Issue 34, 2015

Thiacloprid suspension formula optimization by a response surface methodology

Abstract

A model thiacloprid 25% suspension concentrate was prepared using Tersperse2700 (X1), AE1601 (X2), xanthan gum (X3) and Veegum (X4). A response surface methodology (RSM) was used to evaluate the influences of four experimental factors on the aqueous separation ratio (R1), centrifugal sedimentation ratio (R2) and viscosity (R3). The results show that the main factors influencing the three responses were X3, X4 and X2 followed by X1; moreover, several interactions were also significant. Multiple-response optimization was performed based on a desirability function, considering the minimum R1, R2, and R3 as well as the financial cost. The integrated optimum conditions were X3 = 0.24%, X4 = 1.33%, X2 = 0.50%, and X1 = 2.90% (mass fraction). A verification experiment demonstrated that the optimized formula R1, R2, and R3 were 1.69%, 2.63% and 257.74 mPa s with the average relative predicted value errors 7.69%, 4.18% and −1.41%, respectively. The response surface methodology is an effective approach for optimizing the suspension concentrate formula with comprehensive advantages.

Graphical abstract: Thiacloprid suspension formula optimization by a response surface methodology

Supplementary files

Article information

Article type
Paper
Submitted
07 Jan 2015
Accepted
26 Feb 2015
First published
26 Feb 2015

RSC Adv., 2015,5, 26654-26661

Author version available

Thiacloprid suspension formula optimization by a response surface methodology

B. Li, W. Wang, K. Wang, D. Zhang, L. Guan and F. Liu, RSC Adv., 2015, 5, 26654 DOI: 10.1039/C5RA00292C

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