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Li B, Hayes JE, Ziegler GR. Interpreting consumer preferences: physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage. Food Qual Prefer. 2014;36:27-32doi: 10.1016/j.foodqual.2014.03.001.
Li, B., Hayes, J. E., & Ziegler, G. R. (2014). Interpreting consumer preferences: physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage. Food quality and preference, 3627-32. https://doi.org/10.1016/j.foodqual.2014.03.001
Li, Bangde, et al. "Interpreting consumer preferences: physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage." Food quality and preference vol. 36 (2014): 27-32. doi: https://doi.org/10.1016/j.foodqual.2014.03.001
Li B, Hayes JE, Ziegler GR. Interpreting consumer preferences: physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage. Food Qual Prefer. 2014 Sep 01;36:27-32. doi: 10.1016/j.foodqual.2014.03.001. PMID: 25024507; PMCID: PMC4094130.
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Food Qual Prefer. 2014 Sep 01;36:27-32. doi: 10.1016/j.foodqual.2014.03.001.

Interpreting consumer preferences: physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage.

Food quality and preference

Bangde Li, John E Hayes, Gregory R Ziegler

Affiliations

  1. Sensory Evaluation Center, College of Agricultural Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA ; Department of Food Science, College of Agricultural Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA.
  2. Department of Food Science, College of Agricultural Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA.

PMID: 25024507 PMCID: PMC4094130 DOI: 10.1016/j.foodqual.2014.03.001

Abstract

Designed experiments provide product developers feedback on the relationship between formulation and consumer acceptability. While actionable, this approach typically assumes a simple psychophysical relationship between ingredient concentration and perceived intensity. This assumption may not be valid, especially in cases where perceptual interactions occur. Additional information can be gained by considering the liking-intensity function, as single ingredients can influence more than one perceptual attribute. Here, 20 coffee-flavored dairy beverages were formulated using a fractional mixture design that varied the amount of coffee extract, fluid milk, sucrose, and water. Overall liking (

Keywords: Optimization; coffee milk; consumer insight; physicohedonic model; psychohedonic model; psychophysical model

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