XCU-30307 Sensory Science III: Advanced Sensory Methods and Sensometrics

Course

Credits 7.50

Language of instruction:

English.

Assumed knowledge on:

HNE-30506, HNE-30606, MAT-20306 or MAT-24306.

Continuation courses:

XCU-30407.

Contents:

The course provides and overview of recent and advanced sensory analysis methods and data analysis approaches in sensory science. The students learn a framework for the optimal design of sensory experiments and for analysis of results under given practical constraints. Theoretical aspects and exercises on factorial experimental designs, reliability of sensory testing methods (including descriptive analysis, discrimination testing and time-intensity) will be presented and discussed.
The students will learn to assess statistical power and test sensitivity for different sensory methods using pre- test simulations. New variants of rapid sensory analysis methods and hybrid methods in consumer research will be assessed for their merits and shortcomings in quality control and product development. This will be supported by practical exercises. Different multivariate data analysis methods and the fields of applications within sensory science will be presented and discussed. Hands-on exercises on multivariate modelling for exploring and predicting relationships between sensory data and other data, e.g. from production processes will be introduced. The following aspects will be covered:
- experimental designs (complete/incomplete block, factorial, mixture designs, etc.) ;
- multivariate statistics and applications with sensory and consumer data;
- power estimation and test reliability in simulations;
- principles of Thurstonian and signal detection theory in discrimination testing;
- overview and applications of fast descriptive sensory methods in R&D and QC.

Learning outcomes:

After the course, students are expected to:
- know the applications and limitations of different sensory statistical analyses;
- be able to choose the right data methods and design for sensory studies;
- interpret the results of a sensory experiment in a correct way;
- have basic knowledge of, and can work with, different statistical software programs;
- have a basic working knowledge of the scopes and applications of advanced and emerging sensory methods.

Activities:

Lectures, theoretical and practical exercises, seminars and excursions.

Examination:

A written exam. Requirement for attending exam: Laboratory work carried out, presentations given at colloquia, report submission.

Literature:

To be announced.