scholarly journals Process optimization of supercritical CO2 extraction of Roselle using response surface methodology

2020 ◽  
Vol 16 (1) ◽  
pp. 30-33
Author(s):  
Wong Lee Peng ◽  
Siti Hamidah Mohd Setapar ◽  
Hasmida Mohd Nasir
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Supercritical Co2 ◽  
Extraction Yield ◽  
Hibiscus Sabdariffa ◽  
Native Plant ◽  
Optimum Conditions ◽  
Supercritical Co2 Extraction ◽  
Predicted Values

Hibiscus sabdariffa, commonly known as Roselle, is a native plant in Malaysia that is rich with bioactive compounds. In the present study, supercritical carbon dioxide (SC-CO2) extraction of Roselle was investigated. The optimum particle size (212µm, 300µm, 425µm, 600µm, and 710µm) to obtain highest yield was pre-determined. The effects of two operating parameters, pressure (20MPa, 25MPa, and 30MPa) and temperature (40 ºC, 60 ºC, and 80 ºC) on extraction yield were studied using response surface methodology (RSM). From the experimental data, the optimum conditions were achieved using particle size 300µm, pressure 27.5MPa, and temperature 50.8 ºC. Using the optimized parameters, the highest extraction yield was predicted to be 163.26 mg-extract/g-dried sample. The validation experimental results were consistent with the predicted values. 

Optimization of Supercritical Co2 Extraction of Swietenia Mahagoni Seed by Response Surface Methodology

2014 ◽  
Vol 67 (1) ◽  
Author(s):  
Liza Md Salleh ◽  
Hartati Hartati ◽  
Mohd. Azizi Che Yunus ◽  
Azila Abd. Aziz
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Oil Yield ◽  
High Yield ◽  
Optimum Conditions ◽  
Supercritical Co2 Extraction ◽  
Carbon Dioxide Extraction ◽  
Order Polynomial ◽  
Swietenia Mahagoni

Three operating parameters were pressure, temperature and particle size of supercritical carbon dioxide extraction of oil from Swietenia mahagoni have been optimized by response surface methodology to obtain high yield of oil. Results showed that data were adequately fitted into the second-order polynomial model. The linear and quadratic terms of independent variables of temperature, pressure and particle size have significant effects on the oil yield. Optimum conditions for oil yield within the experimental range of the studied variables were 29.99 MPa, 55.29oC and 0.75 mm, and the oil yield was predicted to be 20.76%.

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.

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.

OPTIMISATION OF MICROENCAPSULATION OF CITRUS HYSTRIX L. OIL SUB AND SUPERCRITICAL CO2 USING RESPONSE SURFACE METHODOLOGY

2017 ◽  
Vol 79 (5-3) ◽  
Author(s):  
Noorrasyidah Mohd Sarmin ◽  
Shazana Azfar Razali ◽  
Masturah Markom
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Volatile Compounds ◽  
Response Surface ◽  
Supercritical Co2 ◽  
Key Factors ◽  
Organic Solution ◽  
Optimum Pressure ◽  
Optimum Result ◽  
Resident Time

Response surface methodology (RSM) was used to optimise the microencapsulation process of Citrus Hystrix L. Oil (CHO) by depressurization of an expanded liquid organic solution (DELOS) sub and supercritical CO2. The particle size and yield (%) was studied with considered to three key factors variables including pressure (30-80 bar), temperature (40-60˚C) and resident time (10-60 minutes) on the microencapsulation process. The optimum result from RSM is 549.4 nanometer for the particle size and 38.193% yield at optimum pressure 54.14bar, temperature 59.65˚C and resident time 58 minutes. The results clearly show that the interactions between pressure, temperature and time have a significant effect on the microencapsulation process. Thus, the microencapsulated formulation has potential to be applied to other volatile compounds.

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