Optimization of the Culture Medium Composition to Improve the Production of Hyoscyamine in Elicited Datura stramonium L. Hairy Roots Using the Response Surface Methodology (RSM)
Abstract
:1. Introduction
- - First, to use the RSM method for the optimization of nutrients (nitrate, calcium and sucrose) in the culture medium B5 [Gamborg, 1968] to improve hyoscyamine production in elicited HRs;
- - Second, to show the value of the RSM method in the optimization of several responses in plant material cultures.
2. Materials and Methods
2.1. Plant Materials
2.2. Elicitation
2.3. Extraction and Hyoscyamine Analysis
2.4. Theory of RSM
2.5. Global Predicted Capacity, Analysis and Diagnostic of the Model
2.6. Determination of the Optimum
2.7. Application of the RSM for Optimization of the Culture Medium B5
- A factorial design with at least one experimental point located in the center of the experimental area;
- A star design whose axial points −α and +α are located on the axis of each factor. This design is particularly adapted to the progressive acquisition of results with a factorial design 2k.
3. Results and Discussion
3.1. Global Predictivity of the Model
3.2. Analysis of the Quadratic Model
3.3. Diagnostic of the Model
3.3.1. Diagnostic Plot
3.3.2. Influential Observations and Accommodation
3.5. Response Surface (RS) Analysis and Determination of Optimal Concentrations
3.6. Optimization Level
4. Conclusion
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Source | Sum of Squares | df | Mean Square | F-value | p-value |
---|---|---|---|---|---|
Model | 9537.1 | 10 | 953.7 | 414.1 | 0.0 |
Residual | 20.7 | 9 | 2.3 | ||
Lack of fit | 16.1 | 4 | 4.0 | 4.3 | 0.1 |
Pure Error | 4.7 | 5 | 0.9 | ||
Total | 9557.8 | 19 |
Model Terms | Coefficient Estimate | t-statistic | p-value |
---|---|---|---|
Intercept | 104.8 | 172.2 | - |
x1: nitrate | 10.5 | 24.6 | 0.0 |
x2: calcium | 5.5 | 12.9 | 0.0 |
x3: sucrose | 4.2 | 9.8 | 0.0 |
x1x2 | 3.5 | 6.5 | 0.0 |
x1x3 | 1.0 | 1.9 | 0.1 |
x2x3 | 1.0 | 1.9 | 0.1 |
x12 | −16.4 | −35.4 | 0.0 |
x22 | −14.4 | −31.1 | 0.0 |
x32 | −14.5 | −31.3 | 0.0 |
x1x2x3 | 0.7 | 1.3 | 0.2 |
Model with Full Terms | |||||||||
---|---|---|---|---|---|---|---|---|---|
Run Order (n) | Variable Code Levels | Measured | Predicted | Residual | hi Leverage | Cook’s Distance | DFFITS | ||
x1 [NO3−] | x2 [Ca2+] | x3 [sucrose] | |||||||
R1 | −1 | −1 | −1 | 43.8 | 43.9 | −0.1 | 0.8 | 0.0 | −0.4 |
R2 | 1 | −1 | −1 | 56.8 | 57.5 | −0.7 | 0.8 | 0.5 | −2.5 |
R3 | −1 | 1 | −1 | 46.8 | 47.5 | −0.7 | 0.8 | 0.5 | −2.4 |
R4 | 1 | 1 | −1 | 70.8 | 72.0 | −1.3 | 0.8 | 1.7 | −5.6 |
R5 | −1 | −1 | 1 | 51.2 | 49.8 | 1.4 | 0.8 | 2.0 | 6.5 |
R6 | 1 | −1 | 1 | 65.2 | 64.4 | 0.8 | 0.8 | 0.7 | 2.8 |
R7 | −1 | 1 | 1 | 55.2 | 54.4 | 0.8 | 0.8 | 0.7 | 2.9 |
R8 | 1 | 1 | 1 | 86.2 | 86.0 | 0.2 | 0.8 | 0.1 | 0.7 |
R9 | −1.52 | 0 | 0 | 50.0 | 50.9 | −0.9 | 0.6 | 0.1 | −1.0 |
R10 | 1.52 | 0 | 0 | 83.6 | 83.0 | 0.7 | 0.6 | 0.1 | 0.8 |
R11 | 0 | −1.52 | 0 | 62.3 | 63.1 | −0.8 | 0.6 | 0.1 | −0.9 |
R12 | 0 | 1.52 | 0 | 80.6 | 79.9 | 0.7 | 0.6 | 0.1 | 0.7 |
R13 | 0 | 0 | −1.52 | 66.7 | 64.8 | 1.8 | 0.6 | 0.4 | 2.7 |
R14 | 0 | 0 | 1.52 | 75.5 | 77.5 | −2.0 | 0.6 | 0.5 | −3.1 |
R15 | 0 | 0 | 0 | 103.8 | 104. 8 | −1.0 | 0.2 | 0.0 | −0.3 |
R16 | 0 | 0 | 0 | 104.7 | 104.8 | −0.0 | 0.2 | 0.0 | 0.0 |
R17 | 0 | 0 | 0 | 105.1 | 104.8 | 0.3 | 0.2 | 0.0 | 0.1 |
R18 | 0 | 0 | 0 | 106.4 | 104.8 | 1.6 | 0.2 | 0.0 | 0.5 |
R19 | 0 | 0 | 0 | 103.8 | 104.8 | −1.0 | 0.2 | 0.0 | −0.3 |
R20 | 0 | 0 | 0 | 104.9 | 104.8 | 0.1 | 0.2 | 0.0 | 0.0 |
Model with Only Significant Terms (Equation 5) | |||||||||
R4 | 1 | 1 | −1 | 70.8 | 74.8 | −4.0 | 0.6 | 0.9 | −4.7 |
R8 | 1 | 1 | 1 | 86.2 | 83.2 | 2.3 | 0.5 | 0.5 | 2.4 |
R14 | 0 | 0 | 1.52 | 75.5 | 77.5 | −2.0 | 0.6 | 0.5 | −2.2 |
Biomass (g DW/L) | Production of HS | |||||
---|---|---|---|---|---|---|
(mg/g DW) | (mg/L) | |||||
Without Elicitation | With Elicitation | Without Elicitation | With Elicitation | |||
B5 * | 8.4 ± 0.6 | 2.1 ± 0.1 | 4.2 ± 0.6 | 17.6 ± 1.6 | 35.3 ± 2.0 | |
B5-OP ** | 12.7 ± 0.2 | 3.8 ± 0.1 | 8.5 ± 0.3 | 48.3 ± 2.3 | 110.3 ± 1.4 | |
Optimization | 51.2% | 81% | 101.2% | 173.6% | 212.7% | |
LSD test | differences | −4.3 | −1.7 | −4.3 | −30.6 | −75.0 |
±limits | 0.9 | 0.2 | 0.8 | 4.4 | 13.8 | |
significance | significant | significant | significant | significant | significant |
© 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
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Amdoun, R.; Khelifi, L.; Khelifi-Slaoui, M.; Amroune, S.; Asch, M.; Assaf-Ducrocq, C.; Gontier, E. Optimization of the Culture Medium Composition to Improve the Production of Hyoscyamine in Elicited Datura stramonium L. Hairy Roots Using the Response Surface Methodology (RSM). Int. J. Mol. Sci. 2010, 11, 4726-4740. https://doi.org/10.3390/ijms11114726
Amdoun R, Khelifi L, Khelifi-Slaoui M, Amroune S, Asch M, Assaf-Ducrocq C, Gontier E. Optimization of the Culture Medium Composition to Improve the Production of Hyoscyamine in Elicited Datura stramonium L. Hairy Roots Using the Response Surface Methodology (RSM). International Journal of Molecular Sciences. 2010; 11(11):4726-4740. https://doi.org/10.3390/ijms11114726
Chicago/Turabian StyleAmdoun, Ryad, Lakhdar Khelifi, Majda Khelifi-Slaoui, Samia Amroune, Mark Asch, Corinne Assaf-Ducrocq, and Eric Gontier. 2010. "Optimization of the Culture Medium Composition to Improve the Production of Hyoscyamine in Elicited Datura stramonium L. Hairy Roots Using the Response Surface Methodology (RSM)" International Journal of Molecular Sciences 11, no. 11: 4726-4740. https://doi.org/10.3390/ijms11114726