PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
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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: 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: 8Citation - Scopus: 9Modeling of Polygalacturonase Enzyme Activity and Biomass Production by Aspergillus Sojae Atcc 20235(Springer Verlag, 2009) Tokatlı, Figen; Tarı, Canan; Ünlütürk, Mehmet; Göğüş, NihanAspergillus sojae, which is used in the making of koji, a characteristic Japanese food, is a potential candidate for the production of polygalacturonase (PG) enzyme, which of a major industrial significance. In this study, fermentation data of an A. sojae system were modeled by multiple linear regression (MLR) and artificial neural network (ANN) approaches to estimate PG activity and biomass. Nutrient concentrations, agitation speed, inoculum ratio and final pH of the fermentation medium were used as the inputs of the system. In addition to nutrient conditions, the final pH of the fermentation medium was also shown to be an effective parameter in the estimation of biomass concentration. The ANN parameters, such as number of hidden neurons, epochs and learning rate, were determined using a statistical approach. In the determination of network architecture, a cross-validation technique was used to test the ANN models. Goodness-of-fit of the regression and ANN models was measured by the R 2 of cross-validated data and squared error of prediction. The PG activity and biomass were modeled with a 5-2-1 and 5-9-1 network topology, respectively. The models predicted enzyme activity with an R 2 of 0.84 and biomass with an R 2 value of 0.83, whereas the regression models predicted enzyme activity with an R 2 of 0.84 and biomass with an R 2 of 0.69.Article Citation - WoS: 52Citation - Scopus: 62Solid-State Production of Polygalacturonase by Aspergillus Sojae Atcc 20235(Elsevier Ltd., 2007) Üstok, Fatma Işık; Tarı, Canan; Göğüş, NihanThe effect of solid substrates, inoculum and incubation time were studied using response surface methodology (RSM) for the production of polygalacturonase enzyme and spores in solid-state fermentation using Aspergillus sojae ATCC 20235. Two-stage optimization procedure was applied using D-optimal and face-centered central composite design (CCD). Crushed maize was chosen as the solid substrate, for maximum polygalacturonase enzyme activity based on D-optimal design. Inoculum and incubation time were determined to have significant effect on enzyme activity and total spore (p < 0.01) based on the results of CCD. A second order polynomial regression model was fitted and was found adequate for individual responses. All two models provided an adequate R2 of 0.9963 (polygalacturonase) and 0.9806 (spores) (p < 0.001). The individual optimum values of inoculum and incubation time for maximum production of the two responses were 2 × 107 total spores and 5-6 days. The predicted enzyme activity (30.55 U/g solid) and spore count (2.23 × 107 spore/ml) were very close to the actual values obtained experimentally (29.093 U/g solid and 2.31 × 107 spore/ml, respectively). The overall optimum region considering the two responses together, overlayed with the individual optima. Solid-state fermentation provided 48% more polygalacturonase activity compared to submerged fermentation under individually optimized conditions.