Growth Characteristics Modeling of Mixed Culture of Bifidobacterium bifidum and Lactobacillus acidophilus using Response Surface Methodology and Artificial Neural Network

Different culture conditions viz. additional carbon and nitrogen content, inoculum size and age, temperature and pH of the mixed culture of Bifidobacterium bifidum and Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted for the cultivations using a Fractional Factorial (FF) design experiments for different variables. This novel concept of combining the optimization and modeling presented different optimal conditions for the mixture of B. bifidum and L. acidophilus growth from their one variable at-a-time (OVAT) optimization study. Through these statistical tools, the product yield (cell mass) of the mixture of B. bifidum and L. acidophilus was increased. Regression coefficients (R2) of both the statistical tools predicted that ANN was better than RSM and the regression equation was solved with the help of genetic algorithms (GA). The normalized percentage mean squared error obtained from the ANN and RSM models were 0.08 and 0.3%, respectively. The optimum conditions for the maximum biomass yield were at temperature 38°C, pH 6.5, inoculum volume 1.60 mL, inoculum age 30 h, carbon content 42.31% (w/v), and nitrogen content 14.20% (w/v). The results demonstrated a higher prediction accuracy of ANN compared to RSM.

Growth characteristics modeling of Lactobacillus acidophilus using RSM and ANN

The culture conditions viz. additional carbon and nitrogen content, inoculum size, age, temperature and pH of Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted to cultivations from a Box-Behnken Design (BBD) design experiments for different variables. This concept of combining the optimization and modeling presented different optimal conditions for L. acidophilus growth from their original optimization study. Through these statistical tools, the product yield (cell mass) of L. acidophilus was increased. Regression coefficients (R²) of both the statistical tools predicted that ANN was better than RSM and the regression equation was solved with the help of genetic algorithms (GA). The normalized percentage mean squared error obtained from the ANN and RSM models were 0.06 and 0.2%, respectively. The results demonstrated a higher prediction accuracy of ANN compared to RSM.

Application of decolourized and partially purified polygalacturonase and α-amylase in apple juice clarification

Polygalacturonase and α-amylase play vital role in fruit juice industry. In the present study, polygalacturonase was produced by Aspergillus awamori Nakazawa MTCC 6652 utilizing apple pomace and mosambi orange (Citrus sinensis var mosambi) peels as solid substrate whereas, α-amylase was produced from A. oryzae (IFO-30103) using wheat bran by solid state fermentation (SSF) process. These carbohydrases were decolourized and purified 8.6-fold, 34.8-fold and 3.5-fold, respectively by activated charcoal powder in a single step with 65.1%, 69.8% and 60% recoveries, respectively. Apple juice was clarified by these decolourized and partially purified enzymes. In presence of 1% polygalacturonase from mosambi peels (9.87 U/mL) and 0.4% α-amylase (899 U/mL), maximum clarity (%T660nm = 97.0%) of juice was attained after 2 h of incubation at 50 ºC in presence of 10 mM CaCl2. Total phenolic content of juice was reduced by 19.8% after clarification, yet with slightly higher %DPPH radical scavenging property.

Optimization of lipid enriched biomass production from oleaginous fungus using response surface methodology.

Oleaginous microorganisms have emerged as potential sources of oils for biodiesel production. To replenish as an alternative to the vegetable oils, higher lipid accumulating strain coupled with process optimization is indispensable. In the present study, response surface methodology (RSM) based central composite design (CCD) was used for optimization of lipid content from oleaginous fungus Aspergillus sp. Maximum lipid yield of 73.07% (w/w) was achieved at 3% (v/v) inoculum volume, pH 5, glucose 1% (w/v), urea 0.5 % (w/v) and incubation time of 5 (days). Biomass (2.08 g/L) having a lipid content of 73.07 % (w/w) with major constituents of hexadecanoic acid methyl ester and 9-Octadecenoic acid methyl ester were obtained. The lipid composition signifies that from the oleaginous microbe are highly encouraging and desirable to be considered as diesel substitute.

Enhanced lipase recovery through RSM integrated differential evolutionary approach from the fermented biomass

The aim of this work was to apply a modeling integrated optimisation approach for a complex, highly nonlinear system for an extracellular lipase extraction process. The model was developed using mutation, crossover and selection variables of Differential Evolution (DE) based on central composite design of Response Surface Methodology. The experimentally validated model was optimized by DE, a robust evolutionary optimization tool. A maximum lipase activity of 134.13 U/gds (more than 36.28 U/gds compared to one variable at a time approach) was observed with the DE-stated optimum values of 25.01% dimethyl sulfoxide concentration, 40 mM buffer, 128.52 min soaking time and 35ºC with the DE control parameters, namely number of population, generations, crossover operator and scaling factor as 20, 50, 0.5 and 0.25, respectively. The use of DE approach improved the optimization capability and decision speed, resulting in an improved yield of 36.28 U/gds compared to the one variable at a time approach for the extracellular lipase activity under the non-optimized conditions. The developed mathematical model and optimization were generic in nature, which seemed to be useful for the scale-up studies of maximum recovery of lipase from the fermented biomass.

Growth characteristics modeling of Bifidobacterium bifidum using RSM and ANN

The aim of this work was to optimize the biomass production by Bifidobacterium bifidum 255 using the response surface methodology (RSM) and artificial neural network (ANN) both coupled with GA. To develop the empirical model for the yield of probiotic bacteria, additional carbon and nitrogen content, inoculum size, age, temperature and pH were selected as the parameters. Models were developed using » fractional factorial design (FFD) of the experiments with the selected parameters. The normalized percentage mean squared error obtained from the ANN and RSM models were 0.05 and 0.1 percent, respectively. Regression coefficient (R²) of the ANN model showed higher prediction accuracy compared to that of the RSM model. The empirical yield model (for both ANN and RSM) obtained were utilized as the objective functions to be maximized with the help of genetic algorithm. The optimal conditions for the maximal biomass yield were 37.4 °C, pH 7.09, inoculum volume 1.97 ml, inoculum age 58.58 h, carbon content 41.74 percent (w/v), and nitrogen content 46.23 percent (w/v). The work reported is a novel concept of combining the statistical modeling and evolutionary optimization for an improved yield of cell mass of B. bifidum 255.

Statistical optimization of culture conditions by response surface methodology for synthesis of lipase with Enterobacter aerogenes

Optimization of lipase production by Enterobacter aerogenes was carried out using response surface methodology (RSM) where the statistical model was obtained by fractional factorial central composite design. The influence of various physico-chemical parameters, viz. temperature, oil concentration, inoculum volume, pH and incubation period on lipase production was examined. Optimization of physico-chemical parameters resulted 1.4- fold increase in lipase activity. The optimum levels of parameters were 34°C, oil concentration 3 percent, inoculum volume 7 percent, pH 7 and incubation time 60 h for obtaining a maximum lipase activity of 27.25 U/ml.

Multivariable parameter optimization for the endoglucanase production by Trichoderma reesei Rut C30 from Ocimum gratissimum seed

The aim of this study was to evaluate the interaction effects of the physico-chemical parameters on the endoglucanase (CMCase) production by Trichoderma reesei Rut C30 on a cellulosic agro-residue by the solid-state fermentation (SSF) and to determine their optimum values by the EVOP factorial design technique. The best combination of physical parameters for the maximum production of the endoglucanase (CMCase) was 28ºC temperature, 79 percent relative humidity and 4.8 pH of the medium. The best combination of the chemical parameters was (mg/L) nicotinic acid 15, naphthalene acetic acid 7, ferric chloride 5 and Tween-80 6. With the application of this technique, the yield of the CMCase increased by ~ 2.3 fold.

Isolation and characterization of a newly isolated Pseudomonas mutant for protease production

Uma bactéria isolada do solo e identificada como Pseudomonas sp. RAJR 044 demonstrou ser uma potencial produtora de protéase extracelular. Um mutante JNGR 242 dessa espécie foi obtido mediante radiação ultravioleta sob condições experimentalmente otimizadas de pH 7,0, temperatura de 34ºC, volume de inóculo de 1,0 mL e tempo de incubação de 24 hora produziu 2,5 mais protease. Também foram realizadas análises comparativas das características química quanto assimilação de diferentes fontes de carbono e de nitrogênio. O crescimento máximo desse mutante na placa de ágar gelatina (2%) foi obtido na presença de sacarose (2%), maltose (2%), sulfato de amônia (2%) e nitrato de potássio (2%), ao passo que no caso da linhagem original a melhor fonte de carbono foi a sacarose (2%) e o nitrato de amônia (2%) como a melhor fonte de nitrogênio. As protéases purificadas de ambas as espécies (original e mutante) mostraram faixas homogêneas que correspondem ao peso molecular 14,4 kDa na SDS-PAGE. Ao se estudar as propriedades cinéticas de ambas as espécies, observou-se que a taxa de hidrólise da caseína era máxima em pH 7,0 e 8,0, , temperaturas de 45ºC e 60ºC para a espécie original e a mutante, respectivamente. Observou-se também que ambas as protéases extracelulares foram inibidas pela serina, isto é, PMSF à concentração de 2mM.

Immobilization of alpha-amylase produced by Bacillus circulans GRS 313

A maltooligosaccharide-forming amylase from B circulans GRS 313 was immobilized by entrapment in calcium alginate beads. The immobilized activity was affected by the size of the bead and bead size of 2mm was found to be most effective for hydrolysis. Kinetics constants, Km and Vmax were estimated and were found to be affected by the bead size. The catalytic activity of the enzyme was studied in presence of various starchy residues and metal ions. HgCl2, CuSO4 and FeCl3 caused inhibition of the enzyme. The reaction conditions, pH and temperature, was optimized using response surface methodology. At the optimum pH and temperature of 4.9 and 57ºC, the apparent activity was 25.6U/g of beads, resulting in almost 2-fold increase in activity. The immobilized enzyme showed a high operational stability by retaining almost 85 percent of the initial activity after seventh use