| 正交设计和均匀设计在优化噻虫胺悬浮剂物理稳定性上的应用 |
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| 引用本文： | 李北兴,王伟昌,张大侠,王凯,管磊,刘峰.正交设计和均匀设计在优化噻虫胺悬浮剂物理稳定性上的应用[J].中国农业科学,2015,48(2):280-292. |
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| 作者姓名： | 李北兴 王伟昌 张大侠 王凯 管磊 刘峰 |
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| 作者单位： | 山东农业大学植物保护学院/农药毒理与应用技术重点实验室,山东泰安,271018 |
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| 基金项目： | 国家公益性行业(农业)科研专项 |
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| 摘 要： | 【目的】比较正交和均匀设计两种多因素试验方法在水悬浮剂配方中应用的优缺点,为该方法在农药制剂学领域的应用提供参考。【方法】在采用流点法初筛得到润湿性能良好的润湿分散剂之后,分别采用正交设计和均匀设计制备30%噻虫胺悬浮剂。综合考察润湿分散剂和黏度调节剂对制剂热贮析水率、离心沉淀率、黏度、流动性、分散性、热贮前后样品的粒度分布(D10、D50和D90)和悬浮率的影响。通过主效应图分析正交试验结果,采用逐步回归和偏最小二乘法(PLS)分析均匀试验结果,最后检验优化配方的各项性能。【结果】正交试验和均匀试验的所有样品黏度均在144.50—317.84 m Pa·s,均具有良好(良级或优级)的流动性和分散性。由于奥氏熟化作用,样品经热贮后,粒子的粒径轻微增大,D10、D50和D90分别由0.56—1.00、0.88—1.53和1.77—2.68μm变为0.76—1.02、1.12—1.56和2.07—3.25μm。所有样品贮前悬浮率均在91.88%—96.39%,经热贮后样品的悬浮率变化不大,分别在91.91%—96.13%,符合悬浮剂质量控制的一般要求,故本研究主要优化了热贮析水率和离心沉淀率两个指标。正交试验分析结果表明,T2700、黄原胶和硅酸镁铝的用量对热贮析水率和离心沉淀率均有显著影响,且均随用量增加而降低,而NR1601的用量对两个因变量的影响不显著。采用正交设计优化的配方,样品黏度为229.6 m Pa·s,流动性和分散性良好,热贮前后悬浮率分别为(94.76±0.70)%和(93.50±0.20)%,热贮析水率为(4.23±0.19)%,离心沉淀率也低于10%。均匀设计中,PLS平方项模型对热贮析水率有良好的预测性,热贮析水率为(2.55±0.03)%,离心沉淀率也仅为(4.36±0.21)%,优化样品的黏度为324.16 m Pa·s,流动性和分散性良好,热贮前后悬浮率分别为(93.19±0.09)%和(92.77±0.22)%,粒子的粒径小且分布较窄。PLS线性模型对离心沉淀率表现出良好的预测性,优化配方的离心沉淀率为(7.75±0.14)%,热贮析水率为(5.24±0.19)%。逐步回归模型对因变量的预测性均较差,优化配方也并非最优配方,热贮析水率为(9.51±0.20)%,离心沉淀率也高达(16.63±0.19)%。采用双重筛选逐步回归和PLS可以同时优化热贮析水率和离心沉淀率两个因变量,其中前者优化的模型拟合性比后者好,但其优化配方也并非最优配方。【结论】正交设计试验次数较多,但数据分析方法简单易掌握,采用主效应图结合方差分析即可有效地优化30%噻虫胺悬浮剂配方。均匀设计的稳健性差于正交设计,但其试验次数少,可有效降低试验成本,若能掌握其复杂的统计及分析方法,也可以获得理想的优化配方。
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| 关 键 词： | 正交设计 均匀设计 偏最小二乘法 逐步回归 物理稳定性 |
| 收稿时间： | 2014-07-07 |
Application of Orthogonal Design and Uniform Design in Physical Stability Promotion of Clothianidin Suspension Concentrate |
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| LI Bei-xing,WANG Wei-chang,ZHANG Da-xia,WANG Kai,GUAN Lei,LIU Feng.Application of Orthogonal Design and Uniform Design in Physical Stability Promotion of Clothianidin Suspension Concentrate[J].Scientia Agricultura Sinica,2015,48(2):280-292. |
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| Authors: | LI Bei-xing WANG Wei-chang ZHANG Da-xia WANG Kai GUAN Lei LIU Feng |
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| Affiliation: | College of Plant Protection, Shandong Agricultural University/Key Laboratory of Pesticide Toxicology & Application Technique, Taian 271018, Shandong |
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| Abstract: | 【Objective】The objective of this study is to discuss the advantages and disadvantages in application of two multi-factor experimental designs in SC (suspension concentrate) formula. Effectively providing reference for the application of orthogonal design and uniform design in pesticide formulation was also expected. 【Method】 Clothianidin 30% SC was prepared based on orthogonal design and uniform design after the wetting-suspending agents with favorable wettability were selected by applying flow point method. The effect of wetting-suspending agent and viscosity modifier on the water separation rate after hot storage (WSRHS), precipitation rate after centrifugation (PRC), viscosity, fluidity, dispersibility, the size distribution (including D10, D50 and D90) and suspensibility of the samples before and after hot storage were investigated. The main effect plots were used to analyze the results of orthogonal design while stepwise regression and partial least squares (PLS) were used to analyze that of uniform design. Finally, validation tests were conducted to assess the properties of optimized formulas.【Result】The viscosity of all samples prepared based on orthogonal design and uniform design ranged from 144.50 to 317.84 mPa·s and all the samples exhibited favorable fluidity and dispersibility. Particle size became larger after hot storage due to ostwald ripening. The D10, D50 and D90 were 0.56-1.00, 0.88-1.53 and 1.77-2.68 μm for samples before storage and 0.76-1.02, 1.12-1.56 and 2.07-3.25 μm for samples after hot storage, respectively. Little change was observed for the suspensibility even after hot storage, of which the suspensibility ranged from 91.88% to 96.39% before storage and 91.91% to 96.13% after hot storage. Given the favorable performance the authors had measured which could satisfy the general requirements of SC quality control, only WSRHS and PRC were mainly optimized in this study. The ANOVA (analysis of variance) results of orthogonal design indicated that the dosage of T2700, xanthan gum and veegum had significant negative effects on the WSRHS and PRC which meant that both the WSRHS and PRC decreased with the increasing dosage of the three adjuvants. However, the dosage of NR1601 showed no significant impact on the two dependent variables. The viscosity of optimized sample based on orthogonal design was 229.6 mPa·s, while its fluidity and dispersibility were favorable. The suspensibility of the optimized sample before and after hot storage were (94.76±0.70)% and (93.50±0.20)%, respectively. The WSRHS of the optimized formula was (4.23±0.19)%, while the PRC was less than 10%. As for uniform design, PLS square model have a good predictability in predicting WSRHS, for which the sample WSRHS of the optimized formula was (2.55±0.03)% and the PRC being (4.36±0.21)%. The viscosity of optimized sample was 324.16 mPa·s, while its fluidity and dispersibility were favorable. The suspensibility before and after hot storage were (93.19±0.09)% and (92.77±0.22)%, respectively. The particle size was small and the size distribution was narrow. PLS linear model exhibited favorable predictability in predicting PRC. The PRC and WSRHS of the optimized formula were (7.75±0.14)% and (5.24±0.19)%, respectively. The predictability of stepwise regression models was poor for both the two properties. What’s more, the optimized formula was not optimum formula, of which the WSRHS was (9.51±0.20)% and the PRC was (16.63±0.19)%. Both the double screening stepwise regression and PLS were capable of optimizing the WSRHS and PRC at the same time while validation test confirmed that the former model matched the final results better, but unfortunately, even optimized formula of the former model was not optimum. 【Conclusion】 Although orthogonal design required a large test number, the data analysis method was simple and easy to grasp. Combining the main effect plots and ANOVA results, the preparation of clothianidin 30% SC was effectively optimized. Although the robustness of uniform design was poorer than orthogonal design, it required fewer experiments, which could significantly decrease financial cost. Ideal formula could also be obtained provided that the complicated statistics and analysis methods were mastered. |
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| Keywords: | orthogonal design uniform design partial least squares stepwise regression physical stability |
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