Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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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: 14Citation - Scopus: 16Classification of Turkish Extra Virgin Olive Oils by a Saw Detector Electronic Nose(John Wiley and Sons Inc., 2011) Kadiroğlu, Pınar; Korel, Figen; Tokatlı, FigenAn electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalik (A), Domat (D), Nizip (N), Gemlik-Edremit (GE), Ayvalik-Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose.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: 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.