Application of response surface methodology and central composite design for the optimisation of supercritical fluid extraction of essential oils from Myrtus communis L. leaves

Estimation of mass transfer coefficients of the extraction process of essential oil from orange peel using microwave assisted extraction

“…Different mathematical approaches have been reported that explain the process involved during traditional methods of extraction. Some authors have described the extraction variables effects on essential oil yield through statistical analysis of experimental data (Ghasemi et al, 2011;Parikh and Desai, 2011;Zhang et al, 2012), being response surface methodology (RSM) successfully applied for optimizing extraction conditions. However, this type of analysis represents parameter values for the optimization process within the experimental values, thereby; it just can be used in the experimental range tested and just represents the evaluated variables effect on analyzed response (Almeida et al, 2008).…”

Chemical composition and antioxidant activity of Lippia alba essential oil obtained by supercritical CO2 and hydrodistillation

“…In other work, Duran et al (2007) found that extraction time directly impacted the composition of L. alba essential oil extracts prepared by microwave radiation-assisted hydrodistillation. The influence of extraction method on the resulting essential oil composition has also been reported for clove buds, patchouli, and Mirtus communis L. (Wenqiang et al, 2007;Donelian et al, 2009;Ghasem et al, 2011). Thus, it appears essential to use more than a single extraction technique when characterizing a plant's volatile secondary metabolite composition (Stashenko et al, 2004).…”

Experimental Design Optimization of the Determination of Total Halogens in Coal by Combustion–Ion Chromatography

“…The difference between a response surface equation and the equation for a factorial design is the addition of quadratic terms that allow model curvature in the response, making them useful for understanding how changes of input factors influence the response of interest, finding the levels of input factors that optimize the response, and selecting the operating conditions to meet the specifications (Hanrahan et al 2005). Central composite design is a response surface methodology that is often used when the design calls for sequential experimentation because this approach may incorporate information from a properly planned factorial experiment (Sahu, Acharya, and Meikap 2009;Ghasemi, Raofie, and Najati 2011). In order to optimize the total halogens extracted from coal, the experiment was conducted with total halogen recovery as the response variable in the central composite design.…”