obtained for the estimation of 1,2 DAG using FTIR spectral data. Major pigments, lutein, pheophytin a and their derivatives and total xanthophylls were quantified successfully by FTIR + UV-Vis with a range of R-cv.(2) of 0.71-0.85, R-pred(2) of 0.70-0.84, and RPD = 1.5-2.5 values but the prediction of the rest of the pigments were poor (R-cv(2) = 0.60-0.76, R-pred(2) = 0.42-0.62, and RPD = 1.2-1.5). Combination of two spectral data resulted in average prediction of wax content of oils (R-cal(2) = 0.95, R-pred(2) = 0.75, and RPD = 1.9). FTIR and UV-vis spectroscopic techniques in combination with PLS regression provided promising results for the prediction of several chemical parameters of olive oils; therefore, they could be alternatives to traditional analysis methods.
  • Article
    Citation - WoS: 90
    Citation - Scopus: 101
    A Rapid Atr-Ftir Spectroscopic Method for Classification of Gelatin Gummy Candies in Relation To the Gelatin Source
    (Elsevier, 2019) Çebi, Nur; Doğan, Canan Ekinci; Ekin Meşe, Ayten; Özdemir, Durmuş; Arıcı, Muhammet; Sağdıç, Osman
    Gelatin is widely used in gummy candies because of its unique functional properties. Generally, porcine and bovine gelatins are used in the food industry. FTIR-ATR combined with chemometrics analysis such as hierarchical cluster analysis (HCA) (OPUS Version 7.2 software), principal component analysis (PCA) (OPUS Version 7.2 software) and partial least squares-discriminant analysis (PLS-DA) (Matlab R2017b) were used for classification and discrimination of gelatin gummy candies related to their gelatin source. The spectral region between 1734 and 1528 cm(-1) was selected for chemometric analysis. The potential of FTIR spectroscopy for determination of bovine and porcine source in gummy candies was examined and validated by a real-time polymerase chain reaction (PCR) method. Twenty commercial samples were tested by developed ATR-FTIR methodology and RT-PCR technique, mutually confirming and supporting results were obtained. Gummy candies were classified and discriminated in relation to the bovine or porcine source of gelatin with 100% success without any sample preparation using FTIR-ATR technique.
  • Article
    Citation - WoS: 82
    Citation - Scopus: 103
    A Comparative Study of Mid-Infrared, Uv-Visible and Fluorescence Spectroscopy in Combination With Chemometrics for the Detection of Adulteration of Fresh Olive Oils With Old Olive Oils
    (Elsevier Ltd., 2019) Uncu, Oğuz; Uncu, Oğuz; Özen, Banu; Özen, Fatma Banu
    The work aimed to detect and quantify adulteration of fresh olive oils with old olive oils from the previous harvest year by using different spectroscopic approaches in combination with chemometrics. Adulterated samples prepared in varying concentrations (10.50%(v/v)) were analyzed with fluorescence, Fourier transform-infrared (FT-IR), and ultraviolet-visible (UV-vis) spectroscopic methods. Orthogonal partial least square-discriminant analysis (OPLS-DA) and partial least squares (PLS) regression techniques were used for the differentiation of adulterated oils from the pure oils and prediction of adulteration levels, respectively. After the application of various pre-treatment methods, all of the OPLS-DA classification models generated for every spectroscopic technique successfully differentiated adulterated and non-adulterated oils with over 90% correct classification rate. FT-IR + UV-vis and fluorescence spectral data were also successfully used to predict adulteration levels with high coefficient of determinations for both calibration (0.94 and 0.98) and prediction (0.91 and 0.97) models and low error values for calibration (4.22% and 2.68%), and prediction (5.20% and 2.82%), compared to individual FT-IR and UV-vis spectroscopy were obtained. Therefore, FT-IR + UV-vis and fluorescence spectroscopy as being fast and environmentally friendly tools have great potential for both classification and quantification of adulteration practices involving old olive oil.