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首页> 外文会议>Symposium on Pesticide Formulations and Application Systems: A New Century for Agricultural Formulations, Twenty First Volume, Oct 24-26, 2000, Orlando, Florida >Strategies for Agricultural Formulations: A Statistical Design Approach
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Strategies for Agricultural Formulations: A Statistical Design Approach

机译：农业配方策略：一种统计设计方法

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摘要

The traditional approach used by formulators of agricultural and pesticide formulations relies heavily on experience, and has been quite valuable in generating acceptable formulations that may or may not be at a global optimum. However, it can be time consuming, and it generally lacks the ability to provide a global view of the contributions of the different components to the performance of the whole. Additionally, the approach does not permit the use of the collected information to investigate or predict the behavior of formulations within the composition space without carrying out further experimentation. In the statistical design approach, one begins with the definition of objectives and constraints, then sets up the experiment with the appropriate response factor measurements. After data collection, a best-fit mathematical model is generated to describe the results and can be displayed graphically in various ways for various purposes. Among other things, model analysis typically reveals how each component contributes to the properties being measured. The model is used to locate optimum performance regions that balance the properties of the different components and satisfy any other constraints that are imposed. Scenario analysis can then be used to predict the performance as component levels are changed. In this work, we will discuss the conceptual framework of the statistical design approach, and exemplify its usefulness with an emulsifiable concentrate formulation.
机译：农业和农药配方设计者使用的传统方法在很大程度上依赖于经验，并且在产生可以或可能不是全球最佳的可接受配方方面非常有价值。但是，这可能很耗时，并且通常缺乏提供不同组件对整体性能贡献的全局视图的能力。另外，该方法不允许在不进行进一步实验的情况下使用收集到的信息来调查或预测组合物空间内制剂的行为。在统计设计方法中，首先要定义目标和约束，然后使用适当的响应因子测量值来进行实验。收集数据之后，将生成一个最合适的数学模型来描述结果，并可以出于各种目的以各种方式以图形方式显示该模型。除其他事项外，模型分析通常会揭示每个组件如何对所测量的特性做出贡献。该模型用于定位最佳性能区域，该区域可以平衡不同组件的属性并满足施加的任何其他约束。然后，可以使用方案分析来预测组件级别更改时的性能。在这项工作中，我们将讨论统计设计方法的概念框架，并通过乳油配方举例说明其实用性。

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