scholarly journals MEDIUM OPTIMIZATION FOR THE PRODUCTION OF BIOMASS BY Cunninghamella sp. 2A1 USING RESPONSE SURFACE METHODOLOGY

2017 ◽  
Vol 22 (3) ◽  
pp. 223
Author(s):  
Siti Aminah Sulaiman ◽  
Aidil Abdul Hamid ◽  
Wan Mohtar Wan Yusoff
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Linear Model ◽  
Medium Optimization ◽  
Statistical Design ◽  
Design Approach ◽  
P Value ◽  
Ammonium Tartrate ◽  
Combined Effects

A statistical design approach has been used to optimize the production of biomass byCunninghamellasp. 2A1, evaluated based on lipidless biomass. A 23full factorial centralcomposite design (CCD) was chosen to study the combined effects of three factors; ammoniumtartrate, peptone and glucose concentrations. The p-value for each factors was < 0.05 suggestingthat these factors have significant effect on the production of lipidless biomass. The productionis represented by a linear model with p-value < 0.0001. The optimized medium consists of 3.86g/l ammonium tartrate, 55.84 g/l glucose and 7.73 g/l peptone predicted 16.83 g/l lipidlessbiomass. Results from four replications based on the optimized medium produced 18.48 g/llipidless biomass, which are in close agreementwith the predicted value. The coefficient forglucose was the highest indicating it as the most significant factoraffecting lipidless biomassproduction. 

Employment of Quality by Design approach via Response Surface Methodology to Optimize and Develop Modified Release formulation of Hydrochlorothiazide

2020 ◽  
Vol 16 ◽  
Author(s):  
Vikas D Singhai ◽  
Rahul Maheshwari ◽  
Swapnil Sharma ◽  
Sarvesh Paliwal
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quality By Design ◽  
Management Tool ◽  
Contour Plot ◽  
P Value ◽  
Average Weight ◽  
Content Uniformity ◽  
Modified Release ◽  
Release Formulation

Background: Heart attack predominantly occurs during the last phase of sleep and early morning hours, causing millions of death worldwide. Hydrochlorothiazide (HCTZ) is recommended drug for the prevention of heart disease but its long action (>4 h) dosage form is lacking in the commercial market and development of extended-release formulation may have industrial significance. Regulatory agencies emphasize Quality by Design based approach for product development to entrust quality in the product. Objective: Aim of the current research was to develop a quality product profile of HCTZ modified-release tablets (MRT; ~14 h) by applying Response Surface Methodology using computational QbD approach. Methods: Three independent factors were identified by qualitative and quantitative risk assessment. Statistical terms like p-value, lack of fit, sum of square, R-squared value, model F value and linear equations were determined. Graphical tools like normal plot of residual, residual vs predicted plot and box cox plot were used to verify model selection. Graphical relationship among the critical, independent variables was represented using the Contour plot and 3-D surface plot. Design space was identified by designing overlay plot using response surface design. Results: Excellent correlation was observed between actual and predicted values. Similarity Factor (F2) of reproducible trials was 78 and 79 and content uniformity was 100.9% and 100.4%. Average weight, hardness, thickness, diameter and friability were within acceptable limits. Conclusions: QbD approach along with quality risk management tool provided an efficient and effective paradigm to build quality MRT of HCTZ.

scholarly journals Effective Chromium Adsorption From Aqueous Solutions and Tannery Wastewater Using Bimetallic Fe/Cu Nanoparticles: Response Surface Methodology and Artificial Neural Network

2021 ◽  
Vol 14 ◽  
pp. 117862212110281
Author(s):  
Ahmed S. Mahmoud ◽  
Nouran Y. Mohamed ◽  
Mohamed K. Mostafa ◽  
Mohamed S. Mahmoud
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Industrial Effluent ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Tannery Wastewater ◽  
P Value ◽  
Cu Nanoparticles ◽  
Artificial Neural ◽  
Cr Removal

Tannery industrial effluent is one of the most difficult wastewater types since it contains a huge concentration of organic, oil, and chrome (Cr). This study successfully prepared and applied bimetallic Fe/Cu nanoparticles (Fe/Cu NPs) for chrome removal. In the beginning, the Fe/Cu NPs was equilibrated by pure aqueous chrome solution at different operating conditions (lab scale), then the nanomaterial was applied in semi full scale. The operating conditions indicated that Fe/Cu NPs was able to adsorb 68% and 33% of Cr for initial concentrations of 1 and 9 mg/L, respectively. The removal occurred at pH 3 using 0.6 g/L Fe/Cu dose, stirring rate 200 r/min, contact time 20 min, and constant temperature 20 ± 2ºC. Adsorption isotherm proved that the Khan model is the most appropriate model for Cr removal using Fe/Cu NPs with the minimum error sum of 0.199. According to khan, the maximum uptakes was 20.5 mg/g Cr. Kinetic results proved that Pseudo Second Order mechanism with the least possible error of 0.098 indicated that the adsorption mechanism is chemisorption. Response surface methodology (RSM) equation was developed with a significant p-value = 0 to label the relations between Cr removal and different experimental parameters. Artificial neural networks (ANNs) were performed with a structure of 5-4-1 and the achieved results indicated that the effect of the dose is the most dominated variable for Cr removal. Application of Fe/Cu NPs in real tannery wastewater showed its ability to degrade and disinfect organic and biological contaminants in addition to chrome adsorption. The reduction in chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), Cr, hydrogen sulfide (H2S), and oil reached 61.5%, 49.5%, 44.8%, 100%, 38.9%, 96.3%, 88.7%, and 29.4%, respectively.

scholarly journals A Response Surface Methodology (RSM) Approach for Optimizing the Attenuation of Human IgE-Reactivity to β-Lactoglobulin (β-Lg) by Hydrostatic High Pressure Processing

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1741
Author(s):  
Xin Sun ◽  
Jialing Vivien Chua ◽  
Quynh Anh Le ◽  
Francisco Trujillo ◽  
Mi-Hwa Oh ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Optimal Condition ◽  
Response Surface ◽  
High Pressure Processing ◽  
Molecular Structures ◽  
Holding Time ◽  
P Value ◽  
Molecular Change ◽  
Ige Reactivity ◽  
Β Lactoglobulin

The response surface methodology (RSM) and central composite design (CCD) technique were used to optimize the three key process parameters (i.e., pressure, temperature and holding time) of the high-hydrostatic-pressure (HHP) processing either standalone or combined with moderate thermal processing to modulate molecular structures of β-lactoglobulin (β-Lg) and α-lactalbumin (α-La) with reduced human IgE-reactivity. The RSM model derived for HHP-induced molecular changes of β-Lg determined immunochemically showed that temperature (temp), pressure (p2) and the interaction between temperature and time (t) had statistically significant effects (p < 0.05). The optimal condition defined as minimum (β-Lg specific) IgG-binding derived from the model was 505 MPa at 56 °C with a holding time of 102 min (R2 of 0.81 and p-value of 0.01). The validation carried at the optimal condition and its surrounding region showed that the model to be underestimating the β-Lg structure modification. The molecular change of β-Lg was directly correlated with HHP-induced dimerization in this study, which followed a quadratic equation. The β-Lg dimers also resulted in the undetectable human IgE-binding.

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 Medium optimization for palmarumycin C13 production in liquid culture of endophytic fungus Berkleasmium sp. Dzf12 using response surface methodology

2013 ◽  
Vol 16 (6) ◽  
Author(s):  
Ligang Zhou ◽  
Jianglin Zhao ◽  
Weibo Sun ◽  
Xiaohan Wang ◽  
Yan Mou ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Endophytic Fungus ◽  
Liquid Culture ◽  
Medium Optimization

scholarly journals Optimization of pretreating poplar wood shavings with cellulase to produce binderless fiberboard using response surface methodology

BioResources ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 6431-6441
Author(s):  
Jianguo Wu ◽  
Yuanyuan Wang ◽  
Zhao Zhang ◽  
Xuanxian Luo ◽  
Chi Wang ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Bending Strength ◽  
Good Choice ◽  
P Value ◽  
Poplar Wood ◽  
Wood Processing ◽  
Wood Shavings ◽  
Validation Experiment ◽  
Pretreatment Conditions

Wood processing waste, poplar wood shavings, were used for fiberboard production, and the pretreatment conditions using cellulase were studied using response surface methodology (RSM). After single factors optimization, central level of temperature, dosage, and liquid/solid ratio (LSR) of cellulase pretreatment conditions were obtained. Further optimization to study the influence of the factors was carried out using Box-Behnken design of experiments. A second-order polynomial equation was obtained, and the low p-value (<0.007) implied that the model was highly significant by analysis of variance (ANOVA). The optimized cellulase pretreatment conditions for maximum bending strength (BS) of the fiberboard were determined by ridge analysis as 44.4 °C of temperature, 1.23 U/g of dosage, 4.2 of LSR, and 5 h of pretreatment time. Under the optimized conditions, the BS of the fiberboard reached 25.12 ± 0.35 MPa by validation experiment, which was twice that of the fiberboard without pretreatment. Thus, the cellulase pretreatment should be a good choice to produce high-strength binderless fiberboard.

scholarly journals Optimization of Coagulation-Flocculation Process of Landfill Leachate by Tin (IV) Chloride Using Response Surface Methodology

2019 ◽  
Vol 6 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Abdul Aziz Hamidi ◽  
Syed Zainal Sharifah Farah Fariza ◽  
Alazaiza Motasem Y.D
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Landfill Leachate ◽  
Chemical Properties ◽  
Oxygen Demand ◽  
Statistical Design ◽  
Water Infiltration ◽  
Flocculation Process ◽  
Maximum Removal

Landfill leachate is highly polluted and generated as a result of water infiltration through solid waste produced domestically and industrially. This study investigated the applicability of the response surface methodology (RSM) to optimize the removal performances of chemical oxygen demand (COD), color, and suspended solids (SS) from landfill leachate by coagulation process using Tin tetrachloride pentahydrate. The leachate samples were collected from Alor Pongsu Landfill (APLS) in Perak, Malaysia. Before starting the experiments, general characterization was carried out for raw leachate samples to investigate their physical and chemical properties. The effects of the dosage and pH of SnCl4 on the removal performances were evaluated as well. An ideal experimental design was performed based on the central composite design (CCD) by RSM. In addition, this RSM was used to evaluate the effects of process variables and their interaction toward the attainment of their optimum conditions. The statistical design of the experiments and data analysis was resolved using the Design-Expert software. Further, the range of coagulant dosage and pH was selected based on a batch study which was conducted at 13000 mg/L to 17000 mg/L of SnCl4 and pH ranged from 6 to 10. The results showed that the optimum pH and dosage of SnCl4 were 7.17 and 15 g/L, respectively, where the maximum removal efficiency was 67.7% for COD and 100% for color and SS. The results were in agreement with the experimental data with a maximum removal efficiency of 67.84 %, 98.6 %, and 99.3%, for COD, color, and SS, respectively. Overall, this study verified that the RSM method was viable for optimizing the operational condition of the coagulation-flocculation process.

Medium optimization for the production of thermal stable β-glucanase by Bacillus subtilis ZJF-1A5 using response surface methodology

2004 ◽  
Vol 93 (2) ◽  
pp. 175-181 ◽  
Author(s):  
Xing-Jun Tang ◽  
Guo-Qing He ◽  
Qi-He Chen ◽  
Xiu-Yan Zhang ◽  
Mokhtar A.M Ali
Keyword(s):  
Response Surface Methodology ◽  
Bacillus Subtilis ◽  
Response Surface ◽  
Medium Optimization ◽  
Thermal Stable
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