Time Intensity Analysis

Time Intensity Analysis

Purpose

Time Intensity tests are designed to measure the temporal evolution of a single attribute.

Results are plotted as time-intensity curves and key parameters of the curves are calculated. Results can be averaged per panellist or per product. 

Data Format

  1. Time_Intensity.xlsx
  2. The dataset should have a single attribute (Intensity) with datatype TDS.
  3. Each row in the dataset has a start and a stop time, the intensity is constant between start and stop times.

Background

Time - intensity (T-I) studies address the relationship between the onset, intensity, and duration of perception of a sensory attribute. In practice, the time and intensity are initially set at zero, subjects are exposed to a stimulus, and the perceived intensity is then recorded with the corresponding time coordinates until the intensity returns to zero again, or the allocated time for the assessment has ended. These relationships are commonly illustrated in the form of Time Intensity curves of perceived intensity versus time. [from Lui and MacFie paper]

The key parameters of the time-intensity curves are calculated in the analysis and are presented in the results.

The time-intensity curve can be divided into four distinct phases.  In practice a curve may not conform strictly to these phases:

  1. Reaction phase: before the first positive value of the perceived intensity is registered, this happens at T-start. This is the period required for the panellist to perceive and react to the stimulus.
  2. Ascending phase: the perceived intensity increases from zero to maximum. Time from T-start to T-max.
  3. Stationary phase: maximum intensity maintained for some interval. In some cases, this phase degenerates to a single point. Time from T-max to T-dec.
  4. Descending phase: from maximum intensity to end of perception. The perceived intensity decreases to zero. Time from T-dec to T-end.

When the curves are averaged, across the Panel or across Panellists, and the Standardize option is not selected, the raw curves are simply averaged - so the average curve is the average intensity taken at each time point.

Where the curves need to be averaged, and the Standardize option is selected, the method in the 1990 Liu and MacFie paper ‘Methods for averaging time-intensity curves’ are followed.

The standardization method works as follows:

  1. The average values of the parameters I-max (maximum intensity), T-start, T-max, T-dec and T-end, of all the individual scores to be averaged, are first calculated. The average values are arithmetic means.
  2. All curves are normalized in the intensity direction, to have the same level of maximum intensity. The values of I for each curve j are transformed to I’ = (I-max/I-max-j) * I
  3. Curves are normalized in the t direction to have the same T-start, T-max, T-dec and T-end as follows:
    1. T’ = ((T-max – T-start)/(T-max-j – T-start-j))*(T-T-start-j) + T-start when T-start-j <= T <= T-max-j
    2. T’ = (T-end – T-dec)/(T-end-j –T-dec-j)*(T-T-dec-j) + T-dec when T-dec-j <= T <= T-end-j
  4. To average the values of I, the ascending and descending phases of each curve are both divided into equal time intervals, in this case for each integer value of T. For each T, the unique corresponding I is calculated.

 If the Correction option is selected, then outliers and anomalies are recoded. And anomaly is defined as, for example, an increase during the decreasing phase. If an intensity point detected at time (t+1) named as It+1 is detected as larger than It and It+1 is larger than It+2 then It+1 is considered an outlier and is replaced by the average between It and It+2.

Options

  1. Results by: Should the curves by displayed by
    1. Panel - giving one curve per product.
    2. Panellist - giving one curve per panellist per product.
    3. Replicates - giving results for each replicate for each panellist and each product (i.e. no averaging)
  2. Correction: Where there is what the software assesses to be an anomaly in the curve e.g. a decrease during the increasing phase or vice versa, should the software correct this Yes/No.
  3. Standardize: Curves are averaged following the method in Lui and MacFie Yes/No.
  4. Number of decimals: Required number of decimals for values given in the results.

Results and Interpretation

Results are returned in two tabs.

TI curves (by Panel and by Panellist)

  1. A table of the intensity values per time point. This is returned for the by Panel and by Panellist options, and the tables are of the averaged values.  If standardize = Yes and / or Correction = Yes, the table contains standardized and / or corrected data. If by Replicates is selected and Correction = Yes, then the table of corrected intensity values per time point is returned in the export, but not displayed in the results.
  2. Plots of the TI values in the table are displayed if by Panel or by Panellist is selected. If by Replicates is selected individual curves are not returned.    

Results

  1. Max. Intensity:  Maximum intensity over the duration of the measurements.
  2. T (First Max): First time that the maximum intensity was reached.
  3. T (Last Max): Time that the maximum intensity ended.
  4. Max. Duration: Length of time that the intensity is at a maximum.
  5. Area (Total): The total area under the time intensity curve.
  6. Area (Max): The area under the time intensity curve for the portion of the curve when the intensity is at a maximum.
  7. Area (90% Max): The area under the time intensity curve for the portion of the curve when the intensity is at or above 90% of the maximum.
  8. T (First 50% Max): First time that 50% of the maximum intensity is reached.
  9. T (Last 50% Max): Last time that 50% of the maximum intensity is recorded.
  10. T Start (90% Max): First time that 90% of the maximum intensity is reached.
  11. T Stop (90% Max): Last time that 90% of the maximum intensity is recorded.
  12. Duration (90% Max): Length of time that the intensity is at or above 90% of the maximum.
  13. Asc. Start: Time the intensity curve starts to ascend.
  14. Asc. Stop: Time the intensity curve stops ascending (should be when the maximum is reached on a standard curve).
  15. Asc. Duration: Length of time that the intensity is increasing (difference between Asc. Stop and Asc. Start).
  16. Asc. Area: Area under the time intensity curve for the ascending portion of the curve.
  17. Asc. Slope: Slope of the ascending portion of the time intensity curve. This is calculated by fitting a linear model to the points in the ascending portion of the curve. If there are only 2 or fewer points in the ascending portion of the curve then the slope is not calculated (and NA is returned).
  18. Desc. Start: Time the intensity curve starts to descend.
  19. Desc. Stop: Time the intensity curve stops descending (should be the last time a non-zero intensity is recorded).
  20. Desc. Duration: Length of time that the intensity is decreasing (difference between Desc. Start and Desc. Stop).
  21. Desc. Area: Area under the time intensity curve for the descending portion of the curve.
  22. Desc. Slope: Slope of the descending portion of the time intensity curve. Calculated as for the ascending slope.

When the “By Replica” option is selected, users can also use the Results table to run ANOVA, for example, on the parameters. The Excel export file of the results table needs to be imported as a dataset in EyeOpenR to run an ANOVA. In order to make the table compatible with EyeOpenR Row 1 (with the table title) and Column A (with the row numbers) needs to be removed so that the Assessor column starts in cell A1.

Technical Information

  1. The time intensity code is written from scratch and does not use any R packages.

References

  1. Y.H. Liu and H.J.H MacFie, methods for averaging time-intensity curves. Chemical Senses, Vol 15, pp471-484, 1990.


    • Related Articles

    • Time Intensity (TI)

      Introduction A Time-Intensity (TI) method is a sensory evaluation technique used to assess the perceived intensity of a sensory attribute over a specific period, typically involving continuous measurements. Panelists are given a time-intensity ...

    • Penalty Analysis

      Purpose To provide a penalty analysis of a consumer data set, that is to investigate how liking or acceptability of product decreases when product attributes are not at the optimal intensity. Data Format Consumer.xlsx Note: for EyeOpenR to read your ...

    • Means over Time

      Available from version: 5.3.1 Purpose The means over time analysis is a helpful tool that can assist you in seeing how a product changes over time. This type of analysis is often useful for quality control, and it consists of a line chart where the ...

    • Principal Component Analysis (PCA)

      Purpose To provide a Principal Components Analysis (PCA) of the imported data. PCA is a popular dimensionality reduction method in sensory and consumer science. In non-technical terms, the analysis reduces an initial set of variables to a smaller set ...

    • Canonical Variates Analysis (CVA)

      Purpose To analyse sensory data using the multidimensional visualisation technique, Canonical Variates Analysis. Data Format Assessor by Product matrix measured on multiple attributes – there should be at least 3 attributes, and at least 3 products. ...