Many food products involve mixtures of ingredients, where the mixtures can be expressed as combinations of ingredient proportions. In many cases, the quality and the consumer preference may also depend on the way in which the mixtures are processed. The processing is generally defined by the settings of one or more process variables. Experimental designs studying the joint impact of the mixture ingredient proportions and the settings of the process variables are called mixture-process variable experiments. In this article, we show how to combine mixture-process variable experiments and discrete choice experiments, to quantify and model consumer preferences for food products that can be viewed as processed mixtures. First, we describe the modeling of data from such combined experiments. Next, we describe how to generate D- and I-optimal designs for choice experiments involving mixtures and process variables, and we compare the two kinds of designs using two examples.

翻译：许多食品产品涉及成分的混合物，其中混合物可表示为成分比例的组合。在许多情况下，质量和消费者偏好也可能取决于混合物的加工方式。加工通常由一个或多个工艺变量的设定来定义。研究混合物成分比例与工艺变量设定共同影响的实验设计称为混合物-工艺变量实验。本文展示了如何结合混合物-工艺变量实验与离散选择实验，以量化和建模消费者对可视为加工混合物的食品产品的偏好。首先，我们描述了此类组合实验数据的建模方法。接着，我们阐述了如何生成涉及混合物和工艺变量的选择实验的D最优和I最优设计，并通过两个实例比较了这两种设计类型。