Table 3.
Classification of sensory temporal tests.
| Test | Type of Evaluation | Data Acquisition | Statistical Analysis | Advantages | Limitations | Variations | Ref. |
|---|---|---|---|---|---|---|---|
| TI 1 | Tracks the evolution of the intensity of sensory attributes over time | ANOVA 2; PCA 3 |
Quantification of the continuous perceptual changes that occur in a specific attribute over time | Time-consuming when used on several attributes | DTI 4; DATI 5; MATI 6 |
[19,143] | |
| TDS 7 | Records several sensory attributes consecutively over time, identifying one specific attribute as “dominant” | Compusense 8; EyeQuestion® 9; Fizz 10; TimeSens 11 |
PCA 3; ANOVA 4 |
Effective regarding temporal differences; Less time consuming; Simpler task foruntrained consumers |
Not so adapted to trained panels | TDL 12; TDE 13; HDTDSE 14 |
[144,145] |
| TCATA 15 | Assessors are asked to check all attributes that apply to the product in evaluation in addition to recording the evolution of sensory changes in products | Compusense at-hand 5.6 16 | Randomization Tests; Cochran’s Q Test; McNemar’s Test; binomial test |
Continuous selection and deselection of attributes based on applicability of the attribute to describe a sample |
More complicated for the consumer | [139,145,146] | |
| TL 17 | Collects scores and perceives variations of the acceptability of a product over time | TimeSens® | ANOVA 4; LSD 18 |
Easier performance in complex or hard-to-evaluate products The ability to evaluate how significant sensory differences are between samples |
Sensory fatigue; large assessor groups need to be used to increase confidence in the data; low statistical power |
TDE 13 | [124,147] |
| TDE 13 | Records several emotions consecutively over time, identifying one specific emotion as “dominant” | TimeSens 1.0 19; FaceReader™; An adapted version of EsSense Profile® |
ANOVA 4; AHC 20; MDA 21 |
Allows for the evaluation of food evoked emotions as motivators for food choices |
Risk of simulated emotions | HDTDSE 14; TDFE 22 |
[133,136,148] |
| HDTDSE 14 | Assessors hold down the attribute button when it is perceived as dominant and release it when it is no longer dominant | TimeSens 23 | ANOVA 4; CVA 24; MANOVA 25 |
Allows for subjects to report indecisive behavior | Does not overcome classic temporal dominance in terms of sensitivity and discrimination ability |
[137] | |
| FCAEF 26 | Assessors describe a product through free comment descriptions during periods, namely attack, evolution, and finish | TimeSens© 27; IRaMuTeQ© |
Bootstrap test; Fisher’s exact tests; Chi-square test; CA 28 |
Description of the temporal evolution with complete freedom of expression | Time-consuming, Redundancy, ambiguity, and requires an extension of terms |
[141] | |
| PC 29 | Assessors place samples on one of three curves | A statistical method developed by [146] | Quantifies three dimensions simultaneously | Requires a large number of assessors | [142] |
Legend: 1. Time-intensity; 2. analysis of variance; 3. principal component analysis; 4. discrete time-intensity; 5. dual attribute time-intensity; 6. multiple attribute time-intensity; 7. temporal dominance of sensations; 8. Compusense (Guelph, Ontario); 9. EyeQuestion® (Elst, the Netherlands); 10. Fizz (Biosystèmes, Couternon, France); 11. TimeSens (Tsi, SAS, Dijon, France); 12. temporal drivers of liking; 13. temporal dominance of emotions; 14. hold-down temporal dominance of sensations and emotions; 15. temporal check-all-that-apply; 16. Compusense at-hand 5.6 (Compusense Inc., Guelph, Ontario, Canada); 17. temporal liking; 18. least significant difference; 19. TimeSens 1.0 (INRAE Dijon, France); 20. agglomerative hierarchical cluster; 21. multidimensional alignment; 22. temporal dominance of facial emotions; 23. TimeSens (version 1.1.601.0, ChemoSens, Dijon, France); 24. canonical variate analysis; 25. multivariate analysis of variance; 26. free comment attack evolution finish; 27. TimeSens© software 2.0 (INRAE, Dijon, France); 28. correspondence analysis; 29. projective categorization.