成分
过程(计算)
实验设计
变量(数学)
质量(理念)
计算机科学
偏爱
数学
计量经济学
统计
化学
食品科学
数学分析
哲学
认识论
操作系统
作者
Mario Becerra,Peter Goos
标识
DOI:10.1016/j.foodqual.2023.104928
摘要
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.
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