2015
DOI: 10.1016/j.indcrop.2015.08.005
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Sage oil extraction and optimization by response surface methodology

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Cited by 29 publications
(18 citation statements)
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“…Then, response surface methodology (RSM) should be conducted to maximize the extraction yield as a statistical multi-response optimization method. RSM is an effective statistic tool with minimized experimental trials and a 3D description of the interactions of parameters [18,26]. …”
Section: Introductionmentioning
confidence: 99%
“…Then, response surface methodology (RSM) should be conducted to maximize the extraction yield as a statistical multi-response optimization method. RSM is an effective statistic tool with minimized experimental trials and a 3D description of the interactions of parameters [18,26]. …”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the RSM analysis of CUPRAC values showed that the model was significant with p-value < 0.0001, did not present lack of fit (p = 0.2818) and could explain 92.73 % of calculated model (adjusted R² = 0.9074). In addition to that, the coefficient of variation (CV) equal to 1.84 %, demonstrates the high degree of precision between the calculated and experimental results [26], and the adequate precision is 16.06 as well.…”
Section: Tfc Yx =-mentioning
confidence: 81%
“…They indicate that the model is more accurate and fits the data [25]. The coefficient of variation (CV) is equal to 4.91 %, indicating the high degree of precision between the calculated and experimental result [26]. Withal, the adequate precision measures the signal to noise ratio and this ratio was 9.29.…”
Section: Optimization Of Extractionmentioning
confidence: 92%
“…the model, For a good adjustment of a model, the R 2 value should be a minimum of 0.80 [39]. Alternatively, a coefficient of variation (CV) of 5.9% indicates a very high degree of precision between the experimental and predicted values [12].…”
Section: Statistical Validation Of the Modelmentioning
confidence: 99%
“…In the framework of improving essential oil yield, studies have been conducted on the optimization of extraction operating parameters through the use of the response surface methodology (RSM) [7][8][9][10][11][12]. The objective of the study of the response surfaces is to model the studied phenomenon.…”
Section: Introductionmentioning
confidence: 99%