Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 11Citation - Scopus: 10Ir Spectroscopy and Chemometrics for Physical Property Prediction of Structured Lipids Produced by Interesterification of Beef Tallow(Academic Press, 2019) Aktaş, Ayşe Burcu; Alamprese, Cristina; Fessas, Dimitrios; Özen, BanuThe aim of this study was the application of infrared spectroscopy and chemometrics to predict slip melting point (SMP), melting points at different melted fat percentages (MP85, MP90, MP95), and consistency of structured lipids to provide fast and reliable methods for their characterization. Tallow was chemically or enzymatically interesterified with corn, canola, or safflower oils, at different ratios. Fourier-transform mid-infrared (FT-IR) and near-infrared (FT-NIR) spectra of melted and solid samples were collected. Partial-least-square regression models constructed after different spectra pre-treatments and variable selection were satisfactory. The best models were obtained with solid sample FT-NIR spectra: in cross-validation, determination coefficients and root mean square errors were, respectively, 0.85 and 1.7 degrees C for SMP, 0.85 and 2.8 degrees C for MP90, and 0.91 and 14 MPa for consistency. Infrared spectroscopy can be considered a promising tool to determine physical properties of interesterified fats.Article Citation - WoS: 12Citation - Scopus: 12Mid-Infrared Spectroscopic Detection of Sunflower Oil Adulteration With Safflower Oil(CSIC Consejo Superior de Investigaciones Cientificas, 2019) Uncu, Oğuz; Özen, Banu; Tokatlı, FigenThe oil industry is in need of rapid analysis techniques to differentiate mixtures of safflower-sunflower oils from pure oils. The current adulteration detection methods are generally cumbersome and detection limits are questionable. The aim of this study was to test the capability of a mid-infrared spectroscopic method to detect the adulteration of sunflower oil with safflower oil compared to fatty acid analysis. Mid-infrared spectra of pure oils and their mixtures at the 10-60% range were obtained at 4000-650 cm(-1) wavenumber and fatty acid profiles were determined. Data were analyzed by multivariate statistical analysis techniques. The lowest level of detection was obtained with mid-infrared spectroscopy at 30% while the fatty acid profile could determine adulteration at around 60%. Adulteration levels were predicted successfully using PLS regression analysis of infrared data with R-2 (calibration) = 0.96 and R-2 (validation) = 0.93. As a rapid and minimum waste generating technique, mid-infrared spectroscopy could be a useful tool for the screening of raw material to detect safflower-sunflower oil mixtures.Article Citation - WoS: 82Citation - Scopus: 103A 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 BanuThe 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.Article Citation - WoS: 5Citation - Scopus: 6Chemometric Studies on Znose™ and Machine Vision Technologies for Discrimination of Commercial Extra Virgin Olive Oils(John Wiley and Sons Inc., 2015) Kadiroğlu, Pınar; Korel, FigenThe aim of this study was to classify Turkish commercial extra virgin olive oil (EVOO) samples according to geographical origins by using surface acoustic wave sensing electronic nose (zNose™) and machine vision system (MVS) analyses in combination with chemometric approaches. EVOO samples obtained from north and south Aegean region were used in the study. The data analyses were performed with principal component analysis class models, partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA). Based on the zNose™ analysis, it was found that EVOO aroma profiles could be discriminated successfully according to geographical origin of the samples with the aid of the PLS-DA method. Color analysis was conducted as an additional sensory quality parameter that is preferred by the consumers. The results of HCA and PLS-DA methods demonstrated that color measurement alone was not an effective discriminative factor for classification of EVOO. However, PLS-DA and HCA methods provided clear differentiation among the EVOO samples in terms of electronic nose and color measurements. This study is significant from the point of evaluating the potential of zNose™ in combination with MVS as a rapid method for the classification of geographically different EVOO produced in industry.Article Citation - WoS: 32Citation - Scopus: 36Application of Mid-Infrared Spectroscopy for the Measurement of Several Quality Parameters of Alcoholic Beverages, Wine and Raki(Springer Verlag, 2012) Öztürk, Burcu; Yücesoy, Dila; Özen, BanuMid-infrared (IR) spectroscopy, which is a rapid and relatively small amount of waste producing technique, was used to predict several quality parameters of two types of alcoholic beverages, wine and raki. Mid-infrared spectra of red, rose and white wines and a traditional aniseed alcoholic beverage, raki were collected and relations were established between measured chemical parameters (pH, brix, total phenol content, anthocyanin content, titratable acidity, sugar content, electrical conductivity and some colour parameters) of these beverages and their infrared spectra using chemometric techniques. Partial least square regression provided excellent prediction of total phenol (R 2 = 0. 97) and anthocyanin contents (R 2 = 0. 98) of wine samples and a good prediction of pH (R 2 = 0. 9), brix (R 2 = 0. 92) and colour intensity (R 2 = 0. 93) values were obtained. Brix, total phenol and sugar content of raki samples were also estimated very successfully (R 2 = 0. 99) for raki and good prediction was obtained with pH value. Mid-IR spectroscopy in combination with chemometrics could be a promising technique for determination of several quality parameters of alcoholic beverages simultaneously and rapidly.Article Citation - WoS: 30Citation - Scopus: 34Authentication of a Turkish Traditional Aniseed Flavoured Distilled Spirit, Raki(Elsevier Ltd., 2013) Yüceesoy, Dila; Özen, BanuConsumption of traditional aniseed alcoholic beverage, raki, adulterated with methanol results in deaths, therefore, its detection is an important issue. In this study, mid-infrared spectra of pure and methanol adulterated (0.5-10% (vol/vol)) raki samples were collected with an attenuated total reflectance attachment of a Fourier-transform infrared spectrometer. Principal component analysis was used to discriminate pure and adulterated raki samples, then, a partial least square model was constructed to determine the adulterant methanol content in raki using mid-IR spectral data. A minimum threshold level of 0.5% methanol in raki samples was successfully detected. A good prediction model for determination of methanol adulteration ratio in raki samples was also constructed (R2 = 0.98 and RPD = 8.35).Article Citation - WoS: 35Citation - Scopus: 40Flavour of Natural and Roasted Turkish Hazelnut Varieties (corylus Avellana L.) by Descriptive Sensory Analysis, Electronic Nose and Chemometrics(John Wiley and Sons Inc., 2012) Alasalvar, Cesarettin; Pelvan, Ebru; Bahar, Banu; Korel, Figen; Ölmez, HülyaA total of eighteen natural and roasted hazelnut varieties (amongst which only Tombul variety is classified as prime quality), grown in the Giresun province of Turkey, were compared for their differences in descriptive sensory analysis (DSA), electronic nose (e-nose) data and chemometrics. Differences in some descriptive of DSA between natural and roasted hazelnuts as well as within the varieties were observed. Although Tombul hazelnut was selected as one of the best varieties in terms of flavour attributes and received the highest intensities in general, no significant differences (P>0.05) existed among hazelnut varieties except in certain flavour attributes ('after taste' and 'nutty'). DSA and e-nose data of natural and roasted hazelnuts were also evaluated for discrimination using principal component analysis (PCA) and cluster analysis. Results of PCA using e-nose data showed that extracted principal components explained 99.7% and 99.8% of the total variance of the data for natural and roasted hazelnut varieties, respectively. Both DSA and e-nose can be used for discrimination of natural and roasted hazelnuts. © 2011 The Authors. International Journal of Food Science and Technology © 2011 Institute of Food Science and Technology.Article Citation - WoS: 231Citation - Scopus: 264Detection of Adulteration of Extra-Virgin Olive Oil by Chemometric Analysis of Mid-Infrared Spectral Data(Elsevier Ltd., 2009) Gürdeniz, Gözde; Özen, Fatma BanuThis study focuses on the detection and quantification of extra-virgin olive oil adulteration with different edible oils using mid-infrared (IR) spectroscopy with chemometrics. Mid-IR spectra were manipulated with wavelet compression previous to principal component analysis (PCA). Detection limit of adulteration was determined as 5% for corn-sunflower binary mixture, cottonseed and rapeseed oils. For quantification of adulteration, mid-IR spectral data were manipulated with orthogonal signal correction (OSC) and wavelet compression before partial least square (PLS) analysis. The results revealed that models predict the adulterants, corn-sunflower binary mixture, cottonseed and rapeseed oils, in olive oil with error limits of 1.04, 1.4 and 1.32, respectively. Furthermore, the data were analysed with a general PCA model and PLS discriminant analysis (PLS-DA) to observe the efficiency of the model to detect adulteration regardless of the type of adulterant oil. In this case, detection limit for adulteration is determined as 10%.Article Citation - WoS: 75Citation - Scopus: 78Classification of Turkish Olive Oils With Respect To Cultivar, Geographic Origin and Harvest Year, Using Fatty Acid Profile and Mid-Ir Spectroscopy(Springer Verlag, 2008) Gürdeniz, Gözde; Özen, Fatma Banu; Tokatlı, FigenFatty acid composition and mid-infrared spectra of olive oils in combination with chemometric techniques were used in the classification of Turkish olive oils with respect to their varieties, growing location and harvest year. In particular, olive oil samples belonging to five different cultivars were obtained from the same orchard in the middle part of Aegean region and two of these varieties were also received from another orchard in northern part of the same region of Turkey in two consecutive harvest years. Evaluation of nine different fatty acid compositions with principal component analysis revealed clear differentiation with respect to variety, geographical origin and harvest year. On the other hand, mid-infrared spectra also achieved varietal and seasonal discrimination to some extent, but differentiation is not as clear as that obtained using fatty acid compositions. © 2008 Springer-Verlag.Article Citation - WoS: 68Citation - Scopus: 76Differentiation of Mixtures of Monovarietal Olive Oils by Mid-Infrared Spectroscopy and Chemometrics(John Wiley and Sons Inc., 2007) Gürdeniz, Gözde; Tokatlı, Figen; Özen, Fatma BanuFourier transform infrared (FT-IR) spectroscopy in combination with chemometric techniques has become a useful tool for authenticity determination of extra-virgin olive oils. Spectroscopic analysis of monovarietal extra-virgin olive oils obtained from three different olive cultivars (Erkence, Ayvalik and Nizip) and mixtures (Erkence-Nizip and Ayvalik-Nizip) of monovarietal olive oils was performed with an FT-IR spectrometer equipped with a ZnSe attenuated total reflection sample accessory and a deuterated tri-glycine sulfate detector. Using spectral data, principal component analysis successfully classified each cultivar and differentiated the mixtures from pure mono-varietal oils. Quantification of two different monovarietal oil mixtures (2-20%) is achieved using partial least square (PLS) regression models. Correlation coefficients (R2) of the proposed PLS regression models are 0.94 and 0.96 for the Erkence-Nizip and Ayvalik-Nizip mixtures, respectively. Cross-validation was applied to check the goodness of fit for the PLS regression models, and R 2 of the cross-validation was determined as 0.84 and 0.91, respectively, for the two mixtures.