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Tuesday, August 13, 2013

PPT On Methods For Sensory Testing


Methods For Sensory Testing Presentation Transcript: 
1.Is this the best way to evaluate products?...

2.Describe what is she doing ?

3.Get motivated, familiar and … ?

4.Methods For Sensory Testing
Before carrying out sensory testing:
Researcher must be thoroughly familiar with each method – its advantages and disadvantages
Researcher must precisely define his objectives & what information he is expected to collect
With above information, he should select the most practical & efficient method

5.Before carrying out sensory testing:
Researcher must be thoroughly familiar with each method – its advantages and disadvantages
Researcher must precisely define his objectives & what information he is expected to collect
With above information, he should select the most practical & efficient method
Discriminatory/ Difference tests
Used to determine whether a difference exists between samples
The panelists does not allow his personal likes and dislikes to influence his response/ judgment
Preference/ Acceptance tests
Tests based on a measure of preference or a measure from which relative preference can be determined
The personal feeling of a panelist toward the products directs his response
Descriptive tests
Used to determine the nature & intensity of the differences

6.Interpretation of sensory test results
All sensory experiments must be planned in advance, to make them > efficient
Interpretation of sensory test results cannot be made by direct examination, due to variability of sensory test results
Results must be tested by statistical methods:
These methods compare the results actually obtained with those that would be obtained by chance alone
Results are usually expressed in degrees of significance, which is the probability that the results are caused by chance

7.Types of tests

8.Difference/discriminatory tests
Triangle test
Test is very useful in:
QC work – to ensure samples from different production lots are the same
Ingredient substitution or change in manufacturing – to determine if change results in detectable difference in product
Panelists selection (often used)
Panelists receive 3 coded samples. Two of the samples are the same (i.e.duplicate samples) and one is different (odd sample). The panelist is asked to identify the odd sample
Note: panelist is asked to find/detect any differences

9.Results of a triangle test indicate whether or not there is a detectable difference between two samples
As number of judgments increases, % of correct responses required for significance decreases
Higher level of significance do not indicate that the differences is greater but there is less probability of saying there is a difference when the fact there is none
Eg. Of questionnaire – pg 21
Analysis of results – pg 22
Advantages of test:
Researcher receives information on size difference between samples
Researcher also receives information on product acceptance (although results need to be confirmed by a preference test)

10.Simple paired comparison tests
A pair of coded samples is presented to panelists for comparison on the basis of some specific characteristics. Eg. sweetness
Applications are similar to triangle test
Fewer samples are required & there is less tasting (however, statistically test is less efficient, as the probability of selecting a sample by chance is 50% or ½)
Test gives no indication of the size difference between the two samples
Eg. Of questionnaire – pg 23
Analysis of results – pg 24

11.Multiple paired comparison tests
When there are >2 samples to be evaluated, each must be compared with every other sampler for a single attribute
The number of pairs is determined by the formula:
where n =no. of samples or treatments
Useful for sets of three to six samples to be evaluated by a relatively inexperienced panel
A panelist is presented with one pair of sample at a time in random  order with the question, “ Which sample is sweeter?”
The panelist will be continue to evaluate all possible pairs that can be formed from the samples
Results will be evaluated by a Friedman – type statistical analysis (excluded from syllabus)

12.Duo-trio test
Three (3) samples are presented to panelists; one is labeled as R (reference) & the other two are coded
Panelist has to identify the odd/different sample
Test has the same application as the Triangle test, but is less efficient, as the probability of selecting the correct sample by chance is 50% or ½
Test is often used instead of triangle test when tasting samples that have a strong flavour because less tasting is required
In this test panelist bases his judgment on any difference he can detect (compare with Paired comparison test)
Eg –questionnaire – pg 30
Analysis of results – pg 30 -31

13.Multiple comparison test
Test is used to examine the effects of replacing/changing an ingredient, packaging material, process or storage
Panelist is presented with a known reference/standard sample (labeled as R) & together with several coded samples
Panelist has to compare each coded sample with reference sample on the basis of specific characteristics
Test is used very efficiently to evaluate 4 or sample 5 at a time
Small differences between samples &R can be detected
Test gives information about size & direction of difference
Eg of questionnaire – pg 32
Analysis of results – pg 33 -37

14.Ranking test
Panelists receives 3 or more coded samples and has to rank them for intensity of a specific characteristics
A rapid test and allows testing of several samples at once
Test is generally used to screen one or two of the best samples from a group of samples
No indication of size of differences between samples
Results from 1 set of rank cannot be compared with the results of another set of ranks
Eg of questionnaire – pg 38
Analysis of results –
Method I – Comparison of rank totals with rank totals in Chart 5 (pg 38 -39)
Method II – ANOVA (pg 39 -41) – excluded from syllabus

15.Scoring test
Coded samples are evaluated for the intensity of a specific characteristics
Panelists records his judgment on a graduated scale
Intervals on the scale can be labeled with numbers or descriptive terms
For effective results, descriptive terms must be carefully selected
Size & direction of difference between samples can be obtained
Include standards at various points if possible:
To minimise panel variability
To prevent drift in meaning of terms with time
Eg. Of questionnaire – pg 43
Analysis of results – pg 44 -46

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