Advanced Sensory and Consumer Measurement

SHORT COURSE

Advanced Sensory and Consumer Measurement
Current knowledge and emerging science

Learn to custom-design evaluation tests for specific food products

10-12 August 2010

Venue:
The University of Reading

Taught by
Professor Michael O’Mahony

University of California
Davis

Course Organiser
Hal MacFie
Bristol

About the Course

This course is designed for both the beginner and the more experienced professional who want an overview of sensory evaluation as it is applied to both sensory assessors and naïve consumers and wish to understand the reasons why tests can be set up in some ways and not in others. The latest state-of-the-art techniques are explained clearly with enough of the theory behind the tests so that the sensory professional can see why tests are set up in specific ways. From this base, the professional can modify and custom-design techniques specific to the product being tested. Frequently, sensory professionals try to fit the food to the test rather than design a test for the food. For example, methods used to test tomatoes will not work well for hot peppers.

The course is not a 'hands-on' beginning class that provides experience in using a 9-point hedonic scale. We assume you can do that already. Rather, the class tells you why a slight change in the wording of the instructions to the judges or consumers can make the test more powerful or ruin it completely. The course also provides explanations of how the sensitivity of a test can be altered by changing the order of tasting and why you might want to do this; how to make your scaling procedure more powerful; and how to avoid response bias. In addition, it looks at new approaches to consumer testing and product optimisation.

The course gives an excellent and lively overview that ties up loose ends for the sensory professional who wants to do more than blindly follow directions. It also provides a simple and entertaining introduction for the beginner who wants to understand what is going to happen in the hands-on situation.

ABOUT Michael O'Mahony

Michael O'Mahony is a professor in the in the Department of Food Science and technology, UC Davis, and author of Sensory Evaluation of Food: Statistical Methods and Procedures and over 150 published journal articles. A consultant to the food industry in the United States, Canada, Europe,Japan, Korea and China, he is also a popular lecturer in America, Asia and Europe where he is recognised for his ability to communicate concepts in a way that is easily understood.

TOPICS

Day 1

9a.m. – 1p.m, 2.00p.m. - 5.00p.m.
	The senses and brain processing associated with consumer perception of the sensory characteristics of food. Psychological and physiological effects and how they interfere with sensory measurement: demand characteristics, suggestion, sensory adaptation, fatiguing. How the brain protects itself from information overload. Illusions and misperceptions How they can affect consumer choice.

	Applications and goals of sensory evaluation, consumer testing and psychophysics in industrial and research settings. How the methods from one area can be wrongly applied to another.

	Why there is more than one type of sensory evaluation. How it can be used in quality assurance, new product development, storage, packaging, reformulation and processing studies as well as basic research. Analytical Type I and market-oriented Type II testing. Possible shortcuts. How does this relate to consumer choice.

	The testing environment: how the right testing conditions control bias. Use and abuse of sensory testing.

	How well can consumers discriminate small changes in the sensory characteristics of foods and other products? What tests should be used to measure this? An examination of difference tests. What is response bias? Why is it essential to control response bias in difference testing? The strategies used to circumvent the problem: forced-choice procedures and signal detection measures, beta and tau criteria. How a slight change in the instructions can ruin a test.

	Types of forced-choice difference tests. How they solve the problem of response bias: paired comparison, triangle, 3-AFC, duo-trio, dual standard, tetrad, octad, two-out-of –five etc. A-Not-A, same-different, 4 IAX tests. Why the A-Not-A and same-different tests have inherent response bias. How inherent response bias can be avoided. Why the same-different method can be the test of the future for consumer discrimination measures. Solutions to problems.

	Preference tests. The ‘no preference’ option. How to get round inherent response bias with a placebo. Practical applications. Many possible forms of analysis for preference tests. Other methods of avoiding response bias. Ongoing research.

	Why judges perform better on some tests than others. An introduction to Thurstonian models, inadequacies of binomial statistics, beta binomial test, d'’analysis of difference and preference tests, statistical power of tests.

	19.30 Course Dinner

Day 2

9a.m. – 1p.m, 2.00p.m. - 5.00p.m.
	Sequencing effects on sensitivity, S.S.A. analyses and effects of memory.

	Appropriate tests for analytical difference testing and for testing consumer discrimination. Test sensitivity, most sensitive tests, warmed-up paired comparisons, Why consumers might not need the most sensitive test.

	Application of difference and preference tests in an industrial setting: testing reality. Home use, central location etc.Getting qualitative data at the same time as quantitative data: application of psychophysical techniques-----------Estimation of population parameters from sample values.

	Signal detection strategies for getting around response bias. Hits, misses, false alarms and correct rejections------------ ROC analyses, d’,’ P(A) computations . Testing assumptions. Practical applications-Introduction to R-Index ananlyses. Introduction to scaling. Nature of numbers. Goals of scaling.

	19.30 Course Dinner

Day 3

9a.m. - 1p.m., 2 p.m. – 5 p.m.

	The properties of numerical estimation. Scaling methods, category scales, line scales, magnitude estimation, time-intensity, other scales, ranking, two stage ranking, rank-rating methods and effects of memory.

	Hedonic scales, just right scales and centering bias. Alternatives: hedonic ranking with R-Index analysis.

	Why the numbers from these scaling techniques are not proper numbers. End effects, anchoring. How long should your scale be when testing consumers ?. Why data from scaling with consumers is relative, not absolute. Consequences of consumers using relative scaling.

	How to analyze numerical data from scaling techniques. Why this breaks basic statistical assumptions. What you can do about it. Thurstonian and signal detection approaches.

	Common uses and abuses of scaling. Badly designed studies. What is the best way of getting numbers from consumers?

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