FOOD9102 Sensory Analysis of Foods
The Complete Study & Assessment Guide · T3 2026FOOD9102 Overview
- UNSW Sydney
- Term 3 2026
- Postgraduate
- Quizzes and laboratory reports
- Food science
What the course is about
FOOD9102 Sensory Analysis of Foods is a postgraduate course in Food and Health at the School of Chemical Engineering, UNSW Sydney, offered in Term 3 2026. It starts from a commercial fact: a food can pass every instrument test and still fail if people do not like the way it looks, smells, tastes or feels.
- Assessed by Four 30-minute Moodle quizzes worth 30%, a group laboratory report worth 20% and two individual laboratory and reflection reports worth 50%.
- Hardest step Choosing the right test and the right guessing rate or tails, then turning a p-value into a sentence about the products.
- How to prepare Rework the Week 2 and Week 3 workshop problems with your own numbers, and revise each week before the quiz that follows it.
- What the reports reward Process and reasoning: a specific research question, a justified test, a correct analysis and explained biases with improvements.
How FOOD9102 is assessed
| Component | Weight | Format |
|---|---|---|
| Online quizzes | 30% | Four Moodle quizzes of 7.5% each, open on the Mondays of Weeks 2, 4, 7 and 10; 30 minutes, one attempt, about ten questions of varying marks |
| Group laboratory report | 20% | Report on the Week 4 discrimination laboratory; maximum five pages; due one week after the class (Week 5); team evaluation after submission |
| Individual laboratory and reflection reports | 50% | Report 1 (20%, maximum two pages) due one week after the Week 7 laboratory (Week 8); report 2 (30%, provided template) due one week after the Week 10 laboratory (Week 11) |
The UNSW Handbook record for 2026 and the Moodle assessment table list the same three components, and their weights total 100%. Within them, each quiz is 7.5%, report 1 is 20% and report 2 is 30%. Attendance at your three timetabled laboratory classes, in Weeks 4, 7 and 10, is compulsory, and the laboratory brief describes attendance and participation as a requirement for completing the course, so treat attendance as a condition to pass the course. The consequence of a missed class is not published as a number or threshold, so if you cannot attend, tell the course convenor as soon as you can, apply for Special Consideration and check the current rules on Moodle.
Assessment structure
Current FOOD9102 dates
| Date | Item | Control |
|---|---|---|
| Friday 16 October 2026 | Report 1 information released | 5:00 pm, ahead of the Week 7 laboratory |
| Friday 6 November 2026 | Report 2 information released | 5:00 pm, ahead of the Week 10 laboratory |
| Monday 16 November 2026 | Quiz 4 open | 12:00 am to 11:59 pm; 30 minutes, one attempt; Weeks 1 to 9 |
Dates are as published in the Term 3 2026 Moodle assessment hub and quiz pages. Confirm exact deadlines and submission settings in the live LMS.
What FOOD9102 covers
Ten chapters follow the course from the definitions of sensory science and the control of bias, through the statistics of discrimination and hedonic tests, to the physiology of taste and the laboratory reports.
Sensory Analysis and the Three Test Families
AIFST definitions of sensory science and sensory testing, why industry runs sensory tests, the five steps of a study, and the discrimination, descriptive and affective families (Week 1)This chapter sets up the vocabulary of the whole course.
- Sensory science and sensory testing, defined
- Sensory analysis as the final check on a finished product
- Seven reasons companies run sensory tests
- Discrimination tests: can people tell the difference?
- Descriptive analysis: how do the products differ, and how strongly?
- Affective tests: how much is it liked, and which is preferred?
Controlling Bias in Sensory Test Design
Associations, sensory fatigue, the halo effect, order bias, balanced serving orders, random three-digit codes, timing and the serving tray (Week 1)Panellists are human, so every sensory test is exposed to bias.
- What bias is and why panellists bring it
- Associations, fatigue and the halo effect
- Order bias and balanced serving orders
- Panel sizes that fit two-sample and three-sample designs
- Random three-digit codes instead of letters
- Timing, palate cleansing and pressure from onlookers
Statistics for Sensory Data: p-Values, Alpha and Error
Evidence not proof, the p-value and alpha level, statistical significance, standard deviation as error, mean and SD reporting (Week 1 workshop)Every sensory claim in this course ends in a statistical judgement.
- Statistics as evidence that a result is not luck
- Why forced-choice tests need a guessing baseline
- The normal distribution and its tails
- The p-value, alpha and statistical significance
- Standard deviation, error bars and reporting mean plus or minus SD
- How error decides whether a difference is significant
Discrimination Tests: 2-AFC, Triangle and Duo-Trio
Desired and undesired differences, overall versus single-attribute questions, the directional paired comparison, triangle, duo-trio and A-not-A tests and how to choose (Week 2)Discrimination tests ask whether a difference between products can be perceived.
- Wanted and unwanted differences between products
- Overall (unspecified) versus single-attribute (specified) questions
- The 2-AFC and its forced choice
- Non-directional paired comparison and same-different tests
- The triangle test and its six serving orders
- The duo-trio and A-not-A tests for reference matching
Binomial Analysis of Discrimination Data
The binomial probability, guessing rates of one half and one third, the p-value as a tail sum, minimum-correct tables and choosing alpha (Week 2)This chapter turns a count of correct answers into a verdict.
- Two outcomes per ballot and the guessing rate p
- The binomial probability of exactly x correct
- The p-value as the tail of x or more correct
- Reading the minimum-correct tables
- Choosing alpha and the risk of a false positive
- Writing the conclusion about the products
Sensory Scales and Hedonic Acceptance Tests
Acceptance versus preference, nominal, ordinal, interval and ratio scales, the 9-point hedonic scale, line scales and their biases, Likert, FACT, pictorial and JAR scales (Week 3)Affective tests ask how much people like a product or which version they prefer.
- Acceptance tests and preference tests
- Nominal, ordinal, interval and ratio scales
- The 9-point hedonic scale and its scores
- Intensity scales versus liking scales
- Line scales, central tendency and relativity bias
- Likert, FACT, pictorial and JAR scales
Analysing Hedonic Data with t-Tests and ANOVA
Comparing mean liking scores, one-tailed and two-tailed t-tests, ANOVA with multiple comparisons and writing the conclusion (Week 3)Hedonic data are numbers, so products are compared through their mean scores and spread.
- Comparing two means with their error
- One-tailed and two-tailed tests from the research question
- Running a t-test in Excel or an online calculator
- ANOVA for three or more samples
- Reading overall and pairwise p-values
- Plotting means with standard deviation error bars
JAR Scales and Penalty Analysis
Unipolar and bipolar just-about-right scales, the 75% benchmark, mean drops, proportions and the penalty plot (Week 3)A just-about-right scale tells a developer whether an attribute is too weak, too strong or right, and penalty analysis says which of those faults matters most.
- Just-about-right scales and their ideal point
- Unipolar and bipolar layouts
- The 75% JAR benchmark
- Pairing JAR ratings with overall liking
- Mean drop and proportion of panellists
- Reading the penalty plot to set priorities
How We Taste: Physiology and Product Design
Flavour as taste plus smell, chemosensory pathways, the five taste modalities and their receptors, perception from receptor to preference, and taste-led product concepts (Week 4)The Week 4 lecture explains what panellists are detecting when they taste.
- Flavour as taste plus smell
- Gustation, olfaction and chemesthesis
- Sweet and umami receptors from the T1R family
- Bitter T2R receptors and adaptation
- Salt taste through the ENaC sodium channel
- From stimulation to perception and preference
Ballot Papers, Serving Plans and the Lab Report
The Week 4 discrimination laboratory, ballot anatomy, the eight report questions, the five-page format, the marking criteria and the individual reportsThis chapter prepares you for the laboratory weeks. It walks through the Week 4 discrimination laboratory, the three experiments and their ballots, how to read the test type off a ballot and how the class data are collected.
- The patties, biscuits and cupcakes experiments
- Reading the test type from the ballot wording
- Running the class: trays, rounds and tally sheets
- The eight questions of the group report
- The five-page budget by section
- The 20-mark marking criteria
The course teaches why consumers perceive food the way they do, how sensory science is used across the food industry, and how to design, run and analyse your own sensory tests with sound statistics.
The first three weeks cover the theory and the numbers. Week 1 defines sensory science and sensory testing, sets out the sources of bias and how a balanced serving design controls them, and revises p-values, alpha and error.
Week 2 is discrimination testing: the 2-AFC, triangle and duo-trio tests and their analysis with the binomial distribution. Week 3 is affective testing: hedonic, line and just-about-right scales, t-tests, ANOVA and penalty analysis.
Weeks 4 and 5 turn to the physiology and psychology of taste, and the later weeks cover preference tests, descriptive analysis, quality assessment and consumer research alongside three laboratory classes.
How you are assessed
Online quizzes are worth 30%: four Moodle quizzes of 7.5% each, open for 24 hours on the Mondays of Weeks 2, 4, 7 and 10, timed at 30 minutes with one attempt.
A group laboratory report on the Week 4 discrimination laboratory is worth 20% and is limited to five pages. Two individual laboratory and reflection reports are worth 50% together: report 1 (20%, at most two pages) follows the Week 7 laboratory, and report 2 (30%, on a template) follows the Week 10 laboratory. Each report is due one week after its laboratory class.
Attendance at the three laboratory classes is compulsory, and the laboratory brief makes attendance and participation a requirement for completing the course, so treat it as a condition to pass the course; the consequence of a missed class is not published as a number or threshold beyond Special Consideration, so check the current rules on Moodle.
What this guide covers
Ten chapters rebuild the Week 1 to Week 4 teaching and the laboratory brief, each with a worked example that uses its own numbers, practice questions with answers and a figure.
A practice chapter sets three mock quizzes, and a closing chapter takes you through quiz day and report day.
Worked example · free
Duo-trio test on a reformulated sports drink
- 1Identify the test and its guessing rate: a duo-trio test has two choices, so the probability of a correct guess is P = 1/2, and chance alone expects 15 of 30 correct.
- 1Find the p-value as a tail: P(X ≥ 21) for n = 30 and P = 1/2 is 0.0214, the probability of 21 or more correct if everyone guessed.
- 1Compare with alpha and the table: 0.0214 < 0.05, and the table needs 20 at 0.05; but 0.0214 > 0.01, and the table needs 22 at 0.01.
- 1Conclude about the products: at alpha 0.05 the panel could tell the new drink from the current one, so the sweetener change is noticeable; at alpha 0.01 the evidence falls short.
Key terms
- Sensory science
- Sensory science is the scientific study of how people perceive and react to foods through sight, smell, taste, touch and hearing.
- Sensory testing
- Sensory testing is a scientific method for determining the sensorial properties of a food product under a controlled protocol.
- Bias
- Bias is anything other than the factor being tested that alters how panellists perceive the samples and so changes the results.
- Discrimination test
- A discrimination test establishes whether panellists can perceive a difference between products, without measuring how large it is.
- Triangle test
- A triangle test serves three coded samples, two alike and one different, and asks the panellist to identify the odd one.
- Duo-trio test
- A duo-trio test asks which of two coded samples matches a labelled reference sample.
- Binomial distribution
- The binomial distribution gives the probability of each number of correct answers when every panellist has the same chance of guessing correctly.
- p-value
- A p-value is the probability of a result at least as extreme as the one observed if chance alone were operating.
- Alpha level
- The alpha level is the threshold set in advance for significance, usually 0.05, and equals the accepted risk of a false positive.
- Hedonic scale
- A hedonic scale is an interval scale of liking, most often nine points from dislike extremely to like extremely.
- Line scale
- A line scale is a continuous line, typically scored from 0 to 100 or 0 to 150, on which a panellist marks a rating.
- JAR scale
- A JAR scale asks whether an attribute is too weak, just about right or too strong, centred on an ideal point.
- Penalty analysis
- Penalty analysis pairs JAR ratings with overall liking to show how much each attribute fault lowers liking and how many panellists it affects.
- Chemesthesis
- Chemesthesis is the chemical sensing of irritation and spiciness in the mouth, separate from taste and smell.
FOOD9102 FAQ
Is there an exam or is it all coursework?
The official assessment table lists three components: online quizzes worth 30%, a group laboratory report worth 20% and individual laboratory and reflection reports worth 50%. The quizzes are four 30-minute Moodle quizzes of 7.5% each, and every report is due one week after its laboratory class, so the workload is spread across the term.
What do the online quizzes cover and how do they run?
Each quiz opens for 24 hours on the Monday of Week 2, 4, 7 or 10, is timed at 30 minutes and allows one attempt. Quiz 1 covers foundational statistics and Week 1; later quizzes are cumulative, reaching Weeks 1 to 9 by Quiz 4. Expect multiple choice, fill in the blank, short answers and longer answers of a few sentences.
How much statistics do I need for sensory analysis?
You need to know what a p-value and an alpha level are, how error and standard deviation affect significance, and how to read the output of a t-test and an ANOVA. For discrimination tests you compare the number of correct answers with the binomial distribution, usually through the minimum-correct tables provided on Moodle.
How do I choose between a triangle test, a duo-trio and a 2-AFC?
Use a triangle test when you want to know whether there is any overall difference; a 2-AFC when one named attribute has been deliberately changed in a known direction; and a duo-trio or A-not-A test when samples must match a reference, as in quality assurance, formulation changes and shelf-life work. The guessing rate is 1/3 for the triangle and 1/2 for the others.
What does the group laboratory report need to include?
It answers eight questions from the brief: the research question and wider objective, the test type and its suitability, the serving order, the analysis of your test's class data, conclusions about the products, biases and improvements, and reflections on running the tests. The introduction takes about one page, the results and discussion three and a half, and the conclusion half a page.
Where do students lose marks in the quizzes?
The Quiz 1 feedback reported a class average of 94% but flagged two weaknesses: research questions that were not specific or answerable, and lists of biases without explanations. Name the samples in every research question, and for each bias say how it would change perception and how your design prevents it.
When should I use a one-tailed rather than a two-tailed t-test?
Use a one-tailed test only when the research question states a direction in advance, such as whether a reformulated product is liked more than the original. When the question simply asks whether liking differs, test both directions with a two-tailed test, which is also the more conservative choice when you are unsure.
Is attendance at the laboratory classes compulsory?
Yes. Attendance at each of your three laboratory classes, in Weeks 4, 7 and 10, is compulsory, and the laboratory brief makes attendance and participation a requirement for completing the course, so treat it as a condition to pass the course. The consequence of missing one is not published as a number or threshold; contact the convenor, apply for Special Consideration and check Moodle.
Questions students ask in each FOOD9102 chapter
- Why do companies still need people when instruments can measure texture and colour?
- Instruments describe the product, but only people can say how it is perceived and whether they would buy it. The Week 1 lecture places sensory analysis after the safety, quality and physical tests for exactly that reason, and frames its purpose as understanding the relationship between consumers and a food's sensorial properties. Chapter 01 · Sensory Analysis and the Three Test Families
- Why should samples carry three-digit codes rather than letters?
- Letters and single digits carry built-in rankings and associations: people read A as better than B, or link a letter to a fruit. Randomised three-digit codes carry no meaning, provided you check the set for accidental patterns such as mirrored numbers or one code that stands out from the rest. Chapter 02 · Controlling Bias in Sensory Test Design
- What does p < 0.05 actually mean?
- It means that a result at least this extreme would occur less than 5% of the time if chance alone were at work. That is strong enough evidence, by the usual convention for sensory data, to call the difference real. It is evidence rather than proof, and the conclusion should say what it means for the samples. Chapter 03 · Statistics for Sensory Data: p-Values, Alpha and Error
- When is a discrimination test a waste of money?
- When the difference is obvious. The lecture is clear that discrimination tests are for subtle differences, where you genuinely do not know whether consumers can tell. Testing a difference everyone can see or taste yields no useful data, although a change that is obvious to the company may still be subtle to the general population. Chapter 04 · Discrimination Tests: 2-AFC, Triangle and Duo-Trio
- Why add up all the higher counts instead of using the probability of my exact count?
- Because a p-value covers your result and every result more extreme than it. The probability of exactly your count is always smaller than the tail, so using it makes results look more significant than they are and can flip a verdict that sits close to alpha. Chapter 05 · Binomial Analysis of Discrimination Data
- Why is the 9-point hedonic scale treated as numeric data?
- Because its points are equidistant, both on the page and mathematically. That makes it an interval scale rather than an ordinal one, so responses can be converted to scores from 1 to 9 and analysed with means, standard deviations, t-tests and ANOVA. Chapter 06 · Sensory Scales and Hedonic Acceptance Tests
- Why not just run t-tests between every pair of samples?
- With three samples you would need three t-tests, and the number grows quickly as products are added. ANOVA compares the variance among all the means at once, then its multiple comparisons show which pairs differ, which the lecture presents as the faster route. Chapter 07 · Analysing Hedonic Data with t-Tests and ANOVA
- Why does a JAR test need a hedonic question as well?
- The JAR question alone shows how many people think an attribute is off, but not how much that costs in liking. Pairing it with an overall liking score lets you calculate a mean drop for each fault, which is what a penalty analysis ranks. Chapter 08 · JAR Scales and Penalty Analysis
- What is the difference between taste and flavour?
- Taste is gustation alone: sweet, sour, salty, bitter and umami. Flavour combines taste with smell, including aromas reaching the nose from the mouth, which is why the lecture writes flavour as taste plus smell. Chapter 09 · How We Taste: Physiology and Product Design
- How long can the group laboratory report be?
- A maximum of five pages, not counting the reference list and appendices, which must still be included. The brief suggests about one page for the introduction, three and a half for results, analysis and discussion, and half a page for the conclusion. Chapter 10 · Ballot Papers, Serving Plans and the Lab Report
How to prepare for the assessments
Work the course in the order it is taught and keep pace with the quizzes, because each one sits just before a laboratory class and checks that you can run it. In Week 1, learn the definitions closely and practise explaining each bias with its effect and its control, since that is where the first quiz separated students.
In Week 2, drill the discrimination tests as a decision: what must the test show, which test answers it, what is the guessing rate, and what panel size suits the serving orders. Then practise reading the minimum-correct tables and checking a tail with a binomial calculator until the comparison with alpha is automatic.
In Week 3, rehearse the choice between a t-test and an ANOVA, decide the tails from the wording of the question, and work a penalty analysis by hand at least once. Before each laboratory, reread the brief and draft the research question you think the test answers. After it, write the results paragraph in four beats: test, number, alpha and products.
When an analysis will not come out, ask Sia to walk through it with fresh numbers and check each step against your own working.
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