Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 18Citation - Scopus: 35Microparticle-Enhanced Polygalacturonase Production by Wild Type Aspergillus Sojae(Springer Verlag, 2017) Karahalil, Ercan; Demirel, Fadime; Evcan, Ezgi; Germeç, Mustafa; Tarı, Canan; Turhan, İrfanPolygalacturonases (PGs), an important industrial enzyme group classified under depolymerases, catalyze the hydrolytic cleavage of the polygalacturonic acid chain through the introduction of water across the oxygen bridge. In order to produce and increase the concentration of this enzyme group in fermentation processes, a new approach called microparticle cultivation, a promising and remarkable method, has been used. The aim of this study was to increase the PG activity of Aspergillus sojae using aluminum oxide (Al2O3) as microparticles in shake flask fermentation medium. Results indicated that the highest PG activity of 34.55 ± 0.5 U/ml was achieved with the addition of 20 g/L of Al2O3 while the lowest activity of 15.20 ± 0.2 U/mL was obtained in the presence of 0.1 g/L of Al2O3. In fermentation without microparticles as control, the activity was 15.64 ± 3.3 U/mL. Results showed that the maximum PG activity was 2.2-fold higher than control. Additionally, smaller pellets formed with the addition of Al2O3 where the lowest pellet diameter was 955.1 µm when 10 g/L of the microparticle was used. Also, it was noticed that biomass concentration gradually increased with increasing microparticle concentration in the fermentation media. Consequently, the PG activity was significantly increased in microparticle-enhanced shake flask fermentation. In fact, these promising preliminary data can be of significance to improve the enzyme activity in large-scale bioreactors.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: 33Citation - Scopus: 34Exploitation of Agricultural Wastes and By-Products for Production of Aureobasidium Pullulans Y-2311 Xylanase: Screening, Bioprocess Optimization and Scale Up(Springer Verlag, 2017) Yeğin, Sırma; Büyükkileci, Ali Oğuz; Sargın, Sayıt; Göksungur, YektaThe potential of several agricultural wastes and by-products (wheat bran, oat bran, corn cob, brewer’s spent grain, malt sprout, artichoke stem, sugar beet pulp, olive seed, cotton stalk and hazelnut skin) was examined as the substrate for xylanase production by Aureobasidium pullulans Y-2311-1. Based on the screening studies, wheat bran was selected as the best substrate for further optimization studies. The effects of initial medium pH, temperature and incubation time on xylanase production in shake flask system were optimized by response surface methodology (RSM). The optimum levels of the process variables defined by the model (initial medium pH, 4.24; temperature, 30.27 °C; and incubation time 126.67 h) resulted in production of 85.19 U/ml xylanase. Taking the RSM optimized parameters in shake-flask scale into consideration; xylanase production was scaled up to bioreactor system with a working volume of 1.5 l. The peak of enzyme production was achieved after 126 h incubation that has previously been determined by RSM studies at shake flask level. Furthermore, the optimum levels of agitation and aeration in bioreactor system was found as 200 rpm and 1.5 vvm. Maximum enzyme production was close to 85 kU/l which could be translated into a productivity of 0.68 kU/l/h. No previous work considered the statistical optimization of xylanase production by A. pullulans on wheat bran and scale up of the bioprocess to a bioreactor systemArticle Citation - WoS: 21Citation - Scopus: 24Isolation and Identification of Arcobacter Species From Environmental and Drinking Water Samples(Springer Verlag, 2016) Talay, Funda; Molva, Çelenk; Atabay, Halil İbrahimWater plays an important role in the transmission of Arcobacter spp. to animals and humans. The aim of this study was to isolate and characterize Arcobacter spp. from 115 different water samples (66 sewage, 25 rivers, 16 spring water, and 8 drinking water) in Izmir, Turkey. In total, 41 samples (35.7 %) were found positive for Arcobacter spp. by the genus-specific PCR. Arcobacter butzleri was detected in 39 out of 115 samples (33.9 %) including 24 sewage, 13 rivers, and 2 spring water. The remaining Arcobacter spp. (n = 2) isolates could not be identified by m-PCR and 16S rRNA gene sequencing. Based on the phenotypic characterization, most of the Arcobacter species (87.8 %) indicated weak catalase activity. In addition, there were differences in phenotypic patterns among isolated species during growth at 37 °C under microaerobic and aerobic conditions, in the presence of 2 % (39/41) and 3.5 % (32/41) NaCl and 0.04 % TTC (39/41) and on MacConkey agar (38/41). The results of this study indicated that environmental water samples are common sources for Arcobacter spp. Therefore, effective control measures should be taken to protect human health.Article Citation - WoS: 12Citation - Scopus: 16Utilization of Orange Peel, a Food Industrial Waste, in the Production of Exo-Polygalacturonase by Pellet Forming Aspergillus Sojae(Springer Verlag, 2015) Büyükkileci, Ali Oğuz; Lahore, Marcelo Fernandez; Tarı, CananThe production of exo-polygalacturonase (exo-PG) from orange peel (OP), a food industrial waste, using Aspergillus sojae was studied in submerged culture. A simple, low-cost, industrially significant medium formulation, composed of only OP and (NH4)2SO4 (AS) was developed. At an inoculum size of 2.8 × 103 spores/mL, growth was in the form of pellets, which provided better mixing of the culture broth and higher exo-PG activity. These pellets were successfully used as an inoculum for bioreactors and 173.0 U/mL exo-PG was produced. Fed-batch cultivation further enhanced the exo-PG activity to 244.0 U/mL in 127.5 h. The final morphology in the form of pellets is significant to industrial fermentation easing the subsequent downstream processing. Furthermore, the low pH trend obtained during this fermentation serves an advantage to fungal fermentations prone to contamination problems. As a result, an economical exo-PG production process was defined utilizing a food industrial by-product and producing high amount of enzyme.Article Citation - WoS: 29Citation - Scopus: 29Microbial Strain Improvement for Enhanced Polygalacturonase Production by Aspergillus Sojae(Springer Verlag, 2014) Heerd, Doreen; Tarı, Canan; Fernandez Lahore, MarceloStrain improvement is a powerful tool in commercial development of microbial fermentation processes. Strains of Aspergillus sojae which were previously identified as polygalacturonase producers were subjected to the cost-effective mutagenesis and selection method, the so-called random screening. Physical (ultraviolet irradiation at 254 nm) and chemical mutagens (N-methyl-N′-nitro-N-nitrosoguanidine) were used in the development and implementation of a classical mutation and selection strategy for the improved production of pectic acid-degrading enzymes. Three mutation cycles of both mutagenic treatments and also the combination of them were performed to generate mutants descending from A. sojae ATCC 20235 and mutants of A. sojae CBS 100928. Pectinolytic enzyme production of the mutants was compared to their wild types in submerged and solid-state fermentation. Comparing both strains, higher pectinase activity was obtained by A. sojae ATCC 20235 and mutants thereof. The highest polygalacturonase activity (1,087.2±151.9 U/g) in solid-state culture was obtained by mutant M3, which was 1.7 times increased in comparison to the wild strain, A. sojae ATCC 20235. Additional, further mutation of mutant M3 for two more cycles of treatment by UV irradiation generated mutant DH56 with the highest polygalacturonase activity (98.8±8.7 U/mL) in submerged culture. This corresponded to 2.4-fold enhanced polygalacturonase production in comparison to the wild strain. The results of this study indicated the development of a classical mutation and selection strategy as a promising tool to improve pectinolytic enzyme production by both fungal strains.Article Citation - WoS: 1Citation - Scopus: 2Discrimination of Bio-Crystallogram Images Using Neural Networks(Springer Verlag, 2014) Ünlütürk, Sevcan; Ünlütürk, Mehmet S.; Pazır, Fikret; Kuşçu, AlperThis 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; Buzrul, Sencer; Alpas, HamiThe 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: 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: 1Citation - Scopus: 2Process Neural Network Method: Case Study I: Discrimination of Sweet Red Peppers Prepared by Different Methods(Springer Verlag, 2011) Ünlütürk, Sevcan; Ünlütürk, Mehmet S.; Pazır, Fikret; Kuşçu, AlperThis 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.