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  • Temporal Dominance of Sensations (TDS)

    Pascal Schlich

    INRA Centre des Sciences du Goût et de l’Alimentation

    [email protected]

    Professional Food Sensory Group A Sense of Change

    Campden BRI, Chipping Campden, UK. June 25, 2012

  • TDS A need for a method of time-profiling

    p. 2

    Attack? Evolution?

    Finish? The attack is sweet,

    then sweet is going down,

    and now there is a dominance of sourness and astringency

    Red Wine TDS curves

    0

    0,05

    0,1

    0,15

    0,2

    0,25

    0,3

    0,35

    0,4

    0,45

    0,5

    0 5 10 15 20 25 30 35 40 45time (s)

    dom

    inan

    ce ra

    te

    Significance

    Chance level

    Astring

    Sweet

    SourHeat

    Bitter?

  • TDS Rose-Marie Pangborn already asked for such a method in 1964 :

    p. 3

    “If an appropriate method could be developed, a modification of the so-called time-intensity study (Neilson, 1958) could be used to establish the temporal and sequential changes in apparent taste intensity of both compounds in a mixture.”

    Pangborn R. M.; Chrisp, R. B. (1964). Taste Interrelationships. Vi. Sucrose, Sodium Chloride, And Citric Acid In Canned Tomato Juice. Journal of Food Science, (29), 490

  • TDS Time-Intensity cannot do the job !

    • TI is difficult for panelist • One TI per attribute would be boring and time-consuming… • moreover, it would ignore attribute interactions • Indeed, results found with several attributes were questionable…

    Tmax

    Imax

    Imax : maximum intensity

    Bitter

    Not bitter

    Extremely bitter

    0 0

    Inte

    nsity

    Time (s)

    100

    0,9 x Imax

    Duration

    Time-Intensity curve

    4

  • TDS Where does TDS come from ?

    • Ep Köster, back in 1999 at CESG in Dijon, dreamed about an « harmonium of sensations »…

    • We try to build one, but ended up with TDS (project sponsored by Fromageries Bel and Danone)

    • Nicolas Pineau and I developed TDS curves and T, D and S parameters for statistical analysis at CESG in 2002

    • We introduced the TDS method at the 2003 Pangborn in Boston

    • Method used quite successfully with many companies on several types of products from 2003 to 2006

    • Rita Pessina defended in 2006 a Ph.D. (University of Foggia and Dijon) on the application of TDS to wine

    • After his Ph.D on panel performances (2006), Nicolas promoted the use of TDS within Nestlé

    • At last, we published a “TDS foundation paper” (Pineau et al., FQP, 2009)

    • Then at least 8 other papers were published using TDS or presenting new data analysis for TDS data

    Centre Européen des Sciences du Goût (CESG)

  • TDS Plan of the presentation

    1. TDS introduction (done)

    2. TDS definition and concept of “dominance”

    3. TDS validation in wine tasting

    4. TDS comparison to classical descriptive analysis and to TI

    5. TDS to better understand taste and flavour perception

    6. TDS to better identify sensory drivers of consumer liking

    7. TDS at the last Pangborn conference (Toronto, September 2011)

    8. TDS achievements and perspectives

    9. TDS references

    6

  • TDS

    Crunchy Dry

    Sticky Brittle Hard Gritty Crispy Light

    0 10

    How does TDS run ?

    STOP The subject puts the product into his mouth and clicks on "START"

    (t=0)

    Then, he chooses what attribute is dominant

    and scores its perceived intensity and so on…

    …until he clicks "STOP"

    START

    0

    START

    Time

    Attribute

    Score

    Crunchy

    3

    4.2

    Brittle

    8.5

    7.7

    Light

    9

    7.5

    Crispy

    11

    3.7

    Sticky

    13.5

    3

    15

    STOP Crispy

    5

    6

    Computer recording

    Instructions Computer screen

    7

  • TDS

    0 0.5

    1 1.5

    2 2.5

    3 3.5

    4 4.5

    5 5.5

    6 6.5

    7 7.5

    8 8.5

    9 9.5

    10 10.5

    11 11.5

    12 12.5

    13 13.5

    14 14.5

    15

    Brittle 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0Crispy 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 0 0Crunchy 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Dry 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Gritty 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Hard 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Light 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0Sticky 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0STOP 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

    0

    START Crunchy

    3 4.2

    Brittle

    8,5 7.7

    Light

    9 7.5

    Crispy

    11 3.7

    Sticky

    13.5 3

    15

    STOP Crispy

    5 6

    Time

    Attribute

    Score

    Dominance periods

    Definition of dominance periods and 0/1 data coding

    An attribute is considered as dominant from the time it is chosen until another one is picked For instance, Crunchy is dominant from 3 to 5 seconds, i.e. for a duration of 2 seconds

    0/1 data coding in an (attribute x time) matrix

    8

  • TDS

    Dominances for subj1 rep1 subj1 rep2 subj2 rep1 subj2 rep2

    subj3 rep1 subj3 rep2 subj4 rep1

    subj4 rep2

    " " " " " " " " " " " " " "

    Dom

    inan

    ce ra

    te

    Smoothed curves of the dominance rate over time Time (s)

    Superimposition of TDS curves of all attributes for a given product is the representation of the TDS

    profile of that product

    Summation of individual 0/1 data tables to draw smoothed TDS curves of proportions of dominances

    Focus on Crunchy

    9

  • TDS TDS curves are generally easy to read

    p. 10

    Red Wine TDS curves

    0

    0,05

    0,1

    0,15

    0,2

    0,25

    0,3

    0,35

    0,4

    0,45

    0,5

    0 5 10 15 20 25 30 35 40 45time (s)

    dom

    inan

    ce ra

    te

    Significance

    Chance level

    Astring

    Sweet

    SourHeat

    Bitter

    At 6 seconds, 39% of the subjects perceived sweet as

    the dominant sensation in this

    wine

    This wine is first sweet, than sour and finally dominated by a strong astringency and some bitterness

    The chance level is 1 divided by the number of attributes (probability of any attribute to be picked if none is dominant) The significance level is the lowest proportion being significantly (p=0.05) higher to the chance level in a binomial test

  • TDS

    Values of T, D and S parameters for Crispy in the TDS run below:

    Time = 5 seconds Duration = (8.5 – 5) + (13.5 – 11) = 6 seconds Score = (3.5 x 6 + 2.5 x 3.7) / 6 = 5.04

    11

    Definition of the T, D and S parameters

    Time = time of the first elicitation of an attribute Duration = total duration of a given attribute over all elicitations Score = average of intensity scores weighted by duration of each elicitation

    0

    START Crunchy

    3 4.2

    Brittle

    8.5 7.7

    Light

    9 7.5

    Crispy

    11 3.7

    Sticky

    13.5 3

    15

    STOP Crispy

    5 6

    Time

    Attribute

    Score

    • Regular statistical analysis (ANOVA, PCA …) can be run on D and S • Analysis of T is not so easy, but already covered by the TDS curves

  • TDS

    12

    Duration and Score can provide complementary information

    On this dairy product application, the duration of the elasticity sensation is highlighted by the first axis of the duration PCA, whereas the elasticity intensity did not discriminate the products

    Duration PCA dim1 = 37.71%, dim2 = 26.17%

    Score PCA dim1 = 53.22%, dim2 = 25.72%

    Axis1: Duration of elasticity Axis2: Duration of firmness and salty vs. Fluid

    Axis1: TDS score of firmness vs. fluid Axis2: TDS Score of soft taste vs. salty

    (Pineau, Cordelle, Schlich 2003)

  • TDS Concept of “Dominance”

    • Definitions in literature have been various: – The most intense (Labbe et al., 2008) – The rising sensation (Pineau et al., 2003; Pessina et al., 2005) – The new / popping up sensation (Pineau et al., 2009 ) – The sensation triggering your attention (Lenfant et al., 2009; Pineau et al. 2009) – Dominant as a stand alone definition (Le reverand et al., 2008; Meillon et al., 2009)

    • So what should I say to my panellist ? – The dominant attribute is the one which catch your attention at a given

    time. – It is likely to be the one which has a rising intensity allowing you to

    suddenly perceived it. – However, it does not mean that this attribute has to be very or the most

    intense in this product

    13

  • TDS Part 3. Validation of TDS in wine (Pessina’s Ph.D)

    • Experimental Merlot red wines each spiked towards one basic taste

    • Experimental Falanghina white wines each spiked towards one flavour

    • Descriptive, TI and TDS panels of 15 judges each

    • 10 training sessions per panel

    • Taste attributes: Sweet, Sour, Bitter, Astringent and Heat

    • Flavour attributes: Floral, White Fruits, Tripical Fruits, Dry Fruits, Honey and Woody

    • Taste and flavour TDS done separately, then conjointly

    14

  • TDS TDS gives the right information

    This base wine was manipulated to make wines in which one of the basic taste is increased

    15

  • TDS

    16 (Pessina et al., 2005)

    This base wine was manipulated to make wines in which one of the basic taste is increased

    TDS gives the right information

  • TDS

    This base white wine was manipulated to increase each flavor at a time

    TDS works quite well on flavor too

    17

  • TDS TDS works quite well on flavor too Floral wine

    Dried fruit wine Woody wine

    Fruity wine

    This base white wine was manipulated to increase each flavor at a time

  • TDS Simultaneous taste & flavor TDS seems possible

    Simultaneous taste & flavor TDS

    Taste TDS of the floral wine Flavor TDS of the floral wine

    19

  • TDS PART 4. Comparing TDS to descriptive analysis and to TI

    p. 20

    a. Comparison to descriptive analysis on Italian wines and on dairy products

    b. Comparison to TI on Italian wines and on dairy products

  • TDS

    The wine maps are alike, only a few differences on attribute interpretation

    Astring

    Bitter

    Heat

    Persist

    Sour

    Sweet

    AstringW

    BaseW

    BaseW1

    BaseW5

    BitterSW

    BitterW

    SourSW

    SweetSW

    Wine CVA from the Descriptive Panel

    HL=3.05 F=6.16 p=0.0001 NDIMSIG=3 - 80 % Confidence Ellipses of PRODUCT Means

    CAN

    2 19

    .52

    %

    -0.8

    -0.6

    -0.4

    -0.2

    0.0

    0.2

    0.4

    0.6

    0.8

    CAN1 68.81 %

    -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

    Sensory map from TDS scores Sensory map from conventional profiling done by another panel on the same wines

    AstrS

    BittS

    HeatS

    SourS

    SweeS

    AstringW

    BaseW BaseW1

    BaseW5

    BitterSW BitterW

    SourSW

    SweetSW

    Wine CVA of the SCORE Parameter from the TDS Panel

    HL=3.04 F=8.05 p=0.0001 NDIMSIG=2 - 80 % Confidence Ellipses of PRODUIT Means

    CA

    N2

    27.6

    3 %

    -0.8

    -0.6

    -0.4

    -0.2

    0.0

    0.2

    0.4

    0.6

    0.8

    1.0

    1.2

    CAN1 67.46 %

    -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

    Comparing Descriptive Analysis to TDS (1/2) Different panels

    (Pessina, Schlich, 2003) 21

  • TDS Comparing Descriptive Analysis to TDS (2/2) Same panel

    High similarity between these two maps

    12 dairy products x 10 attributes x 16 subjects x 4 replicates

    (Pineau, Cordelle, Schlich 2003) 22

    PCA from Descriptive data PCA of the Score TDS parameter

  • TDS Comparing Time-Intensity to TDS (1/3)

    Attributes differ by their slope and Imax but not by their Tmax

    A sequence of dominance is identified

    The sweet spiked experimental red wine TDS TI

    Sequence of sensations is detected by TDS, but not by TI (Pineau, Cordelle, Schlich 2003) 23

  • TDS Comparing Time-Intensity to TDS (2/3)

    5 dairy products x 10 attributes x 16 subjects x 3 replicates

    TDS TI

    Sequence of sensations is detected by TDS, but not by TI (Pineau, Cordelle, Schlich 2003) 24

  • TDS

    5 dairy products x 10 attributes x 16 subjects x 3 replicates

    TI TDS

    Higher intensity does not necessarily involve dominance

    Comparing Time-Intensity to TDS (3/3)

    (Pineau, Cordelle, Schlich 2003) 25

  • TDS PART 5. TDS to better understand taste and flavour perception

    p. 26

    a. TDS to understand perceived complexity in wines. Meillon’s Ph.D. (INRA-Pernod Ricard)

    b. TDS for investigating sweet and salt perception at Givaudan. Sophie Davodeau

    c. TDS at the Sensory Lab of the University of Florence. Erminio Monteleone

  • TDS

    • Five wines - Standard Syrah from Australia

    • Is a sensory difference perceptible between the wines ?

    Standard Syrah

    Wines dealcoholized by the Experimental Unit of Pech Rouge

    (INRA, France) 13.5 %

    Triad Vintage Nb correct ans./ Nb total ans. Pvalue α Témoin / T-2% Syrah 16/41 0.27 Témoin / T-4% Syrah 19/41 0.06 Témoin / T-5.5% Syrah 12/17 0.002 T-2% / T-4% Syrah 14/40 0.47

    -4 %

    Alcohol removal (reverse osmosis)

    - 2 %

    Syrah-5.5 Syrah - 2

    - 5.5 %

    Syrah - 4 11.5 % 9.5 % 8 %

    Sugar grape addition (8.44 g/l) 8 %

    Syrah-5.5 Cp

    Yes, for the comparison where the dealcoholization ratio is ≥ to – 4 %

    TDS to understand perceived complexity due to subtle differences in products (1/4) (Meillon et al., 2010)

    27

  • TDS

    Complexity score : 4.78

    Deacreases the perception of bitter, heat and berries sensations to the expense of astringency

    IMPACT OF ALCOHOL REDUCTION

    TDS to understand perceived complexity due to subtle differences in products (2/4)

    28

  • TDS

    Decreases the perception of astringency - Appearance of berries sensation but no appearance of heat and bitter sensations as in the standard

    IMPACT OF COMPLEMENTATION WITH SUGAR

    Complexity score : 4.78

    TDS to understand perceived complexity due to subtle differences in products (3/4)

    29

  • TDS

    Wines perceived as more complex by consumers displays a more complex temporal profile (higher number of perceived sensations, sensations blended and not distinct)

    LINK BETWEEN TDS AND COMPLEXITY

    Complexity score : 4.78

    TDS to understand perceived complexity due to subtle differences in products (4/4)

  • TDS PART 6. TDS to better understand consumer preferences

    p. 31

    A confidential application to sweet cereal snack

  • 32

    Chocolate snack: Brand A minus Brand B

    « Poor temporality »

    « Good temporality »

    Fruit snack: Brand A minus Brand B

    In a consumer test, Brand A was preferred to Brand B in chocolate, whereas it was the opposite in fruit. Plotting the difference between the TDS curves of A to B, one can suggest what can be a good and a poor temporality of sensations.

    « Good temporality »

    « Poor temporality »

    THUS, A GOOD SNACK SHOULD : « have a moderate crunchy start, soon relayed by the flavour, the sweet and the butter and must not last too long »

    AND SHOULD NOT : « start on a dry sensation, have a long-lasting pasty sensation with difficulty to masticate and to swallow and finally end on astringency »

    TDS as a tool for discovering temporal drivers of preference

  • TDS PART 7. Review of 4 TDS posters presented at the last Pangborn conference (Toronto, 2011)

    p. 33

    1. A method to monitor panel performances in TDS Nicolas Pineau

    2. Effect of level of training, number of attributes, intensity scales/buttons and definition of dominance on TDS responses Anne Saint-Eve

    3. TOS: a simplified TDS Suzanne Pecore

    4. Using TDS to evaluate wine-cheese combination Asgeir Nilsen

  • TDS ANOVA with TDS data to monitor panel performances

    p. 34

    Panel performance assessment for temporal dominance of sensations data N. Pineau*, T. Neville, M. Lepage, Nestlé Research Center, Switzerland

    ... … … … … … … … … …

    An appealing approach for a number of reasons: • 3 to 5 time periods are enough since panelists usually click no more often then 4-8 time in TDS

    • The product by time period (PT) interaction measures how much products differ in the temporal aspect of their perception

    • The performance table delivers clear diagnostics for almost every aspects of panel performances

    • Much more easy and faster to use than permutation tests…

  • TDS Level of training - Number of attributes - Scale/Button - Dominance definition. A. St Eve*, F. Lenfant, E. Teillet, N. Pineau, L. Souchon, N. Martin AgroParisTech, France & Nestlé Research Center, Switzerland

    p. 35

    CONCLUSIONS: 1.Discrimination increases

    with training, though untrained panel still discriminates

    2.If an important attribute is missing, panelists are disturbed

    3.Buttons are better that intensity scales (conclusion shared by most TDS users)

    4.“Triggers the most your attention” is the best definition of dominance

  • TDS Temporal Order of Sensations (TOS)

    p. 36

    Temporal order of sensations S.D. Pecore*, C. Rathjen-Nowak, T. Tamminen, General Mills, Inc, USA

    TOS data acquisition

    TOS data analysis by proportion of 1st hit

    In a test product (right plot), perception of spiciness is delayed from spoon 1 to spoon 2, compared to the current product (left plot)

    Panelists record which attribute hits first, then which one hits 2nd and finally which one hits 3rd for three spoonfuls. Single aftertaste also captured after 4th spoonful (not shown)

    TOS is a TDS with 0/1 scale, limited to 3 dominances and with no record of time between 2 consecutive hits. Surely TOS is simpler to do than TDS because subjects do not need to consider timing nor intensity. Thus the essential idea of rating a succession of spoons can be implemented more easily than in TDS or TI.

  • TDS Evaluation of combinations of wine and cheese using TDS A. Nilsen*, M. Billing & A. Oström (Orebro University, Sweeden)

    p. 37

    SWEET

    FRUIT FL.

    SALTY DAIRY FL.

    ACIDITY

    SWEET FRUIT FL.

    SWEET

    Sauternes +

    Roquefort Roquefort Sauternes

    TDS along a full meal… why not, using a PC-tablet or a mobile phone !

  • TDS

    ACHIEVMENTS • TDS answers to the need of a multivariate temporal tool • TDS helps to understand food perception, but also consumer liking • Most sensory softwares now include TDS • TDS entered the sensory toolbox of several major companies • Tools are now available to monitor panel performances in TDS

    PERSPECTIVES • To benchmark panel performances in TDS using databases (as the one

    developed by INRA and Nestlé) • To apply TDS or simplified TDS (as TOS) with consumers • To use TDS in natural eating contexts (several bites, food combinations,

    meals, snacking …) • To use TDS out of the lab on mobile phones, PC-tablets (TimeSens project) • To develop new sensometrics for TDS data analysis (TimeSens project)

    PART 8. TDS achievements and perspectives

    38

  • TDS

    39

    PART 9. TDS References

    PUBLICATIONS • Pessina, R. (2006). Dominanza temporale delle sensazioni gustative ed aromatiche del vino. Ph.D Thesis defended

    on July 11, 2006 at the University of Foggia, Italy. • Le Reverend, F. M., Hidrio, C., Fernandes, A., & Aubry, V. (2008). Comparison between temporal dominance of

    sensations and time intensity results. Food Quality and Pref., 19, 174-178. • Labbe D., Schlich P., Pineau N., Gilbert F., Martin N. (2008). Temporal Dominance of Sensations and Sensory

    Profiling: A Comparative Study. Food Quality and Pref., 20, 216-221. • Pineau N., Schlich P., Cordelle S., Mathonnière C., Issanchou S., Imbert A., Rogeaux M., Etiévant P., Köster E.

    (2009). Temporal Dominance of Sensations: Construction of the TDS curves and comparison with time–intensity. Food Quality and Pref., 20, 450-455

    • Meillon S., Urbano C., Schlich P. (2009). Contribution of the Temporal Dominance of Sensations method to the sensory description of subtle differences in partially dealcoholized red wines. Food Quality and Pref., 20, 490-499.

    • Lenfant F., Loret C., Pineau N., Hartmann C., Martin N. (2009). Perception of oral food breakdown. The concept of sensory trajectory. Appetite, 52, 659-667.

    • Meillon, S. (2009). Impact de la réduction d’alcool sur la perception sensorielle des vins et acceptabilité par les consommateurs. Ph.D Thesis defended on December 18, 2009 at the University of Burgundy, Dijon, France.

    • Meillon S, Viala D, Medel M, Urbano C, Guillot G, Schlich P (2010). Impact of partial alcohol reduction in wine on perceived complexity and temporality of sensations and link with preference. Food Qual Prefer 21, 732-740

    • Meyners M., Pineau N. (2010). Statistical inference for Temporal Dominance of Sensations data. Using Randomization Tests. Food Quality and Pref., 21, 805-814

    • Meyners M. (2011). Panel and panelist agreement for product comparisons in studies of Temporal Dominance of Sensations Original. Food Quality and Preference, 22, 365-370.

    • Saint-Eve A., Déléris I., Panouillé M., Dakowski F., Cordelle S., Schlich P., Souchon I.. (2011). How texture influences aroma and taste perception over time in candies. Accepted in Journal of Chemosensory Perception

  • TDS Thanks are due to a lot of people:

    • The members of the original TDS project: Ep Köster, Patrick Etiévant, Christelle Mathonière, Annie Imbert (Fromageries Bel), Michel Rogeaux (Danone) & Sylvie Issanchou

    • My former Ph.D. students: Nicolas Pineau, Rita Pessina and Sophie Meillon

    • TDS users and developers who kindly shared their work with me: Erminio Monteleone, Sophie Davodeau, Suzanne Pecore, Anne St Eve, Morten Paulsen & Asgeir Nilsen

    • The numerous companies for which we applied TDS and thanks to which we learned how to improve it

    • The TimeSens team in Dijon: Michel Visalli, Guillaume Duployer & Carole Monterymard

    p. 40

    Temporal Dominance of Sensations�(TDS)�A need for a method of time-profilingRose-Marie Pangborn already asked for such a method in 1964 :Time-Intensity cannot do the job !Where does TDS come from ?Plan of the presentationHow does TDS run ?Definition of dominance periods and 0/1 data codingSummation of individual 0/1 data tables to draw smoothed TDS curves of proportions of dominancesTDS curves are generally easy to readDefinition of the T, D and S parametersDuration and Score can provide complementary informationConcept of “Dominance” Part 3. Validation of TDS in wine (Pessina’s Ph.D)TDS gives the right informationTDS gives the right informationTDS works quite well on flavor tooTDS works quite well on flavor tooDiapositive numéro 19PART 4. Comparing TDS to descriptive analysis and to TIComparing Descriptive Analysis to TDS (1/2)�Different panelsComparing Descriptive Analysis to TDS (2/2)�Same panelComparing Time-Intensity to TDS (1/3)Comparing Time-Intensity to TDS (2/3)Comparing Time-Intensity to TDS (3/3)PART 5. TDS to better understand taste and flavour perceptionTDS to understand perceived complexity due to subtle differences in products (1/4) (Meillon et al., 2010)TDS to understand perceived complexity due to subtle differences in products (2/4)TDS to understand perceived complexity due to subtle differences in products (3/4)TDS to understand perceived complexity due to subtle differences in products (4/4)PART 6. TDS to better understand consumer preferencesDiapositive numéro 32PART 7. Review of 4 TDS posters presented at the last Pangborn conference (Toronto, 2011)ANOVA with TDS data to monitor panel performances Level of training - Number of attributes - Scale/Button - Dominance definition. A. St Eve*, F. Lenfant, E. Teillet, N. Pineau, L. Souchon, N. Martin AgroParisTech, France & Nestlé Research Center, SwitzerlandTemporal Order of Sensations (TOS)Evaluation of combinations of wine and cheese using TDS�A. Nilsen*, M. Billing & A. Oström (Orebro University, Sweeden)PART 8. TDS achievements and perspectivesPART 9. TDS ReferencesThanks are due to a lot of people: