Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 41Citation - Scopus: 43Changes in Quality Characteristics of Strawberry Juice After Equivalent High Pressure, Ultrasound, and Pulsed Electric Fields Processes(Springer Verlag, 2020) Yıldız, Semanur; Ünlütürk, Sevcan; Ünlütürk, Sevcan; Barbosa-Canovas, Gustavo V.; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyUnderstanding the efficacy of viable emerging technologies in preserving overall quality attributes and antioxidant characteristics of fruit juices is of great interest. This study aimed to evaluate the effect of high pressure (HP), ultrasound (US), and pulsed electric fields (PEF) processes on natural microbiota inactivation, as well as changes in physicochemical attributes and phytochemical content of strawberry juice (SJ). HP at 300 MPa (1 min), US at 55 degrees C (3 min) and 517.1 mW/mL acoustic energy density, and PEF at 35 kV/cm (27 mu s) using monopolar square pulses with 2 mu s pulse width were applied, and then compared with a conventional thermal pasteurization treatment (72 degrees C, 15 s). The nonthermal processes were equivalent in terms ofEscherichia coli(E. coli) inactivation since the selected processing conditions led to almost identical inactivation level (at least 5-log) of inoculatedE. coli. The current study analyzes why these equivalent processes had different effect on SJ quality. All treatments significantly reduced the initial natural microbiota (i.e., total mesophilic aerobic bacteria and yeast-molds) below 2 log CFU/mL. No significant changes were observed on the total soluble solid content (7.83-8.00 degrees Brix), titratable acidity (0.79-0.84 g/100 mL), and pH (3.45-3.50; except in sonication) between SJ processed samples and the untreated ones (p > 0.05). HPP and PEF significantly promoted higher retention of total phenolic content (TPC) and radical scavenging activity (RSA) than thermal pasteurization, and significantly enhanced total anthocyanin content (TAC) compared with unprocessed SJ. HPP and PEF increased the TPC (4-5%), RSA (18-19%), and TAC (15-17%) in comparison with unprocessed SJ. Multivariate data analysis tools, i.e., principal component analysis (PCA) and hierarchical cluster analysis (HCA), were successfully applied for discrimination and classification of SJ samples based on the similarities or differences among physicochemical and phytochemical characteristics. PCA and HCA indicated that HPP- and PEF-treated samples had similar enhanced properties in terms of phytochemical content and were superior to sonicated, thermally pasteurized, and unprocessed samples. The multivariate data analysis methods were very useful to compare and classify SJ quality characteristics as a function of the processing technology. This study demonstrated that the application of the equivalent processing approach may reveal new opportunities to produce equivalent or even enhanced quality fruit juices.Article Citation - WoS: 1Citation - Scopus: 2Discrimination of Bio-Crystallogram Images Using Neural Networks(Springer Verlag, 2014) Ünlütürk, Sevcan; Ünlütürk, Sevcan; Pazır, Fikret; Kuşçu, Alper; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThis study utilized a unique neural network model for texture image analysis to differentiate the crystallograms from pairs of fresh red pepper fruits from conventional and organic farms. The differences in visually analyzed samples are defined as the distribution of crystals on the circular glass underlay, the thin or thick structure of crystal needles, the angles between branches and side needles, etc. However, the visual description and definition of bio-crystallogram images has major disadvantages. A novel methodology called an image neural network (INN) has been developed to overcome these shortcomings. The 1,488 × 2,240 pixel bio-crystallogram images were acquired in a lab and cropped to 425 × 1,025 pixel images. These depicted either a conventional sweet red pepper or an organic sweet red pepper. A set of 19 images was utilized to train the image neural network. A new set of 4 images was then prepared to test the INN performance. Overall, the INN achieved an average recognition performance of 100 %. This high level of recognition suggests that the INN is a promising method for the discrimination of bio-crystallogram images. In addition, Hinton diagrams were utilized to display the optimality of the INN weights.Article Citation - WoS: 38Citation - Scopus: 48The Impact of Uv-C Irradiation on Spoilage Microorganisms and Colour of Orange Juice(Springer Verlag, 2013) Hakgüder Taze, Bengi; Ünlütürk, Sevcan; Ünlütürk, Sevcan; Hakgüder Taze, Bengi; 01. Izmir Institute of Technology; 03.08. Department of Food Engineering; 03. Faculty of EngineeringThe effect of UV-C irradiation on inactivation of spoilage microorganisms and colour of freshly squeezed orange juice were investigated. Orange juice samples were intentionally fermented in order to increase the natural microflora which were mostly composed of yeasts and then exposed to UV-C irradiation at an intensity level of 1.32 mW/cm2 and sample depth of 0.153 cm for several exposure times by using a collimated beam apparatus. Applied UV dose was in the range of 0 and 108.42 mJ/cm2. Resistance of yeast to UV light and existence of suspended particles limited the effectiveness of the process. Survival data obtained for yeasts was either described by the Weibull or traditional first-order model and goodness-of-fit of these models was investigated. Weibull model produced a better fit to the data with higher adjusted determination coefficient (R2 adj) and lower mean square error (MSE) values which were 0.99 and 0.003, respectively. Time and UV dose of first decimal reduction were obtained as 5.7 min and 31 mJ/cm2, respectively. The data suggests that biodosimetric studies performed by using inoculated microorganisms for assesment of the efficiency of UV irradiation treatment in the shelf life extension of juices must be carefully evaluated. UV-C irradiation had no influence on the colour of orange juice.Article Citation - WoS: 1Citation - Scopus: 2Process Neural Network Method: Case Study I: Discrimination of Sweet Red Peppers Prepared by Different Methods(Springer Verlag, 2011) Ünlütürk, Sevcan; Ünlütürk, Sevcan; Pazır, Fikret; Kuşçu, Alper; 03.08. Department of Food Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThis study utilized a feed-forward neural network model along with computer vision techniques to discriminate sweet red pepper products prepared by different methods such as freezing and pureeing. The differences among the fresh, frozen and pureed samples are investigated by studying their bio-crystallogram images. The dissimilarity in visually analyzed bio-crystallogram images are defined as the distribution of crystals on the circular glass underlay and the thin or the thick structure of crystal needles. However, the visual description and definition of bio-crystallogram images has major disadvantages. A methodology called process neural network (ProcNN) has been studied to overcome these shortcomings.