Metadata
Title
FDSC30020
Category
general
UUID
6f9e54c8249e4eecb8183ccb4751fd96
Source URL
https://hub.ucd.ie/usis/!W_HU_MENU.P_PUBLISH?p_tag=MODULE&MODULE=FDSC30020&TERMC...
Parent URL
https://hub.ucd.ie/usis/!W_HU_MENU.P_PUBLISH?p_tag=COURSE&MAJR=FSS2&AUDIENCE=
Crawl Time
2026-03-23T20:06:51+00:00
Rendered Raw Markdown
# FDSC30020

**Source**: https://hub.ucd.ie/usis/!W_HU_MENU.P_PUBLISH?p_tag=MODULE&MODULE=FDSC30020&TERMCODE=202500&ACYR=2026
**Parent**: https://hub.ucd.ie/usis/!W_HU_MENU.P_PUBLISH?p_tag=COURSE&MAJR=FSS2&AUDIENCE=

Academic Year 2025/2026

Print

#### Food investigation (FDSC30020)

Subject:
:   Food Science

College:
:   Health & Agricultural Sciences

School:
:   Agriculture & Food Science

Level:
:   3 (Degree)

Credits:
:   5

Module Coordinator:
:   Professor Saskia van Ruth

Trimester:
:   Autumn

Mode of Delivery:
:   Blended

Internship Module:
:   No

How will I be graded?
:   Letter grades

Curricular information is subject to change.

This module will cover the theoretical background and the applications of food investigation techniques including intelligence analysis methods, root cause analysis methodologies and food product analysis techniques.

## About this Module

Open All 
 Close All

### What will I learn?

###### Learning Outcomes:

After successful completion of this course, students are expected to be able to:\
1. Explain the basic principles underlying the investigation of different classes of non-accidental food issues when using specific intelligence analysis, root cause analysis, and product analysis methodologies.\
2. Interpret selected data which demonstrate important aspects of qualitative and quantitative analysis.\
3. Develop food investigation strategies which require a diversity of modern methodologies and which must be often used in combination to achieve the desired result in practical use.\

###### Indicative Module Content:

The module focuses on the identification and comprehension of food issues using a wide variety of methodologies. The type of methodologies applied can be divided into three key course elements: (A): Intelligence analysis, (B) Root cause analysis and (C) Product analysis.

### How will I learn?

###### Student Effort Hours:

| Student Effort Type | Hours |
| --- | --- |
| Autonomous Student Learning | 72 |
| Lectures | 24 |
| Tutorial | 24 |
|  |  |
| --- | --- |
| Total | 120 |

\

###### Approaches to Teaching and Learning:

Activities involve lectures and group/individual assignments. \
\
Key theoretical lectures are delivered as a mix of on campus and online lectures. Lecture slides will be made available for all lectures for self-study. Relevant scientific papers will be available through Brightspace for the students to familiarise themselves with key concepts ahead of lectures.\
\
Group assignments on (A) Intelligence analysis, (B) Root cause analysis, and (C) Product analysis will be held weekly to reinforce learning and to apply the theoretical concepts delivered in the lectures. Each group will produce a factsheet (Assignment A: Intelligence analysis), a videoreport (Assignment B: Root cause analysis), and a poster with infographic (Assignment C: Product analysis). Finally, in week 12, students will individually conduct a class test on Intelligence analysis, Root cause analysis, and Product analysis.\
\
Attending group assignments and the final class test is mandatory.

### Am I eligible to take this module?

###### Requirements, Exclusions and Recommendations

Not applicable to this module.

\

###### Module Requisites and Incompatibles

**Pre-requisite:**\
FDSC20010 - Food Macronutrients, FDSC20020 - Nutritional Energy Metabolism, FDSC20090 - Food Macronutrients\
\
\
 \

### How will I be assessed?

###### Assessment Strategy

| Description | Timing | Component Scale | Must Pass Component | % of Final Grade | In Module Component Repeat Offered |
| --- | --- | --- | --- | --- | --- |
| Exam (In-person): In-class test, individual test on the applied food investigation technologies in week 12 | Week 12 | Alternative linear conversion grade scale 40% | No | 50 | No |
| Group Work Assignment: Assignment Intelligence analysis: Factsheet | Week 4 | Alternative linear conversion grade scale 40% | No | 10 | No |
| Group Work Assignment: Assignment Root cause analysis: Video report | Week 7 | Alternative linear conversion grade scale 40% | No | 20 | No |
| Group Work Assignment: Assignment Product analysis: Poster with infographic | Week 11 | Alternative linear conversion grade scale 40% | No | 20 | No |

\

###### Carry forward of passed components

No

\

### What happens if I fail?

| Resit In | Terminal Exam |
| --- | --- |
| Spring | No |

*Please see [Student Jargon Buster](https://www.ucd.ie/students/services/ucdstudentjargonbuster/) for more information about remediation types and timing.* \

### Assessment feedback

###### Feedback Strategy/Strategies

• Feedback individually to students, post-assessment\
• Group/class feedback, post-assessment\
• Peer review activities\

###### How will my Feedback be Delivered?

Not yet recorded.

### Associated Staff

| Name | Role |
| --- | --- |
| Mr Joris Boom | Lecturer / Co-Lecturer |
| Dr Aleksandra Konic Ristic | Lecturer / Co-Lecturer |
| Matta Asaad Mesak Ebaid | Tutor |

### When is this module offered?

**Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.**

|  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Autumn | Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Fri 09:00 - 10:50 |
| Autumn | Tutorial | Offering 2 | Week(s) - 1, 2, 11 | Wed 11:00 - 12:50 |
| Autumn | External & School Exams | Offering 2 | Week(s) - 12 | Wed 11:00 - 12:50 |
| Autumn | Tutorial | Offering 2 | Week(s) - 3, 4, 5, 6, 7, 8, 9, 10 | Wed 11:00 - 12:50 |

[Print this page](# "Print this page")