Application of response surface methodology to optimise supercritical carbon dioxide extraction of essential oil from Cyperus rotundus Linn.

Wang, Hongwu; Liu, Yanqing; Wei, Shoulian; Zhou, Yan

doi:10.1016/j.foodchem.2011.10.075

Cited by 83 publications

(35 citation statements)

References 36 publications

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“…RSM can be effectively used to evaluate the effects of multiple factors and their interactions on one or more response variables (Xu et al, 2013;Azmir et al, 2014). One of the advantages of RSM is that it reduces the number of experiments and provides a mathematical model (Karacabey and Mazza, 2010;Nagendra et al, 2011;Wang et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Zhang

Hou

et al. 2015

Industrial Crops and Products

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Section: Introductionmentioning

confidence: 99%

Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Zhang

Hou

et al. 2015

Industrial Crops and Products

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“…The predicted values can be calculated using the derived model while the experimental values are obtained as average values from an experiment performed in at least triplicates with assigned values of independent variables. Aybastier et al (2013), compared the values predicted using equations (11) to (13) with the experimental values as shown in Table 3 and found that the deviation was only in the range of 0.2 -3 %. Similarly, Tian et al (2013) investigated the interaction between four variables in producing the highest fatty acids methyl ester.…”

Section: Current Optimization Research Using Bbmentioning

confidence: 99%

“…By establishing a model equation, RSM can evaluate the relationship as well as interactions among the multiple parameters using quantitative data. There are three steps in RSM implementation; (1) design of experiment i.e Box Behnken and Central Composite Design (CCD); (2) statistical and regression analysis to develop model equations that represent the response surface modeling; and (3) parameters/variables optimization carried out through model equation [11].…”

Section: Introductionmentioning

confidence: 99%

Overview on the Response Surface Methodology (RSM) in Extraction Processes

Said

Amin

2016

JASPE

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Response Surface Methodology (RSM) is an optimization tool that can identify interrelationship between variables as being adopted by experiment/ research studies in food and herbal plants extraction niche area. This review discusses the optimization approach through utilization of research surface methodology either using central composite design or Box-Behnken method specifically in extraction processes. The use of analysis of variance (ANOVA) to evaluate the degree of accuracy held by the derived model is based on several responses. RSM helps to determine the best experimental design in order to identify the relationship between variables. This paper also discusses on the utilization of RSM to derive a model equation that later can be applied for response prediction and the determination of optimal conditions. The discussion presented here has clearly established the importance of choosing the right optimization tools such as response surface methodology (RSM). Major achievement of response surface methodology compared to conventional methods is the reduction of experimental runs for the same objective which is to obtain optimal variables condition/value for the highest output/response. Besides, the model derived can be used to predict the response prior to experimentation phase. Moreover, this step can help researcher or industries to focus on certain variables/aspect that contribute to the highest effect on process output. The use of either central composite design or Box-Behnken for extraction purposes especially with high-cost raw material is an economical alternative to traditional optimization approach through one-factor method. Combining extraction process with RSM can cause significant degree of accuracy in model prediction.

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“…By statistical optimization techniques, the influence of the extraction process variables on the yield of desired extractive substance(s) is analyzed through a smaller number of experiments, which reduces greatly laboratory work and reagent consumption. For the optimization of liquid-solid extraction processes, the response surface methodology (RSM) is usually applied in combination with the full factorial design (FFD) [1][2][3], central composite design (CCD) [4][5][6][7][8][9][10][11] or Box-Behnken design (BBD) [12][13][14] serving for the data collection. The Plackett-Burman design followed by either CCD [15] or BoxBehnken design [16][17][18] has also been applied in optimizing liquid-solid extraction processes.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Box-Behnken, Face Central Composite and Full Factorial Designs in Optimization of Hempseed Oil Extraction by n-Hexane: a Case Study

Stamenković¹,

Kostić²,

Radosavljević³

et al. 2018

Period. Polytech. Chem. Eng.

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show abstract

Application of response surface methodology to optimise supercritical carbon dioxide extraction of essential oil from Cyperus rotundus Linn.

Cited by 83 publications

References 36 publications

Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Optimization of ultrasound-assisted hexane extraction of perilla oil using response surface methodology

Overview on the Response Surface Methodology (RSM) in Extraction Processes

Comparison of Box-Behnken, Face Central Composite and Full Factorial Designs in Optimization of Hempseed Oil Extraction by n-Hexane: a Case Study

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