Optimization of the Griddling Process of Kpejigaou (a Traditional Low Fat Nutritious Cowpea Food) Using Response Surface Methodology

2010 ◽  
Vol 16 (4) ◽  
pp. 351-356
Author(s):  
E. Amonsou ◽  
E. Sakyi-Dawson ◽  
F. Saalia ◽  
S. Sefa-Dedeh ◽  
L.D. Abbey
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Regression Models ◽  
Profile Analysis ◽  
Textural Properties ◽  
Optimum Conditions ◽  
Low Fat ◽  
Texture Profile ◽  
Multiple Regression Models ◽  
Important Quality

Kpejigaou is a griddled cowpea paste product eaten mainly in West Africa. As its processing does not involve the use of fat, it has the potential of meeting consumers’ demand for healthy, low fat nutritious foods. Product texture is considered an important quality index by kpejigaou consumers. The objective of this study was to determine the optimum processing conditions of kpejigaou with respect to its textural properties. The study followed a 2 × 3 design with two processing variables each at three levels as follows: griddling temperature (130, 200, 270 °C) and time (5, 7.5 and 10 min). Texture Profile Analysis (TPA) was done on freshly processed samples. The data were fitted into multiple regression models from which the optimum griddling conditions for kpejigaou were determined. Kpejigaou processed at the optimum conditions was evaluated by untrained consumers for acceptability. Traditionally processed kpejigaou served as the control. The TPA results showed that hardness, chewiness and modulus of deformability were significantly affected by griddling conditions. Adjusted R2 for the models for hardness, chewiness and modulus of deformability were 96%, 97% and 78%, respectively. Using response surface methodology, the optimum griddling conditions for kpejigaou (for acceptable textural properties) were determined to be 170 °C for 5-6 min. The texture of optimized kpejigaou was very much liked for its higher degree of sponginess as compared to the control. It also had acceptable sensory attributes of color, taste and flavor. These findings provide the basis for the development of a process for mass production and quality assurance of kpejigaou.

scholarly journals Enzyme optimization to reduce the viscosity of pitanga (Eugenia uniflora L.) juice

2016 ◽  
Vol 19 (0) ◽  
Author(s):  
Ricardo Schmitz Ongaratto ◽  
Luiz Antonio Viotto
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Incubation Time ◽  
Regression Models ◽  
Incubation Temperature ◽  
Correlation Coefficients ◽  
Enzyme Concentration ◽  
Optimum Conditions ◽  
Activity Time ◽  
Independent Variables

Summary The aim of this work was to separately evaluate the effects of pectinase and cellulase on the viscosity of pitanga juice, and determine the optimum conditions for their use employing response surface methodology. The independent variables were pectinase concentration (0-2.0 mg.g–1) and cellulase concentration (0-1.0 mg.g–1), activity time (10-110 min) and incubation temperature (23.2-56.8 °C). The use of pectinase and cellulase reduced the viscosity by about 15% and 25%, respectively. The results showed that enzyme concentration was the most important factor followed by activity time, and for the application of cellulase the incubation temperature had a significant effect too. The regression models showed correlation coefficients (R2) near to 0.90. The pectinase application conditions that led to the lowest viscosity were: concentration of 1.7 mg.g–1, incubation temperature of 37.6 °C and incubation time of 80 minutes, while for cellulase the values were: concentration of 1.0 mg.g-1, temperature range of 25 °C to 35 °C and incubation time of 110 minutes.

Instrumental Texture Profile Analysis (TPA) of Shelled Sunflower Seed Caramel Snack Using Response Surface Methodology

2007 ◽  
Vol 13 (6) ◽  
pp. 455-460 ◽  
Author(s):  
R.K. Gupta ◽  
Alka Sharma ◽  
R. Sharma
Keyword(s):  
Response Surface Methodology ◽  
Product Quality ◽  
Response Surface ◽  
Sunflower Seed ◽  
Profile Analysis ◽  
Texture Profile Analysis ◽  
Texture Profile ◽  
Texture Analyzer ◽  
Instrumental Texture

Models capable of predicting product quality of shelled sunflower seed caramel snack have been developed using response surface methodology. The textural profile analysis was conducted on the snacks using a texture analyzer. The quality attributes measured were hardness, cohesiveness, springiness, chewiness, and resilience as a function of sugar and sunflower kernels content. The sugar and shelled seed proportions affect the textural characteristics of the product significantly (p<0.05). The values of hardness, cohesiveness, springiness, chewiness, and resilience varied from 2.048 to 42.030 N, 1.002 to 5.003, 1.138 to 1.69, 2.773 to 228.146N, and 0.301 to 0.779, respectively. The highest values of hardness and chewiness were attained for the product with 70:30 sugar and shelled sunflower seed proportion respectively. Similarly the highest values of cohesiveness, springiness and resilience were observed in 50 : 30, 50 : 40, and 50 : 50 proportions respectively. The lowest values of hardness and chewiness were observed in 50 : 50 (sugar: shelled sunflower seed) proportion respectively. Similarly the lowest values of cohesiveness were observed in 70: 50 whereas the lowest values of springiness and resilience were observed in 70 : 30 proportions respectively. Hardness, cohesiveness, and chewiness trended to increase whereas springiness and resilience decreased with increase in sugar proportion.

scholarly journals The effect of oat bran and psyllium husk fibre on oil reduction and some physicochemical properties of magwinya – a deep-fried dough

2018 ◽  
Vol 16 (1) ◽  
pp. 247-254 ◽  
Author(s):  
Kwinda ◽  
Onipe ◽  
Jideani
Keyword(s):  
Response Surface Methodology ◽  
Physicochemical Properties ◽  
Response Surface ◽  
Oil Content ◽  
Textural Properties ◽  
Oil Absorption ◽  
Optimum Conditions ◽  
Psyllium Husk ◽  
Oat Bran ◽  
Method Of Production

Oat bran (OB) and psyllium husk fibre (PF) were incorporated into magwinya (fat cake) – a cereal fried dough with the aim of reducing oil content and evaluating some of its physicochemical properties using one-factor of the response surface methodology. Two methods of magwinya processing were employed: traditional (TM) and modified (MM) methods. Addition of PF and OB significantly (p < 0.05) reduced oil in MM compared to TM. Lowest oil content for PF and OB magwinya were 3.10 and 4.35% using MM and 6.00 and 6.25% for TM. Addition of PF up to 3% and OB up to 2% significantly improved textural properties. Comparing the additives and the method of production, optimum conditions with highest desirability of 0.83 was obtained for OB modified magwinya with 35.08% moisture, 2.31% ash and 4.74% oil. Hence, the use of MM and OB reduced oil absorption.

scholarly journals OPTIMIZATION OF REFLUX EXTRACTION FOR CAESALPINIA SAPPAN LINN. WOOD BY USING RESPONSE SURFACE METHODOLOGY

2020 ◽  
Vol 83 (1) ◽  
pp. 85-92
Author(s):  
Mohd Azahar Mohd Ariff ◽  
Muhammad Syafiq Abd Jalil ◽  
Noor ‘Aina Abdul Razak ◽  
Jefri Jaapar
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Drinking Water ◽  
Response Surface ◽  
Extraction Time ◽  
Percentage Error ◽  
Optimum Conditions ◽  
Caesalpinia Sappan ◽  
The Mean ◽  
Repeated Runs

Caesalpinia sappan linn. (CSL) is a plant which is also known as Sepang tree contains various medicinal values such as to treat diarrhea, skin rashes, syphilis, jaundice, drinking water for blood purifying, diabetes, and to improve skin complexion. The aim of this study is to obtain the most optimum condition in terms of the ratio of sample to solvent, particle size, and extraction time to get the highest amount of concentration of the CSL extract. In this study, the ranges of each parameters used were: ratio sample to solvent: 1.0:20, 1.5:20, 2.0:20, 2.5:20, 3.0:20, particle size: 1 mm, 500 um, 250 um, 125 um, 63 um, and extraction time: 1 hr, 2 hr, 3 hr, 4 hr, 5 hr. The concentration was analyzed using a UV-vis spectrophotometer. The optimum conditions were obtained by response surface methodology. From the design, 20 samples were run throughout this experiment. The optimized value from the RSM were 2.0:20 for ratio sample to solvent, 125 µm of particle size and 2.48 hours with the concentration of 37.1184 ppm. The accuracy of the predictive model was validated with 2 repeated runs and the mean percentage error was less than 3%. This confirmed the model’s capability for optimizing the conditions for the reflux extraction of CSL’s wood.

scholarly journals Optimising Brewery-Wastewater-Supported Acid Mine Drainage Treatment vis-à-vis Response Surface Methodology and Artificial Neural Network

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1485
Author(s):  
Enoch A. Akinpelu ◽  
Seteno K. O. Ntwampe ◽  
Abiola E. Taiwo ◽  
Felix Nchu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Acid Mine Drainage ◽  
Response Surface ◽  
Mine Drainage ◽  
Sulphate Reduction ◽  
Optimum Conditions ◽  
Acid Mine ◽  
Artificial Neural

This study investigated the use of brewing wastewater (BW) as the primary carbon source in the Postgate medium for the optimisation of sulphate reduction in acid mine drainage (AMD). The results showed that the sulphate-reducing bacteria (SRB) consortium was able to utilise BW for sulphate reduction. The response surface methodology (RSM)/Box–Behnken design optimum conditions found for sulphate reduction were a pH of 6.99, COD/SO42− of 2.87, and BW concentration of 200.24 mg/L with predicted sulphate reduction of 91.58%. Furthermore, by using an artificial neural network (ANN), a multilayer full feedforward (MFFF) connection with an incremental backpropagation network and hyperbolic tangent as the transfer function gave the best predictive model for sulphate reduction. The ANN optimum conditions were a pH of 6.99, COD/SO42− of 0.50, and BW concentration of 200.31 mg/L with predicted sulphate reduction of 89.56%. The coefficient of determination (R2) and absolute average deviation (AAD) were estimated as 0.97 and 0.046, respectively, for RSM and 0.99 and 0.011, respectively, for ANN. Consequently, ANN was a better predictor than RSM. This study revealed that the exclusive use of BW without supplementation with refined carbon sources in the Postgate medium is feasible and could ensure the economic sustainability of biological sulphate reduction in the South African environment, or in any semi-arid country with significant brewing activity and AMD challenges.

Optimization of photocatalytic degradation of real textile dye house wastewater by response surface methodology

2016 ◽  
Vol 74 (9) ◽  
pp. 1999-2009 ◽  
Author(s):  
Sayed Mohammad Bagher Hosseini ◽  
Narges Fallah ◽  
Sayed Javid Royaee
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Advanced Oxidation Process ◽  
Influential Factor ◽  
P Value ◽  
Textile Dye ◽  
Optimum Conditions ◽  
Effective Parameters ◽  
Initial Ph

This study evaluates the advanced oxidation process for decolorization of real textile dyeing wastewater containing azo and disperse dye by TiO2 and UV radiation. Among effective parameters on the photocatalytic process, effects of three operational parameters (TiO2 concentration, initial pH and aeration flow rate) were examined with response surface methodology. The F-value (136.75) and p-value &lt;0.0001 imply that the model is significant. The ‘Pred R-Squared’ of 0.95 is in reasonable agreement with the ‘Adj R-Squared’ of 0.98, which confirms the adaptability of this model. From the quadratic models developed for degradation and subsequent analysis of variance (ANOVA) test using Design Expert software, the concentration of catalyst was found to be the most influential factor, while all the other factors were also significant. To achieve maximum dye removal, optimum conditions were found at TiO2 concentration of 3 g L−1, initial pH of 7 and aeration flow rate of 1.50 L min−1. Under the conditions stated, the percentages of dye and chemical oxygen demand removal were 98.50% and 91.50%, respectively. Furthermore, the mineralization test showed that total organic compounds removal was 91.50% during optimum conditions.

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