2023/24 Taught Postgraduate Module Catalogue
FOOD5472M Sensory Science
20 creditsClass Size: 100
Module manager: Dr Peter Ho
Email: p.ho@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2023/24
Module replaces
FOOD5600M, FOOD5471MThis module is not approved as an Elective
Module summary
This module will examine techniques used in the analysis of sensory properties, including food texture. It is also aimed at providing practical training in sensory analysis techniques and statistical methods for the analysis of sensory data.Objectives
On completion of this module students will be better able to1. Understand the principles and techniques for sensory measurement and analysis
2. Design, apply and interpret statistically valid sensory analysis methods to assess food quality and consumer preference
3. Understand the scientific principles and methods for measuring food texture and rheological properties
Learning outcomes
On completion of this module students will be better able to:
1. Understand the basic principles of sensory analysis and factors that affect sensory perception
2. Design and conduct sensory tests for selecting sensory assessors, sample preparation, and for the collection, analysis and interpretation of sensory data
3. Apply statistical methods for the analysis and interpretation of sensory data
4. Outline instrumental measurement techniques for food texture and discuss the relationship between sensory and food texture attributes
Skills outcomes
On completion of this module students will be better able to:
1. use computerised sensory tools to plan and design sensory tests
2. use statistical packages to analyse data from a range of different sensory analysis tests used in quality control, new product development and research.
Syllabus
This module will examine techniques used in the analysis of sensory properties, including food texture. It is also aimed at providing practical training in sensory analysis techniques and statistical methods for the analysis of sensory data.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Computer Class | 6 | 2.00 | 12.00 |
| Lectures | 15 | 1.00 | 15.00 |
| Practicals | 5 | 1.00 | 5.00 |
| Class tests, exams and assessment | 4 | 1.00 | 4.00 |
| Private study hours | 164.00 | ||
| Total Contact hours | 36.00 | ||
| Total hours (100hr per 10 credits) | 200.00 | ||
Private study
The module will be delivery using team-based learning. This requires students to do planned independent study and independent and group learning. The module is divided into 4 main content areas covering the learning outcomes and 1 for introducing the use of the team-based learning methodology. For each of the content areas, students are required to do a pre-assigned reading assignment prior to the first in-course MCQ. The MCQs will be divided into an individual and group MCQ. Feedback on MCQ will be provided immediately after the MCQs and students will work in teams where they can examine their answers and can submit an appeal against the group mark. Teams will be required to provide a written justification as to the reasons why they feel that the answer they provided should be provided with a mark. Independent learning is also required for the planned group assignment, which would allow for the contribution of each member of the team to the group assignment. This is essential as all group work will be peer assessed. Independent learning and private study is also required for the statistics assignment. Students should also consider spending 1 hour as part of their planned private study to prepare for the practical sessions. The remaining private study time should be used for report writing, reading and studying for in-course MCQs and the final exam.Opportunities for Formative Feedback
Feedback will be provided for each of the 4 subject area as follows. A Team Appeal’s session will be provided after each of the MCQs to allow students to discuss their answers. Answers to the MCQs will be provided. A group assignment for each subject area will be assessed with a 2500 word essay. Practical application (statistical analysis and practical sessions) will be assessed with individual report.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| In-course MCQ | 4 Individual MCQs | 20.00 |
| Computer Exercise | 4 Individual reports | 20.00 |
| Essay | 4 group essays | 50.00 |
| Self/Peer Assessment | A single online form | 10.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
The module will be delivery using team-based learning. This requires students to do planned independent study and independent and group learning. The module is divided into 4 main content areas covering the learning outcomes and 1 additional introductory unit for introducing the team-based learning pedagogical methodology. For each of the content areas, students are required to do a pre-assigned reading assignment prior to the first in-course individual MCQ. Feedback on MCQ will be provided in the form of a group MCQ and team appeals activity immediately after the MCQs, where students will work in teams to examine their answers. Independent learning is also required for the planned group essay assignment. A single peer assessment will account for individual contributions to the group assignment. Independent learning and private study are also required for the computer exercise. Students should also consider spending 1 hour as part of their planned private study to prepare for the practical sessions. The remaining private study time should be used for report writing, reading, and pre-assigned reading for in-course MCQs. A resit will be provided if any one of the assessment types results in a failure. These will be: 1. A single individual MCQ covering all areas examined by the 4 MCQs. 2. A single individual assignment for the computer exercise that examines what was covered by the 4 individual reports. 3. A single individual essay assignment that examines what was covered by the 4 group essays.
Reading list
The reading list is available from the Library websiteLast updated: 28/04/2023 14:55:42
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