MCB-32806 Advanced Sensory Methods and Sensometrics

Course

Credits 6.00

Language of instruction:

English

Assumed knowledge on:

HNE-30506 Principles of Sensory Science; Advanced Statistics (MAT-20306 Advanced Statistics or MAT-24306 Advanced Statistics for Nutritionists).

Continuation courses:

HNE-30606 Instrumental Sensory Science and MCB-33306 Integrated Sensory Science; Thesis Sensory Science and Eating Behaviour.

Contents:

How does reformulating a product to reduce, e.g., its fat or sugar content, will affect consumer acceptance? Which sensory attributes explain best a consumer liking or healthiness perception? How can we approach this information? This advanced course provides students with the necessary tools to start becoming independent researchers in the growing area of sensory and consumer methods. Students will gain deeper insight in how to perform sensory tests (scope, application, testing environment, and methods) and conduct advanced analyses of sensory and consumer data. Theory will be combined with hands-on exercises including: analysis of sensory panel performance, descriptive sensory analysis (QDA, FCP, Flash Profile, CATA), holistic sensory methods (Sorting, Napping), acceptance testing and relations to external data (including Drivers of Liking, Preference Mapping, and Ideal Profile Mapping). The methods will be presented, discussed, and assessed for their merits and shortcomings in R&D.
The software used for the statistical analyses will be R. The students will become familiar on how to programme the basics in R language to be able to understand and analyse their data, and know the underlying principles of each statistical method in this course.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- provide an overview of current and advanced analytical and affective sensory test methods, their scopes, and applications;
- demonstrate knowledge on experimental sensory test designs and data analysis by means of univariate and multivariate statistical methods;
- identify the applications and limitations of different data analyses;
- evaluate the sensory test objective in relation to selecting the appropriate test method and experimental setup;
- correctly interpret results of sensory experiments;
- reflect on sensory methods and data analysis tools in realistic sensory and consumer evaluation situations;
- demonstrate working knowledge of the statistical software program R in sensory applications.

Activities:

Lectures
Several topics related to the field of sensory science and consumer methods will be addressed. The first week is dedicated to provide a global picture of the methods and a solid statistics base, the second week is dedicated to design of experiments and attribute-based methods, the third to qualitative/holistic approaches, the fourth week to liking and techniques that combine the sensory and the hedonic data, and the final weeks to work on the group projects.

Extensive practical training
The techniques and methods described in the lectures will be analysed in R with existing datasets. The extensive practicals aim to let the students get further acquainted and practice themselves the techniques learnt with exercises, and to conduct on their own (in groups) a project. Videos with tutorials will be available for them to review the main steps for each analysis. Additionally, students will be able to deepen their knowledge of the theoretical aspects of the analyses.

Intensive practical training
During the intensive practicals students will gain empirical experience on how to conduct experiments, mostly in the PC rooms with visual stimuli. Importantly, a step-by-step in-depth explanation of the exercises provided during the extensive practical training will be delivered and discussed.

Examination:

Written exam (70 %; individual mark), the group report of practical work (20%) and the individual performance during the course and assignments (10%)
Attending all lectures and doing the group work is required. For the written exam at least an 5.5 is required to pass this course.
Check the course guide for details on examination.

Literature:

Strongly advised to follow: Analysing Sensory Data with R (ISBN: 9781466565722)
As other support:
- Rapid Sensory Profiling Techniques, 1st Edition (ISBN: 9781782422488)
- Novel Techniques in Sensory Characterization and Consumer Profiling (ISBN: 9781466566293)
- Sensory Evaluation of Food: Principles and Practices. 2nd ed. (ISBN: 13 978 1441964878)