39 research outputs found
Feasibility of distillers dried grain with solubles (DDGS) for production of cellulase and xylanase enzymes cocktail
No full textBacterial cellulase production using grape pomace hydrolysate by shake-flask submerged fermentation
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Improvement of Pectinase Production by Co-culture of Bacillus spp. Using Apple Pomace as a Carbon Source
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Cost-effective approach to ethanol production and optimization by response surface methodology
No full textFood wastes disposed from residential and industrial kitchens have gained attention as a substrate in microbial fermentations to reduce product costs. In this study, the potential of simultaneously hydrolyzing and subsequently fermenting the mixed carbohydrate components of kitchen wastes were assessed and the effects of solid load, inoculum volume of baker's yeast, and fermentation time on ethanol production were evaluated by response surface methodology (RSM). The enzymatic hydrolysis process was complete within 6 h. Fermentation experiments were conducted at pH 4.5, a temperature of 30 C, and agitated at 150 rpm without adding the traditional fermentation nutrients. The statistical analysis of the model developed by RSM suggested that linear effects of solid load, inoculum volume, and fermentation time and the quadratic effects of inoculum volume and fermentation time were significant (P 90% accuracy. An optimum ethanol concentration of 32.2 g/l giving a yield of 0.40 g/g, comparable to yields reported to date, was suggested by the model with 20% solid load, 8.9% inoculum volume, and 58.8 h of fermentation. The results indicated that the production costs can be lowered to a large extent by using kitchen wastes having multiple carbohydrate components and eliminating the use of traditional fermentation nutrients from the recipe
A Statistical Optimization Study on Dilute Sulfuric Acid Pretreatment of Distillers Dried Grains with Solubles (DDGS) As a Potential Feedstock for Fermentation Applications
No full textDistillers dried grains with solubles (DDGS) are co-product of dry-grind ethanol plant, which can be used as a feedstock for fermentation, e.g. for biofuels or other value-added products. However, DDGS loading is a critical factor in the pretreatment, hydrolysis, and fermentation, where the low DDGS loading lowers sugar concentration in the hydrolysate and yields low product concentrations, which can result in high energy cost at the recovery step, while too high loading may have inhibitory effects on the microbial growth during fermentation. Therefore, an optimal DDGS loading needs to be determined at the pretreatment step for high sugar yields. In this study, dilute sulfuric acid pretreatment of DDGS was optimized to obtain the high release of sugars with the use of high DDGS loading at an appropriate acid concentration. An experimental design was constructed with the Box-Behnken response surface method using the ranges of 5-20% (wt) DDGS, 1-5% (wt) H2SO4, and 20-60 min pretreatment times at a constant temperature of 120 degrees C. The results revealed the highest yields of sugars (0.39 g/g) at 20% DDGS, 5% (wt) H2SO4, and 120 degrees C after 1 h. The results justify complete hydrolysis of hemicellulose and residual starch fractions and provide sufficient amount of sugars for the fermentation process
Optimising clarification of carrot juice by bacterial crude pectinase
No full textThis study was undertaken to search for potential use of crude bacterial pectinase enzyme produced from Bacillus subtilis grown on hazelnut shell hydrolysate in clarification of carrot juice and to optimize the enzyme load, pH and time using the Box-Behnken response surface methodology (RSM). The carrot juice was treated with the crude pectinase enzyme (5.60 U mL(-1)) at different concentrations (0.1-0.5%), pH (4-7), and time (2-6 h). The obtained enzyme was also compared with commercial fungal pectinase at identical conditions. RSM provided optimal clarification conditions of 0.5% (w/v) enzyme load, 7.0 pH, and 6 h of time estimating 100% clarity, whose experimental counterpart was 94.47 +/- 0.01%. High values of coefficient of determination (R-2 = 0.9631), predicted R-2 (0.8989) and insignificant lack-of-fit (0.12) also showed that the model was successful in predicting % clarity for various combinations. This study also indicated that crude bacterial pectinase providing about 95% clarity is superior to commercial fungal pectinase, which gave 78% clarity under tested conditions, in terms of clarification ability for carrot juice
Comparison of Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) Models in Simulating Polygalacturonase Production
No full textThe artificial neural network (ANN) method was used in comparison with the adaptive neuro-fuzzy inference system (ANFIS) to describe polygalacturonase (PG) production by Bacillus subtilis in submerged fermentation. ANN was evaluated with five neurons in the input layer, one hidden layer with 7 neurons, and one neuron in the output layer. Five fermentation variables (pH, temperature, time, yeast extract concentration, and K2HPO4 concentration) served as the input of the ANN and ANFIS models, and the polygalacturonase activity was the output. Coefficient of determination (R2) and root mean square values (RMSE) were calculated as 0.978 and 0.060, respectively for the best ANFIS structure obtained in this study. The R2 and RMSE values were computed as 1.00 and 0.030, respectively for the best ANN model. The results showed that the ANN and ANFIS models performed similarly in terms of prediction accuracy
