Consumer perception of milk with different fat content: Integrating check-all-that-apply, quantitative descriptive analysis, rate-all-that-apply, and facial emotion analysis
Year: 2025
Type: article
Abstract: As public concern over the potential health risks associated with high-fat diets intensifies, the market for low-fat dairy is experiencing a surge in demand. However, sensory characteristics, including flavor and mouthfeel, significantly influence consumer preferences, underscoring the importance of understanding how these attributes affect overall acceptance of milk. This study employs check-all-that-apply, quantitative descriptive analysis, rate-all-that-apply, and facial emotion intensity to dissect the sensory attributes of skimmed, low-fat, and whole milk and their influence on consumer satisfaction. The findings indicate that whole milk is rated higher in terms of mouthfeel thickness, milkiness, creaminess, and overall preference, whereas skimmed and low-fat milks are perceived as less favorable. Consumers can recognize differences in milk fat content by selecting descriptive terms, with 12 sensory terms serving as key discriminators. Facial emotion analysis reveals significant emotional responses from consumers before and after swallowing different milk types, with whole milk provoking more pronounced positive emotions. Positive sensory attributes of milk are positively correlated with consumers' pleasurable emotional responses. Five pivotal indicators, including happy emotions before swallowing, serve as potential markers for distinguishing milk with varying fat content. Our findings provide new insights into flavor design and marketing strategies for low-fat dairy products.
Source: Journal of Dairy Science
Authors: Xuelu Chi, Jianfeng Wang, Jian He, Weizhe Wang, Yanmei Xi, Lunaike Zhao, Yufang Su, Aoyi An, Baoguo Sun, Nasi Ai
Institution: Beijing Technology and Business University
Language: English
Subfield: Food Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,500
Awards: G6409790383, G7910640822
OpenAlex ID: W4415015661
