RECENT ADVANCES IN DENTAL CERAMICS RECENT ADVANCES IN DENTAL CERAMICS.
Recent Advances in Sensory Science - secure.compusense.com
Transcript of Recent Advances in Sensory Science - secure.compusense.com
Recent Advances in Sensory Science
Chris Findlay & John CasturaFebruary 23, 2016CIFST
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• Increased discrimination test power
• Temporal Check-All-That-Apply (TCATA)
• Individual Differences
Overview
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Increased discrimination test power
Neither the Triangle and Tetrad test methods required the nature of the difference to be stated, but the Tetrad test requires dramatically fewer assessors to achieve the same statistical power.
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Sensory Discrimination Testing
vs.
triangle
tetrad
Triangle test method
Select the odd sample.
Select the cookie that is different.
N total responses
x correct responses
p0 chance probability (1/3)
A
A Bδ
383 719 540
Select the cookie that is different.
Select the cookie that is different.
702 619 451
Tetrad test method
Group samples into 2 groups of 2
by similarity
Tetrad test method
Claim: provides better operational power than the triangle test.
N total responses
x correct responses
p0 chance probability (1/3)
383 719 540 266
Group samples into 2 groups of 2
by similarity.
Sample sizes (α=0.05; power=0.8)
Delta Tetrad Triangle
1.00 65 220
1.25 34 102
1.50 20 57
Ennis, J.M. & Jesionka, V. (2011). The Power of Sensory Discrimination Methods Revisited. Journal of Sensory Studies, 26, 371-382.
Temporal Check-All-That-Apply (TCATA)
TCATA summary
• Extends CATA to continuously track sensory properties.
• Builds on earlier non-intensity methods
(Flavor Profile, Time-Quality Tracking, Temporal
Dominance of Sensations, Temporal Order of
Sensations, …)
• Used with trained panelists or consumers
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:20
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:00
Timer starts when Startbutton is clicked
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:01
Check/uncheck attributes to describe the sample
…immediately
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:15
Check/uncheck attributes to describe the sample…
or after a waiting period (e.g. after swallowing)
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:01
Instructions related to evaluation protocol could be provided
Swallow the sample now…
TCATA question
Check and uncheck words to track changes in the orange juice. At each moment, the words that are checkedshould describe the orange juice (check all that apply, in that moment).
Astringent
Sourness
Sweetness
Off Flavor
Bitterness
Orange Flavor
0:45
Evaluation ends at a set time (determined by study objectives)
TCATA raw data
Eggy
Sweetness
Milk flavor
Hard
Icy
Soft
Time (seconds)
Natural Vanilla
Smooth texture
Artificial vanilla
Buttery
TCATA reference lines
Product trajectories
Refereed Publications
Ares, G., Jaeger, S. R., Antúnez, L., Vidal, L, Giménez, A., Coste, B., Picallo, A., & Castura, J. C. (2015). Comparison of TCATA and TDS for dynamic sensory characterization of food products, Food Research International, 78, 148-158. http://dx.doi.org/10.1016/j.foodres.2015.10.023
Boinbaser, L., Parente, M. E., Castura, J. C., & Ares, G. (2015). Dynamic sensory characterization of cosmetic creams during application using Temporal Check-All-That-Apply (TCATA) questions. Food Quality and Preference, http://dx.doi.org/10.1016/j.foodqual.2015.05.003
Castura, J. C., Antúnez, L., Giménez, A., & Ares, G. (2016). Temporal Check-all-that-apply (TCATA): A novel dynamic method for characterizing products. Food Quality and Preference, http://dx.doi.org/10.1016/j.foodqual.2015.06.017
Oliveira, D., Antúnez, L., Giménez, A., Castura, J. C., Deliza, R., & Ares, G. (2015). Sugar reduction in probiotic chocolate-flavored milk: Impact on dynamic sensory profile and liking. Food Research International, http://dx.doi.org/10.1016/j.foodres.2015.05.050
Selected Conference Presentations
Castura, J. C., Baker, A. K., & Ross, C. F. (2015). Characterizing wine finish using TCATA product contrails. In 1st Afrosense Conference. 23-26 November. Stellenbosch, South Africa. (Submitted abstract).
Castura, J. C., King, S. C., Li, Q., & Serrano, D. (2015). Using Temporal Check-All-That-Apply (TCATA) to understand the relationship among hedonic, emotion, and sensory attributes. In 11th Pangborn Sensory Science Symposium. 23-27 August. Gothenburg, Sweden. Scientific Poster Presentation. (Forthcoming).
Open access
Individual Differences
Is it possible to create products for individuals?
New Basic Tastes
Oleogustus and Kokumi
Understanding Genetic variation
Specific Anosmia
Super Tasters and Bitter Blindness
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What do we know ?
• There is no product that is “universally” liked, even water.
• Optimization of products is essential to achieve efficiency and market success
• To optimize, you must have a clear target.
• Unless you segment your consumers based upon their sensory preference you will not have a clear target.
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3.00 4.00 5.00 6.00 7.00 8.00 9.00
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
Cabernet Sauvignon Mean Liking
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3.00 4.00 5.00 6.00 7.00 8.00 9.00
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
3.00 4.00 5.00 6.00 7.00 8.00 9.00
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
3.00 4.00 5.00 6.00 7.00 8.00 9.00
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
3.00 4.00 5.00 6.00 7.00 8.00 9.00
W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
Cluster 1 – 28% Cluster 2 – 23%
Cluster 3 –32% Cluster 4 – 17%
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GPA of 16 Whole Grain Breads 55 Sensory Attributes
-1.10 1.10
-0.50
0.50
Variance Accounted for:DIM1 – 66%DIM2 – 9%DIM3 – 7%DIM4 – 4%
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3 4 5 6 7 8 9
Overall LikingAll 570 Category Consumers
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7.1
6.8
6.6
6.5
6.4
6.2
5.9
5.9
5.8
5.8
5.7
5.5
5.5
5.2
5.0
7.3
LOVE IT!
HATE IT!
2 3 4 5 6 7 8 9
Cluster 1 Overall Liking 25.8 % 147 Consumers
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7.4
6.7
6.7
6.6
6.5
6.1
5.8
6.0
4.9
5.6
4.9
4.4
4.5
4.4
3.2
7.8
LOVE IT!
HATE IT!
3 4 5 6 7 8 9
Cluster 2 Overall Liking 45.3 % 258 Consumers
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7.9
7.8
7.7
7.5
7.3
7.0
6.6
6.9
6.3
6.5
6.0
5.9
5.9
5.7
5.6
8.0
LOVE IT!
HATE IT!
3 4 5 6 7 8 9
Cluster 3 Overall Liking 28.9 %165 Consumers
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6.9
6.2
6.1
5.9
5.7
5.5
5.3
5.5
4.6
4.9
4.6
4.5
4.5
4.5
3.7
7.6
LOVE IT!
HATE IT!
• Consumer segmentation is essential to understand liking
• This applies to all consumers
• Even little ones
Understanding Consumers is important!
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PC
2
PC 1
Product Liking Clusters
X2
B1
G8
G1
G4X1
G2
Products that are found close together are in the same liking cluster
CLUSTER 1
CLUSTER 2
Strawberry Jam Consumer Liking Clusters
Chunksof
Fruit
Smooth and
Sweet
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Conclusions
• We must be aware of the increase in our understanding of perception and the methods for measuring the eating and drinking experience.
• Statistical tools allow the results we obtain to be interpreted with greater confidence.
• It’s probably impractical to tailor products for individuals
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Thank You