Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article Citation - WoS: 3Citation - Scopus: 4Evaluation of Agro-Industrial Wastes, Their State, and Mixing Ratio for Maximum Polygalacturonase and Biomass Production in Submerged Fermentation(Taylor and Francis Ltd., 2015) Göğüş, Nihan; Evcan, Ezgi; Tarı, Canan; Cavalitto, Sebastian F.The potential of important agro-industrial wastes, apple pomace (AP) and orange peel (OP) as C sources, was investigated in the maximization of polygalacturonase (PG), an industrially significant enzyme, using an industrially important microorganism Aspergillus sojae. Factors such as various hydrolysis forms of the C sources (hydrolysed-AP, non-hydrolysed-AP, hydrolysed-AP + OP, non-hydrolysed-AP + OP) and N sources (ammonium sulphate and urea), and incubation time (4, 6, and 8 days) were screened. It was observed that maximum PG activity was achieved at a combination of non-hydrolysed-AP + OP and ammonium sulphate with eight days of incubation. For the pre-optimization study, ammonium sulphate concentration and the mixing ratios of AP + OP at different total C concentrations (9, 15, 21 g-1) were evaluated. The optimum conditions for the maximum PG production (144.96 ml-1) was found as 21 g-1 total carbohydrate concentration totally coming from OP at 15 g-1 ammonium sulphate concentration. On the other hand, 3:1 mixing ratio of OP + AP at 11.50 g-1 ammonium sulphate concentration also resulted in a considerable PG activity (115.73 ml-1). These results demonstrated that AP can be evaluated as an additional C source to OP for PG production, which in turn both can be alternative solutions for the elimination of the waste accumulation in the food industry with economical returns.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.