Sensory and Consumer Tests Performed at the Sensory Science Center
At the WSU Sensory Science Center, we conduct a diverse range of sensory and consumer tests tailored to meet our clients’ needs. Additionally, we develop, and design specific testing and research opportunities as needed by our clients.
Testing Options
Consumer Acceptance and Preference
Determine the acceptance and preferences of your food, beverages, or other products through in-lab or at-home tests. We use acceptance, willingness to purchase, or preference questions to provide valuable insights.
Difference/Similarity Tests
Compare products to identify overall differences or probe-specific difference in attributes. Tests we employ include the triangle test, duo-trio, tetrad test, and difference from control tests. When a specific attribute is of interest, we use a ranked attribute test or a paired comparison.
Attribute Diagnostic Tests
Examine products for specific sensory attributes using “just-about-right” or check-all-that-apply questions. Insights gained inform how to adjust specific product properties to enhance overall liking.
Trained Panel Profiling
Benefit from evaluations by our trained sensory panels, covering appearance, aroma, flavor, taste, texture, and mouthfeel attributes for foods and beverages.
Threshold Determination
Utilize threshold testing to pinpoint the concentration of a flavor or taste compound that causes a change in perception.
Focus Groups
Engage in insightful discussions about products or services through tailored focus group sessions, structured around your specific information needs.
Statistical analysis provided by the Sensory Science Center
At the WSU Sensory Science Center, our expertise extends beyond sensory evaluation testing. Our team is proficient in employing various sensory analysis methods, including:
- Analysis of variance (with mean separation techniques) for parametric data.
- Kruskal-Wallis for non-parametric data.
- Cochran’s Q for check-all-that-apply data.
- Penalty Analysis and Chi Square for “just about right” questions.
- Friedman’s Rank Sum for ranked data.
- Multivariate techniques such as Principal Component Analysis, Partial Least Squares, Internal and External Preference Mapping, Factor Analysis, and Agglomerative Hierarchical Clustering.