Food Engineering / Gıda Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/12

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  • Article
    Citation - WoS: 9
    Citation - Scopus: 11
    Prediction of Vinegar Processing Parameters With Chemometric Modelling of Spectroscopic Data
    (Elsevier, 2021) Çavdaroğlu, Çağrı; Çavdaroğlu, Çağrı; Özen, Banu; Özen, Fatma Banu
    Spectroscopic methods have the advantages of being rapid and environmentally friendly and can be used in measurement and control of processing parameters during food production. It was aimed to predict several quality and chemical parameters of vinegar processing from UV-visible and mid-infrared spectroscopic profiles. Two processing lines of both traditional and submerged vinegar production from 2 separate grape varieties (green and red grapes) were monitored. Some of the important markers of the fermentation processes; pH, brix, total acidity, total flavonoid content, total and individual phenolic contents, organic acid, sugar, ethanol concentrations as well as UV-visible and mid-infrared spectra were obtained during both types of vinegar processing and quality and chemical parameters were predicted from spectroscopic data using chemometric methods. Individual UV-visible and mid-infrared spectral profiles along with low level of data fusion were used in building of chemometric prediction models. Accurate, reliable and robust prediction models (R(2)cal and R(2)val >0.9) were obtained for quality parameters mostly with combination of two spectroscopic datasets. Predictive models used for phenolic components were below average except for p-coumaric and syringic acids. Citric and acetic acids were the most accurately estimated ones among organic acids along with ethanol. Close agreements between reference and predicted values were obtained during the monitoring of changes of some quality parameters for vinegar fermentation process through rapid and simultaneous spectroscopic measurements.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 6
    Chemometric Studies on Znose™ and Machine Vision Technologies for Discrimination of Commercial Extra Virgin Olive Oils
    (John Wiley and Sons Inc., 2015) Kadiroğlu, Pınar; Korel, Figen
    The 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: 32
    Citation - Scopus: 36
    Application 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, Banu
    Mid-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: 35
    Citation - Scopus: 40
    Flavour 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, Hülya
    A 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: 75
    Citation - Scopus: 78
    Classification 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, Figen
    Fatty 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.