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：许多食品产品涉及多种成分的混合物，其中混合物的组成可通过各成分比例的组合加以描述。在某些情况下，产品质量及消费者偏好也可能受混合物加工方式的影响，而加工过程通常由一个或多个过程变量的设定值定义。研究混合物成分比例与过程变量设定值共同影响的实验设计被称为"混合物-过程变量实验"。本文展示了如何将混合物-过程变量实验与离散选择实验相结合，以量化并建模消费者对可视为加工混合物的食品产品的偏好。首先，我们描述了此类联合实验数据的建模方法；其次，阐述了如何生成面向涉及混合物与过程变量的选择实验的D-最优与I-最优设计，并通过两个实例对两类设计进行了比较。