Desirability Function Methodology Research Articles

Investigation on biogas production process from chicken processing industry wastewater using statistical analysis: Modelling and optimization

In this present study, biogas production process was investigated using four factors—three level Box-Behnken statistical experimental design under different anaerobic conditions such as pH (4–10), temperature (25–45 °C), alkalinity dose (6%–24%), and time (6–30 days) from chicken processing industry wastewater. The obtained results were analyzed by analysis of variance and the second order polynomial model was developed to study the interactive effect of process conditions on the biogas yield. Optimum conditions for maximizing the biogas yield were determined using derringer's desired function methodology and it was found to be pH of 7, temperature of 40 °C, alkalinity dose of 16%, and time of 21 days. Under optimum conditions, predicted biogas yield was found to be 905 ml with a desirability value of 0.985. Suitability of the predicted optimum conditions was validated using experimental data.

Multi-response Optimization of Pectinase Processing Conditions on Blueberry Juice Extraction by Desirability Function Methodology

Response Surface Methodology (RSM) was employed to analyze the effect of pectinase processing on Juice Yield (JY), Total Anthocyanin content (TA), Total Phenol content (TP) and Total Flavonoid content (TF) of blueberry juice. The processing conditions included enzyme dosage, hydrolysis temperature and hydrolysis time. For resolving multi-response optimization, desirability function method was used to integrate JY, TA, TP and TF into a new target D (Desirability value). Predicted values of JY, TA, TP, TF and D were found to be in good agreement with experimental values as indicated by the high R 2 values of 0.9963, 0.9217, 0.9586, 0.9901 and 0.9933, respectively. The optimum conditions were: enzyme dosage of 0.6 mg/g, hydrolysis temperature of 51.6°C and hydrolysis time of 2.36 h. At this optimum point, JY, TA, TP, TF and D were 71.406%, 420.367 mg/L, 2.784 g/L, 3.121 g/L and 0.9206, respectively. The study showed that RSM was an effective technique to model the effect of pectinase processing on blueberry juice parameters and desirability function method could be used for multi- response optimization of blueberry juice extraction.

A composite desirability function-based modeling approach in predicting mass condensate flux of condenser in seawater greenhouse

The main aim of this paper was the development of a new empirical model based on the composite desirability function methodology for predicting mass condensate flux of a condenser in a seawater greenhouse located at Al-Hail, Muscat, Oman. The computational analyses were conducted for simulating relative humidity of inlet dry air, inlet temperature of humid air (dry bulb temperature), temperature of the seawater at the inlet, mass flow of humid air input, and mass flow of seawater at the inlet. The performance of the proposed empirical model was assessed by means of various descriptive statistical indicators. The comparison of the proposed approach with existing condensation data exhibits very good precision of the developed composite desirability function-based model in predicting the mass condensate flux for the condenser process. The proposed mathematical formulation eliminated the various complex variable interactions and many unit conversions usually carried out in the theoretical approach.

Statistical based media optimization and production of naringinase using Aspergillus brasiliensis 1344

Statistics based optimization, Plackett–Burman design (PBD) and response surface methodology (RSM) were employed to screen and optimize the media components for the production of naringinase from Aspergillus brasiliensis MTCC 1344, using solid state fermentation. Cassava waste (CW) was used as both the solid support and carbon source for the growth of A. brasiliensis. Based on the positive influence of the Pareto chart obtained from PBD on naringinase activity, three media components – maltose, peptone and calcium chloride were screened. Box–Behnken design (BBD) was employed using these three factors at three levels, for further optimization, and the second order polynomial equation was derived, based on the experimental data. Derringer's desired function methodology showed that the concentrations of maltose (7.74g/L), peptone (4.19g/L) and calcium chloride (7.63mM) were the optimal levels for maximal naringinase activity (889.91U/mg) which were validated through experiments.

MODEL DEVELOPMENT AND PROCESS OPTIMIZATION FOR SOLVENT EXTRACTION OF POLYPHENOLS FROM RED GRAPES USING BOX–BEHNKEN DESIGN

The objective of the present study is to find out the optimum extraction conditions for extraction of polyphenols from red grapes using Box–Behnken design. Red grapes polyphenols were extracted using acid–ethanol solvent at various extraction temperature (40–60°C), extraction time (20–100 min) and different solid–liquid ratio (1:5–1:15 g:ml). The effect (main and interactive) of extraction conditions on total anthocyanin, phenolic and flavonoid content were studied using Box–Behnken design (three factors at three levels). The results showed that the contribution of the quadratic model was significant for all the responses. Second-order mathematical regression models were developed and were found to fit well with observed data. Derringer's desirability function methodology was performed to find out the optimal conditions based on both individual and combinations of all responses (extraction temperature: 57°C, time: 61 min, and solid–liquid ratio: 1:8.7 g:ml) were established. At this optimal condition, the anthocyanin yield, total phenolic and flavonoid content were 73.92 mg/100 g, 221.4 mg GAE/100 g, and 79.08 mg CE/100 g, respectively. A desirability value of 0.902 was achieved at this point.

Microwave assisted extraction of pectin from waste Citrullus lanatus fruit rinds

In this present study, microwave-assisted extraction (MAE) was applied to extraction of pectin from waste Citrullus Lanatus fruit rinds. Extraction parameters which are employed in this study are microwave power (160–480W), irradiation time (60–180s), pH (1–2) and solid–liquid ratio (1:10–1: 30g/ml) and they were optimized using a four factor three levels Box–Behnken response surface design (BBD) coupled with desirability function methodology. The results showed that, all the process variables have significant effect on the extraction yield of pectin. Optimum MAE conditions for the highest pectin yield from waste C. Lanatus fruit rinds (25.79%) were obtained with microwave power of 477W, irradiation time of 128 s, pH of 1.52, solid–liquid ratio of 1:20.3g/ml respectively. Validation experiment results were well agreed with predicted value.

Modeling and optimization of betalain extraction from Opuntia ficus-indica using Box–Behnken design with desirability function

The extraction of betalain and color from prickly pear (Optunia ficus indica) fruits was optimized using Box–Behnken response surface design coupled with numerical optimization technique. The individual and interactive effect of process variables (temperature, time, mass and pH) on the extracted betalain concentration and color of the extract were studied. The results showed that, temperature, mass and time had significant effect on the betalain and color extraction from prickly pears fruit. The experimental data obtained were analyzed by Pareto analysis of variance (ANOVA) and second-order polynomial models were developed using multiple regression analysis. The models developed from the experimental design were predictive and good fit with the experimental data with high coefficient of determination (R2) values (more than 0.95). An optimization study using Derringer's desired function methodology was performed and the optimal extraction conditions were found to be extraction temperature of 42°C, time of 115min mass of 1.2g and pH of 6.9. The corresponding predicted values were 41.54mg/100g for betalain concentration and 21.35 for color respectively.

Optimization of microwave assisted extraction of pectin from orange peel

In this study, microwave-assisted extraction was applied for pectin extraction from the dried orange peel and Box–Behnken response surface design was used to study and optimize the effects of processing variables (microwave power, irradiation time, pH and solid–liquid ratio) on the yield of pectin. The amount of pectin extracted increased with increasing microwave power, while it reduces as the time, pH and solid–liquid ratio increased. From the results, second order polynomial model was developed and it adequately explained the data variation and significantly represented the actual relationship between independent variables and the response. An optimization study using Derringer's desired function methodology was performed and optimal conditions based on both individual and combinations of all independent variables (microwave power of 422W, irradiation time of 169s, pH of 1.4 and solid–liquid ratio of 1:16.9g/ml) were determined with maximum pectin yield of 19.24%, which was confirmed through validation experiments.

Box-Behnken design based multi-response analysis and optimization of supercritical carbon dioxide extraction of bioactive flavonoid compounds from tea (Camellia sinensis L.) leaves

The popularity of tea is increasing on the global aspect because of its role as a significant source of phenolic compounds in human diet. The objectives of this present study is to develop a supercritical carbon dioxide (SC-CO2) extraction method suitable for extraction of phenolic compounds such as total phenolics, flavonoids and tannin from tea leaves at various extraction conditions such as extraction pressure (100–200 bar), temperature (40–60 °C) and co-solvent (ethanol) flow rate (1–3 g/min). Furthermore, the total antioxidant activity of the SC-CO2 tea leaves extracts was assessed using ABTS+ (2, 2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid)) method. Response surface methodology (RSM) combined with Box-Behnken design was used to investigate and optimize the process variables. The results showed that, extraction pressure and co-solvent flow rate have significant effect on the responses. From the experimental data, second order polynomial mathematical models were developed for each response with high coefficient of determination value (R2 > 0.95). An optimization study using Derringer’s desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variables (extraction pressure of 188 bar, temperature of 50 °C and co-solvent flow rate of 2.94 g/min) were determined with maximum total phenolic content of 131.24 mg GAE/100 ml, total flavonoid content of 194.60 mg QE/100 ml, total tannin content of 49.99 mg TAE/100 ml and totalantioxidant activity of 262.23 μMol TEAC/100 ml of extracts respectively with a overall desirability value of 0.983, which was confirmed through validation experiments.

Ultrasound assisted extraction of bioactive compounds from Nephelium lappaceum L. fruit peel using central composite face centered response surface design

In this study, four factors at three level central composite face centered design was employed to study and optimize the process variables on extraction of bioactive compounds (total anthocyanin, phenolic and flavonoid content) from Nephelium lappaceum L. fruit peel. The effect of process variables such as extraction temperature (30–50°C), power of ultrasound (20–40W), extraction time (10–30min) and solid–liquid ratio (1:10–1:20g/ml) is studied. Multiple regression analysis was done on the experimental data to develop second-order polynomial models with high coefficient of determination value (R2>0.99). The optimal conditions based on both individual and combinations of all process variables (extraction temperature of 50°C, ultrasound power of 20W, extraction time of 20min and solid–liquid ratio of 1:18.6g/ml) were determined by Derringer’s desired function methodology. Under these conditions, total anthocyanin (10.26±0.39 (mg/100g)), phenolics (552.64±1.57 (mg GAE/100g)) and flavonoid (104±1.13 (mgRE/100g)) content values were determined and it is closely related with the predicted values (10.17mg/100g of total anthocyanin, 546.98mgGAE/100g of total phenolics and 100.93mgRE/100g of total flavonoid content) and indicted the suitability of the developed models.

Box–Behnken design based statistical modeling for ultrasound-assisted extraction of corn silk polysaccharide

In this study, ultrasound assisted extraction (UAE) conditions on the yield of polysaccharide from corn silk were studied using three factors, three level Box–Behnken response surface design. Process parameters, which affect the efficiency of UAE such as extraction temperature (40–60°C), time (10–30min) and solid–liquid ratio (1:10–1:30g/ml) were investigated. The results showed that, the extraction conditions have significant effects on extraction yield of polysaccharide. The obtained experimental data were fitted to a second-order polynomial equation using multiple regression analysis with high coefficient of determination value (R2) of 0.994. An optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variables (extraction temperature of 56°C, time of 17min and solid–liquid ratio of 1:20g/ml) were determined with maximum polysaccharide yield of 6.06%, which was confirmed through validation experiments.

Response surface modeling and optimization of process parameters for aqueous extraction of pigments from prickly pear (Opuntia ficus-indica) fruit

The objectives of this study are to determine the optimum conditions for the aqueous extraction of pigments from prickly pear fruit using a three-level three-factor Box–Behnken design under response surface methodology. Pigments were extracted from prickly pears using water as solvent at different extraction temperature (30–50 °C), time (20–120 min) and mass of fruit (0.5–1.5 g). The experimental data obtained were analyzed by Pareto analysis of variance (ANOVA) and fitted to a second-order polynomial equation using multiple regression analysis. An optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all responses (extraction temperature of 40 °C, time of 115 min and mass of 1.44 g) were determined. At this optimum condition, the total betacyanin and betaxanthin content were found to be 13.4354 mg/100 g and 24.2922 mg/100 g with desirability value of 0.917. The experimental values agreed with those predicted values.

Composite desirability function‐based empirical modeling for packed tower design in physical ammonia absorption

ABSTRACTThis paper describes two new empiricial models based on the composite desirability function methodology for the prediction of packed column diameter and packing height in solving problems of physical ammonia absorption. The computational analysis including a total of 131 absorption scenarios were conducted for six fundamental operating parameters such as inlet gas flow rate (500–5000 m3/h), solute concentration in the inlet gas (5–10%), desired removal efficiency (87–98%), operating temperature (10–60 °C), percentage of the minimal liquid‐to‐gas flow rates ratio (24–52%) and percent of flooding velocity (30–80%). The ceramic Raschig rings were selected as one of the most common packing types for the present analysis. The column diameter to packing size ratio were considered to be greater than 30 for a total of 500 packing sizes (0.01–5 inches in diameter) included in the numerical cycle. New non‐linear regressions as the functions of packing factor, packing size and various transfer unit constants (α, β, γ, η and ϕ) were implemented in the prediction scheme of the proposed empirical models. The performance of the models was evaluated with various descriptive statistical indicators. The testing results showed that all predictions were proven to be satisfactory with very high determination coefficients of about R2 = 0.997 and R2 = 0.963 for the packed column diameter and required packing height, respectively. © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.

CP Severity Index: A Reliable Scoring System to Assess Severity and Progression of Chronic Pancreatitis

Background: Chronic pancreatitis (CP) is a syndrome characterized by structural changes in the pancreas that lead to chronic abdominal pain and varying degree of pancreatic functional failure. It has difficult to assess the severity and progression of CP based upon pancreatic duct (PD) changes alone. The aims of this study were: (1) to develop a 'CP severity index' to assess the severity of CP; and (2) correlate the 'CP severity index' with different clinical outcomes in the natural history of CP. Patients and Methods: A prospective study of subjects with established CP was performed at the Pancreatitis Center of the VCU Medical Center, Richmond, VA. Baseline clinical, laboratory and radiologic findings were recorded. Patients were followed in the pancreatitis clinic at 6-month intervals or as the clinical situation warranted. Desirability function methodology was used to develop the CP severity score which ranges between 0 (most severe) and 1 (not severe). Of the 14 recorded variables, on the a stepwise ordinal logistic regression analysis, 8 variables were selected based on a stepwise ordinal logistic regression and combined into a 'pancreatitis severity score' alcohol use, side branch size, side branch ectasia (SBE >3),main PD (MPD) irregularity, MPD stricture, MPD leak, MPD calculi, and contour abnormality of the bile duct. The key outcomes assessed included: exocrine failure, endocrine insufficiency (diabetes), presence or development of a pseudocyst and bile duct stricture. An ordinal 'response' score was created at baseline and at one-year followup, which counted the number of the above outcomes in each patient. Results: Eighty nine subjects with CP (mean age 48 yrs, 54% males) were evaluated, of whom 48 (54%) were African American and 41 (46%) were Caucasian. On independent ordinal regression analysis, only the side branch size correlated with the severity of CP (p= 0.03). The 'CP severity score' significantly correlated with the number of adverse outcomes in CP (p=0.038) and was negatively associated with the number of outcomes. The average CP severity score in subjects with none, one, two, three and four adverse outcomes was 0.74, 0.70, 0.63, 0.60 and 0.43, respectively. For each 0.1 unit increase in the CP severity score the odds of moving to more adverse outcomes decreased by 0.85 times. Conclusions: The 'CP severity score' significantly correlates with the severity of CP. The 'CP severity index' reliably predicts the progression of CP by taking into consideration both imaging changes as well as behavioral risk factors as ongoing alcohol use.

13 C-Di-Peptide Breath Test to Assess Exocrine Pancreatic Function in Chronic Pancreatitis: A Novel Non-Invasive Method

Background: Chronic pancreatitis (CP) is a syndrome characterized by structural changes in the pancreas that lead to chronic abdominal pain and varying degree of pancreatic functional failure. It has difficult to assess the severity and progression of CP based upon pancreatic duct (PD) changes alone. The aims of this study were: (1) to develop a 'CP severity index' to assess the severity of CP; and (2) correlate the 'CP severity index' with different clinical outcomes in the natural history of CP. Patients and Methods: A prospective study of subjects with established CP was performed at the Pancreatitis Center of the VCU Medical Center, Richmond, VA. Baseline clinical, laboratory and radiologic findings were recorded. Patients were followed in the pancreatitis clinic at 6-month intervals or as the clinical situation warranted. Desirability function methodology was used to develop the CP severity score which ranges between 0 (most severe) and 1 (not severe). Of the 14 recorded variables, on the a stepwise ordinal logistic regression analysis, 8 variables were selected based on a stepwise ordinal logistic regression and combined into a 'pancreatitis severity score' alcohol use, side branch size, side branch ectasia (SBE >3),main PD (MPD) irregularity, MPD stricture, MPD leak, MPD calculi, and contour abnormality of the bile duct. The key outcomes assessed included: exocrine failure, endocrine insufficiency (diabetes), presence or development of a pseudocyst and bile duct stricture. An ordinal 'response' score was created at baseline and at one-year followup, which counted the number of the above outcomes in each patient. Results: Eighty nine subjects with CP (mean age 48 yrs, 54% males) were evaluated, of whom 48 (54%) were African American and 41 (46%) were Caucasian. On independent ordinal regression analysis, only the side branch size correlated with the severity of CP (p= 0.03). The 'CP severity score' significantly correlated with the number of adverse outcomes in CP (p=0.038) and was negatively associated with the number of outcomes. The average CP severity score in subjects with none, one, two, three and four adverse outcomes was 0.74, 0.70, 0.63, 0.60 and 0.43, respectively. For each 0.1 unit increase in the CP severity score the odds of moving to more adverse outcomes decreased by 0.85 times. Conclusions: The 'CP severity score' significantly correlates with the severity of CP. The 'CP severity index' reliably predicts the progression of CP by taking into consideration both imaging changes as well as behavioral risk factors as ongoing alcohol use.

Optimization of osmotic dehydration of cantaloupe using desired function methodology

Our objective was to optimize the osmotic dehydration of the cantaloupe using the desired function methodology. Cantaloupe cylinders were cut and weighted, initial humidity and °Brix were measured, then four cylinders were osmo-dehydrated in solutions of sucrose of give concentration and temperature by a stipulated time. The conditions of dehydration were established by means of a central rotable composite design for temperatures, concentrations and times between 40–50 °C, 45–55 °Brix and 60–120 min, respectively. Weight, humidity and °Brix were determined in each cylinder after each dehydration in order to calculate the mass loss, water loss and °Brix increase. These response variables were fitted to predictive models applying multiple linear regressions. Applying the method of the desired function, the dehydration was optimized in 37.95 °C, 41.6 °Brix and 132.30 min in order to obtain weight loss equal to 0.11 g/g, water loss equal to 0.33 g/g and °Brix increase equal to 12.3 °Brix/g.