scholarly journals A cleaner production of diosgenin from Dioscorea Zingiberensis Wright biotransformed by Lactobacillus casei

2017 ◽  
pp. 760
Author(s):  
He Chen ◽  
Zhuo Wang ◽  
Guowei Shu
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Conversion Rate ◽  
Lactobacillus Casei ◽  
Inoculum Size ◽  
Cleaner Production ◽  
Single Factor ◽  
Fermentation Conditions ◽  
Predicted Values ◽  
Factor Variable

The effect of 24 probiotics on disogenin production had been conducted in our preliminary work. Consequently, Lactobacillus casei was selected as the fermentation strain with high potential in biotransformation and effects of main parameters on biotransformation were verified through single factor variable experiments. The fermentation conditions were optimized using response surface methodology, which would be helpful to enhance biotransformation efficiency and achieve a high-valued utilization of DZW in diosgenin production. Single factor variable experiments indicated that biotransformation was highly depend on temperature. The conversion rate of saponin reached to (22.1 ± 0.6) %, (15.5 ± 0.3) % and (17.0 ± 0.4) % under each optimal condition of 43°C, 24 hours and 4% inoculum size respectively. According to results of single factor variable experiments, fermentation conditions were optimized through response surface methodology. The 32.4% of conversion rate and 3.95 µg/mL of diosgenin concentration were predicted to be optimal value under the condition of 42°C, 27 hours, 3% inoculum size. The verification results were (32.8 ± 0.9)% of conversion rate and (4.01±0.02) µg/mL of diosgenin concentration under the same conditions, which were close to the predicted values. The conversion rate increased by 41.9% compared to the initial value. Feasibility of converting saponin to diosgenin through probiotics by biotransformation was verified in this paper and the results could be the reference for a cleaner production of diosgenin.

scholarly journals Study on optimal adsorption conditions of norfloxacin in water based on response surface methodology

2022 ◽  
Author(s):  
Ming Zhang ◽  
Kuo Zhang ◽  
Jinpeng Wang ◽  
Runjuan Zhou ◽  
Jiyuan Li ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Reaction Temperature ◽  
Polynomial Regression ◽  
Single Factor ◽  
Solution Ph ◽  
Box Behnken Design ◽  
Simulated Wastewater ◽  
Predicted Values ◽  
Single Factor Experiment

Abstract The waste pomelo peel was pyrolyzed at 400 °C to prepare biochar and used as adsorbent to remove norfloxacin (NOR) from simulated wastewater. The adsorption conditions of norfloxacin by biochar were optimized by response surface methodology (RSM). On the basis of single-factor experiment, the adsorption conditions of biochar dosage, solution pH and reaction temperature were optimized by Box-Behnken Design (BBD), and the quadratic polynomial regression model of response value Y1 (NOR removal efficiency) and Y2 (NOR adsorption capacity) were obtained respectively. The results show that the two models are reasonable and reliable. The influence of single factor was as follows: solution pH > biochar dosage > reaction temperature. The interaction between biochar dosage and solution pH was very significant. The optimal adsorption conditions after optimization were as follows: biochar dosage = 0.5 g/L, solution pH = 3, and reaction temperature = 45 °C. The Y1 and Y2 obtained in the verification experiment were 75.68% and 3.0272 mg/g, respectively, which were only 2.38% and 0.0242 mg/g different from the theoretical predicted values of the model. Therefore, the theoretical model constructed by response surface methodology can be used to optimize the adsorption conditions of norfloxacin in water.

Optimization of Fermentation Conditions for Cold-Active Cellulase Production by Response Surface Methodology

2011 ◽  
Vol 183-185 ◽  
pp. 1025-1029
Author(s):  
Shuo Dong ◽  
Nai Yu Chi ◽  
Qing Fang Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Inoculum Size ◽  
Batch Reactors ◽  
Fermentation Conditions ◽  
Cold Active ◽  
Seed Age ◽  
Cost Efficient

The design of an optimum and cost-efficient fermentation conditions for production of cold-active cellulase by Penicillium cordubense D28 was attempted by using response surface methodology (RSM). Based on the Plackett–Burman design, temperature, seed age and inoculum size were selected as the most critical condition. Subsequently, they were investigated by the Box-Behnken design. Results showed that the maximum cold-active cellulase activity of 110.4U/mL was predicted when the coded values of temperature, seed age and inoculum size were -0.495, 0.455, and 0.253, respectively. The results were further verified by triplicate experiments. The batch reactors were operated under an optimized condition of the respective temperature, seed age and inoculum size of 17°C, 29h and 12.5%. The maximum cold-active cellulase activity of 219.9 U/mL was obtained based on the optimized fermentation conditions with further verified the practicability of this optimum strategy.

scholarly journals Homogenate Extraction of Crocins from Saffron Optimized by Response Surface Methodology

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Yingpeng Tong ◽  
Yu Jiang ◽  
Dan Guo ◽  
Yongqiu Yan ◽  
Shiping Jiang ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Extraction Yield ◽  
Extraction Time ◽  
Process Conditions ◽  
Extraction Temperature ◽  
Single Factor ◽  
Extraction Voltage ◽  
Homogenate Extraction

Saffron, which has many kinds of biological activities, has been widely used in medicine, cosmetics, food, and other fields of health promotion industries. Crocins are the main component of saffron (Crocus sativus L.). At present, most of the extraction methods for crocins require long time or special instruments to complete the process and some of them are not suitable for industrial production at present. In this article, homogenate extraction technology which is a convenient and efficient method was developed for crocins extraction from saffron. Firstly, the influences of extraction voltage, extraction time, ethanol concentration, and temperature on crocins yield were studied by single factor experiments; and then response surface methodology (RSM) was used to optimize levels of four variables based on the result of single factor experiments. Results showed that the optimum extraction process conditions for crocins were as follows: extraction voltage, 110 V; ethanol concentration, 70%; extraction temperature, 57°C; and extraction time, 40 s. Based on these conditions, the extraction yield of crocins can reach 22.76% which is higher than ultrasonic extraction method. Therefore, homogenate extraction is an effective way to extract crocins from saffron with higher extraction yield and shorter extraction time.

scholarly journals Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Oxygen Demand ◽  
Inoculum Size ◽  
Coefficient Of Determination ◽  
Oil Removal ◽  
Box Behnken Design ◽  
Stenotrophomonas Rhizophila ◽  
Crude Oil Removal

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

scholarly journals Optimization of Supercritical Carbon Dioxide Extraction of Quercus infectoria Oil

2015 ◽  
Vol 74 (7) ◽  
Author(s):  
Liza Md Salleh ◽  
Stashia ELeaness Rosland Abel ◽  
Gholamreza Zahedi ◽  
Russly Abd Rahman ◽  
Hasmida Mohd Nasir ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Goodness Of Fit ◽  
Maximum Yield ◽  
Extraction Yield ◽  
Extraction Time ◽  
Extraction Temperature ◽  
Predicted Values ◽  
Artificial Neural Network Ann ◽  
Quercus Infectoria

This current study focuses on the modelling and optimization of supercritical fluid extraction of Quercus infectoria galls oil. In this case, response surface methodology (RSM) and artificial neural network (ANN) were applied for the modelling and prediction of extraction yield of galls oil. A 17-run Box-Behnken Design (BBD) was employed to statistically optimize the process parameters of SC-CO2 extraction of Quercus infectoria galls at a condition as follows: pressure (5000, 6000, 7000 Psi), temperature (40, 50, 60°C) and extraction time (30, 45, 60 min). The maximum yield of the extracted oil is1.12 % and the optimum conditions are at an extraction pressure of 5574 Psi; extraction temperature of 75°C and extraction time of 54 min. Under the optimal conditions, the experimental results agree with the predicted values obtained through analysis of variance (ANOVA). This indicates a successful response surface methodology and highly satisfactory goodness of fit of the model used. The analysis of experimental design for process optimization results demonstrates that temperature and extraction time are the main parameters that influence the oil extraction of Quercus infectoria.

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