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Integrating uniform design and response surface methodology to optimize thiacloprid suspension

View Article: PubMed Central - PubMed

ABSTRACT

A model 25% suspension concentrate (SC) of thiacloprid was adopted to evaluate an integrative approach of uniform design and response surface methodology. Tersperse2700, PE1601, xanthan gum and veegum were the four experimental factors, and the aqueous separation ratio and viscosity were the two dependent variables. Linear and quadratic polynomial models of stepwise regression and partial least squares were adopted to test the fit of the experimental data. Verification tests revealed satisfactory agreement between the experimental and predicted data. The measured values for the aqueous separation ratio and viscosity were 3.45% and 278.8 mPa·s, respectively, and the relative errors of the predicted values were 9.57% and 2.65%, respectively (prepared under the proposed conditions). Comprehensive benefits could also be obtained by appropriately adjusting the amount of certain adjuvants based on practical requirements. Integrating uniform design and response surface methodology is an effective strategy for optimizing SC formulas.

No MeSH data available.


Response surface plots for viscosity.
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f4: Response surface plots for viscosity.

Mentions: To visualize these relationships further, response surfaces were also plotted to reveal the influence of the tested factors on viscosity. As stated above, three variables were maintained at median levels while the other variable ranged from the lowest level to the highest level to investigate the respective influence of the four factors. As illustrated in Fig. 4a, the viscosity decreased dramatically with increasing amounts of X1. However, significant increases in viscosity were observed with an increase in X2, X3 or X4 (Fig. 4b,c and d). The interactions between X2 and X3, X2 and X4, and X3 and X4 were significant and are displayed in Fig. 4. The viscosity increased significantly with the amount of X2 regardless of the amount of X3 added, as shown in Fig. 4e. When X2 was maintained at the lowest level, the viscosity varied little with variations in the amount of X3. However, when X2 was added at the highest level, an increase of approximately 30 mPa s in viscosity was observed with increasing amounts of X3 (Fig. 4e). As depicted in Fig. 4f, viscosity increased significantly with the levels of X2 and X4 when X1 and X3 were maintained at median levels. In terms of the interaction between X3 and X4, viscosity varied slightly with the amount of X3 but increased dramatically with X4 regardless of the X3 level (Fig. 4g).


Integrating uniform design and response surface methodology to optimize thiacloprid suspension
Response surface plots for viscosity.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5382544&req=5

f4: Response surface plots for viscosity.
Mentions: To visualize these relationships further, response surfaces were also plotted to reveal the influence of the tested factors on viscosity. As stated above, three variables were maintained at median levels while the other variable ranged from the lowest level to the highest level to investigate the respective influence of the four factors. As illustrated in Fig. 4a, the viscosity decreased dramatically with increasing amounts of X1. However, significant increases in viscosity were observed with an increase in X2, X3 or X4 (Fig. 4b,c and d). The interactions between X2 and X3, X2 and X4, and X3 and X4 were significant and are displayed in Fig. 4. The viscosity increased significantly with the amount of X2 regardless of the amount of X3 added, as shown in Fig. 4e. When X2 was maintained at the lowest level, the viscosity varied little with variations in the amount of X3. However, when X2 was added at the highest level, an increase of approximately 30 mPa s in viscosity was observed with increasing amounts of X3 (Fig. 4e). As depicted in Fig. 4f, viscosity increased significantly with the levels of X2 and X4 when X1 and X3 were maintained at median levels. In terms of the interaction between X3 and X4, viscosity varied slightly with the amount of X3 but increased dramatically with X4 regardless of the X3 level (Fig. 4g).

View Article: PubMed Central - PubMed

ABSTRACT

A model 25% suspension concentrate (SC) of thiacloprid was adopted to evaluate an integrative approach of uniform design and response surface methodology. Tersperse2700, PE1601, xanthan gum and veegum were the four experimental factors, and the aqueous separation ratio and viscosity were the two dependent variables. Linear and quadratic polynomial models of stepwise regression and partial least squares were adopted to test the fit of the experimental data. Verification tests revealed satisfactory agreement between the experimental and predicted data. The measured values for the aqueous separation ratio and viscosity were 3.45% and 278.8 mPa·s, respectively, and the relative errors of the predicted values were 9.57% and 2.65%, respectively (prepared under the proposed conditions). Comprehensive benefits could also be obtained by appropriately adjusting the amount of certain adjuvants based on practical requirements. Integrating uniform design and response surface methodology is an effective strategy for optimizing SC formulas.

No MeSH data available.