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.Book Part Citation - Scopus: 3Infrared Spectroscopy for the Detection of Adulteration in Foods(John Wiley and Sons Inc., 2012) Özen, Banu; Tokatlı, FigenIR spectroscopy in combination with chemometric techniques is an effective tool for the detection of adulteration of high economic value food products such as wine, dietary supplements and olive oil. It provides practical and quick alternative to other commonly used analytical methods.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.