Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 35Citation - Scopus: 43Potential of Fourier-Transform Infrared Spectroscopy in Adulteration Detection and Quality Assessment in Buffalo and Goat Milks(Elsevier, 2021) Şen, Sevval; Dündar, Zahide; Uncu, Oğuz; Özen, BanuAdulteration of higher priced milks with cheaper ones to obtain extra profit can be the cause of adverse health effects as well as economic loss. In this study, it was aimed to differentiate goat-cow and buffalo-cow milk mixtures and also to estimate the critical quality parameters of these milks by the evaluation of Fourier-transform infrared (FTIR) spectroscopic data with chemometric methods. Raw goat and buffalo milks were mixed with cow milk at 1-50% (v/v) concentrations and FTIR spectra of the pure and mixed samples were obtained at 4000-650 cm-1. Orthogonal partial least square discriminant analysis (OPLS-DA) resulted in differentiation of goat-cow and buffalo-cow milk mixtures with 93% and 91% correct classification rates, respectively. Detection level for mixing is determined as higher than 5% for both milks. Total fat, protein, lactose and non-fat solid contents were predicted from FTIR spectral data of the combination of three types of milks by partial least square models with R2 values of 0.99. As a result, FTIR spectroscopy provides rapid and simultaneous detection of adulteration and prediction of quality parameters regardless of the milk type.Article Citation - WoS: 25Citation - Scopus: 30Prediction of Chemical Parameters and Authentication of Various Cold Pressed Oils With Fluorescence and Mid-Infrared Spectroscopic Methods(Elsevier Ltd., 2021) Doğruer, Ilgın; Uyar, H. Hilal; Uncu, Oğuz; Özen, BanuIt was aimed to compare the performances of two spectroscopic methods, fluorescence and mid-infrared spectroscopy, in terms of their adulteration detection and estimation of several chemical properties for various cold pressed seed oils. Spectroscopic profiles, fatty acid, free fatty acid and total phenol contents of pumpkin seed, grape seed, black cumin oil, and sesame seed oils were determined and these oils were mixed with sunflower oil at 1–50% (v/v). Both spectroscopic techniques provided comparable results for determination of adulteration of each oil type and the most successful prediction was obtained for pumpkin seed oil at levels >%1. Combined data set of oils resulted in successful quantification of their free fatty acid value, total phenol and major fatty acids contents with both spectroscopic methods regardless of oil type. Both techniques could be used as reliable, fast and environmentally friendly alternatives in the analyses of different types of seed oils. © 2020 Elsevier LtdArticle 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: 14Citation - Scopus: 18Evaluation of Three Spectroscopic Techniques in Determination of Adulteration of Cold Pressed Pomegranate Seed Oils(Elsevier Ltd., 2020) Uncu, Oğuz; Napiórkowska, Alicja; Szajna, Tomasz K.; Özen, BanuIt was aimed to compare three spectroscopic methods in determination of adulteration of cold pressed pomegranate seed oils (PSOs) with sunflower oil in this research. UV–visible, mid-infrared and fluorescence spectra of pure and adulterated pomegranate oils (1–50%, v/v) were collected and data were analyzed with multivariate statistical analysis techniques. According to orthogonal partial least square discriminant analysis, best differentiation between pure and mixed samples was obtained with mid-infrared spectroscopy having 100% success rate. Fluorescence and UV–visible spectroscopy also provided good discrimination between samples with 96 and 88% successful classification rates, respectively. As a result of partial least square regression analysis, detection limits for mid-infrared, UV–visible and fluorescence spectroscopies are determined as >1, 5 and 10% in order. Since all spectroscopic methods provided detection of mixtures of cold pressed PSOs with sunflower oil at low concentrations they could serve as easy to use and rapid techniques in control laboratories. © 2020 Elsevier B.V.Article Citation - WoS: 30Citation - Scopus: 30Discriminative Capacities of Infrared Spectroscopy and E-Nose on Turkish Olive Oils(Springer Verlag, 2017) Jolayemi, Olusola Samuel; Tokatlı, Figen; Buratti, Susanna; Alamprese, CristinaThe potentials of Fourier transform (FT) near- (NIR) and mid-infrared (IR) spectroscopy, and electronic nose (e-nose) on varietal classification of Turkish olive oils were demonstrated. A total of 63 samples were analyzed, comprising Ayvalik, Memecik, and Erkence oils. Spectra were pretreated with standard normal variate and second derivative. Classification models were built with orthogonal partial least square-discriminant analysis (OPLS-DA), considering the single data sets and also the combined FT-NIR-IR spectra. OPLS-DA models were validated both by cross validation and external prediction. All the models gave good results, being the average correct classification percentages in prediction higher than 90% for spectroscopic data and equal to 82% for e-nose data. The combined FT-NIR-IR data set gave the best results in terms of coefficients of determination (0.95 and 0.67). Different e-nose sensors discriminated Ayvalik, Memecik, and Erkence oils, explaining their distinct aromatic profiles.Article Citation - WoS: 18Citation - Scopus: 21Monitoring of Wine Process and Prediction of Its Parameters With Mid-Infrared Spectroscopy(John Wiley and Sons Inc., 2017) Canal, Canan; Özen, BanuIt was aimed to predict the chemical (ethanol, glycerol, organic acids, titratable acidity, °Brix, sugars, total phenolic and anthocyanin content) and microbiological parameters of red, rose and white wines during their processing from must to bottling using mid-infrared (IR) spectroscopy in combination with one of the multivariate statistical analysis techniques, partial least square (PLS) regression. Various spectral filtering techniques were employed before PLS regression analysis of mid-IR data. The best results were obtained from the second-order derivation for the chemical parameters except for alcohols. PLS models developed for the prediction of some of the chemical parameters have R2 values greater than 0.9, with low root mean square error values; however, prediction of microbial population from mid-IR spectroscopy did not provide accurate results. IR spectroscopic and chemical–chromatographic data were also used to investigate the differences between processing steps, and principal component analysis allowed clear separation of the beginning of the process from the rest. Practical Applications: Monitoring of the wine process from must to final product is necessary for better control of the process and the quality. As a rapid and a minimum waste-producing technique, mid-IR spectroscopy in combination with chemometric methods could allow prediction of several chemical parameters simultaneously. Therefore, any problems that could be encountered during wine processing could be determined and interfered in a short time.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: 37Citation - Scopus: 39Comparison of Fatty Acid Profiles and Mid-Infrared Spectral Data for Classification of Olive Oils(John Wiley and Sons Inc., 2010) Gürdeniz, Gözde; Özen, Banu; Tokatlı, FigenThe composition of olive oils may vary depending on environmental and technological factors. Fatty acid profiles and Fourier-transform infrared (FT-IR) spectroscopy data in combination with chemometric methods were used to classify extra-virgin olive oils according to geographical origin and harvest year. Oils were obtained from 30 different areas of northern and southern parts of the Aegean Region of Turkey for two consecutive harvest years. Fatty acid composition data analyzed with principal component analysis was more successful in distinguishing northern olive oil samples from southern samples compared to spectral data. Both methods have the ability to differentiate olive oil samples with respect to harvest year. Partial least squares (PLS) analysis was also applied to detect a correlation between fatty acid profile and spectral data. Correlation coefficients (R2) of a calibration set for stearic, oleic, linoleic, arachidic and linolenic acids were determined as 0.83, 0.97, 0.97, 0.83 and 0.69, respectively. Fatty acid profiles were very effective in classification of oils with respect to geographic origin and harvest year. On the other hand, FT-IR spectra in combination with PLS could be a useful and rapid tool for the determination of some of the fatty acids of olive oils.Article Citation - WoS: 120Citation - Scopus: 135Authentication of Pomegranate Juice Concentrate Using Ftir Spectroscopy and Chemometrics(Elsevier Ltd., 2008) Vardin, Hasan; Tay, Abdullatif; Özen, Fatma Banu; Mauer, LisaFourier transform infrared (FTIR) spectroscopy and chemometric techniques were used to detect the adulteration of pomegranate juice concentrate (PJC) with grape juice concentrate (GJC). The main differences between PJC and GJC infrared spectra occurred in the 1780-1685 cm-1 region, which corresponds to C{double bond, long}O stretching. Principal component analysis of the spectra was used to: (1) differentiate pure PJC and GJC samples and (2) classify adulterated (containing 2-14% vol/vol GJC) and pure PJC samples. Two principal components explained 99% of the variability in each of these applications. Partial least square analysis of the spectra resulted in prediction of the GJC adulterant concentration in PJC with a correlation coefficient, R2, of 0.9751. Partial least square analysis of spectra could also predict % titratable acidity and total solids in PJC with correlation coefficients of 0.9114 and 0.9916, respectively. Therefore, FTIR and chemometrics provide a useful approach for authenticating pomegranate juice concentrate.