2012
DOI: 10.1111/j.1365-2621.2012.02948.x
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Application of response surface methodology to optimise supercritical carbon dioxide extraction of oil from rapeseed (Brassica napusL.)

Abstract: Summary Supercritical CO2 fluid extraction technology was used to extract oil from rapeseed. Extraction temperature, pressure, time and the sample particle size were selected and optimised by response surface methodology. Conventional solvent extraction was applied as a comparative method. The maximum extraction yield of 32.65 ± 1.01% was achieved at a temperature of 40 °C and a pressure of 345 bar, using an extraction time of 3 h and a 60‐mesh particle size. The chemical compositions of rapeseed oil using est… Show more

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Cited by 26 publications
(9 citation statements)
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“…Three independent variables, X 1 -solvent concentration, X 2 -extraction temperature, and X 3 -extraction time, were studied, as shown in Table S10. For the three factors, a three-level face-centered cube design was applied, consisting of 15 experimental runs with three replicates at the central point [41,42]. All experiments were conducted in random order to eliminate error due to the extraneous factors.…”
Section: Experimental Designmentioning
confidence: 99%
“…Three independent variables, X 1 -solvent concentration, X 2 -extraction temperature, and X 3 -extraction time, were studied, as shown in Table S10. For the three factors, a three-level face-centered cube design was applied, consisting of 15 experimental runs with three replicates at the central point [41,42]. All experiments were conducted in random order to eliminate error due to the extraneous factors.…”
Section: Experimental Designmentioning
confidence: 99%
“…Optimization of extraction conditions of phenolic compound, flavonoids and crude fiber from date seeds powder were carried out using a central composite design (CCD) and response surface methodology (RSM), according to Montgomery (2001, 2002). A four factors and a three level face centered cube design consisting of twentynine experimental runs were conducted with five replicates at the central point (Jing et al 2012). The orders of all experiments were performed randomly to minimize error, due to extraneous factors.…”
Section: Experimental Designmentioning
confidence: 99%
“…The quality of the model's fit can be defined by the coefficient of determination (R 2 ), adjusted R 2 , predicted R 2 , coefficient of variation (CV), adequate precision (AP) and prediction error sum of squares (PRESS) (Bezerra et al, 2008;Golalikhani et al, 2014;Rouhi et al, 2017). The high value of R 2 (0.9730) indicated a good relationship between the observed and predicted data and implied that 97.30% of the variations could be predicted by the fitted model (Yu et al, 2012). The nearer the value of R 2 is to 1, the better the proposed model fits the actual data (Suhag & Nanda, 2015).…”
Section: Response Surface Methodologymentioning
confidence: 99%