ASCENDING METHOD OF LIMITS

Test Method

A more involved method for flavor threshold determination involves a series of triangle sensory tests, see, for example, American Society of Brewing Chemists (ASBC) methods and the key references noted earlier for complete details (Lawless & Heymann, 2010; Lawless, 2013; Meilgaard, Civille & Carr, 2016 and Meilgaard, 1991). Such methods are based on the American Society for Testing and Materials (ASTM) and the International Organization for Standardization (ISO). This method also covers training on new compounds and gets the threshold value for an individual.

Here is a considered example: six (6) triangle tests — each with two reference beers (lager with no addition) and one test beer (e.g., isoamyl acetate) are set up for presentation to a team. For a test beer sample, the concentration of the ester was increased each time by a factor of 2 in each subsequent triangle set; triangle tested in increasing concentration of spike (e.g., 1, 2, 4, 8, 16, and 32 mg/L). In each triangle set the question is asked: Which sample differed from the others?

Results

The data are worked through similarly to that described above for the simpler method and although a bit more involved, simple programs can speed up the work. For example, in one study (see above) after training, the isoamyl acetate threshold in beer was shown to decrease (dropping from 7.8 to 3.9 ppm). This showed performance improvement for panelists as a whole and illuminated any need to recalibrate any individual palate. Distillers need to get up to speed with such methods and training, but be aware of the impact of high ethanol concentrations. Groups and organizations such as FlavorActiv, Aroxa (Cara Technologies), and the author of this article can assist here, but it is important to start looking at this type of training. An important note deals with the question of where to begin with the concentrations to use for such threshold testing. Threshold values are being increasingly reported upon in the literature and by suppliers of sensory stocks (FlavorActiv and Aroxa). See the article by Jeffrey & Spedding in Artisan Spirit issue 12 for some key values for starters. The American Society of Brewing Chemists member-accessible website has details of many component threshold values for beer, which also form a good base to launch from. A key starting point for whiskies is the early work of Lee et al., (2000). With an extensive list of many whiskey-related and other components provided by Miller (2019). A recent work by Barnes et al., (2022) is of current note.

PANEL FLAVOR THRESHOLD Example for DMS

With some repetition of the details from above, a simple example here will serve to illustrate the process and calculations. This example is from the spiking of beer samples with dimethyl sulfide (DMS). Some caveats to note: Most tests are run on beer/spirits where the concentration of the substance being tested is not actually known as it exists in the sample prior to the addition of the spiked test component. Thus, BET values are noted as concentrations (quantitative amounts) on top of that already present in the sample. Typically, a set of samples would be presented starting with a zero addition to the sample (a “control”), then Y ppm (or ppb) of the known/ test/training compound is added to the next glass, followed by successive doublings of the concentration (Example, 0, 12.5, 25, 50, 100, and 300 ppb) of the compound would be present in successive glasses. Such values are usually determined based on the known or estimated group BET as a central starting concentration. Here 50 ppb (anchor) is halved and halved again and doubled and doubled again. Noting here that the terminal value was set at 300 ppb, not 200 for this actual example — not a print error here. The assumption is that no one will selectively identify the component in the first non-zero (control) concentration sample glass (12.5 ppb) and certainly not in the control. Otherwise, the concentration that exists in the beer/spirit sample might need to be determined (as it is already at a detectable level, and that might reflect a naturally high presence in the base spirit). In that case, some thought on redesigning the experiment may be needed. Some people are eager to please — a natural bias — and want to “show off” a bit. For very low threshold detectable compounds (those with high volatility that vaporize quickly) we have found that biases occur based on smelling the compound in the air from the higher concentration glasses (diacetyl a prime example). The volatile is released into the surrounding air and sensory booths or stations as others perform the assessment. So, we suggest that closed bottles be provided with instructions for a group to open each bottle at the same time and then in successive order and assess the sample (by pouring a small amount into an acceptable sensory evaluation glass or cup). Then all participants are instructed to close their current test sample bottle (pour back the remaining sample from glass to bottle or have the glass covered and set aside or perhaps removed by the panel leader before moving to the next sample). Panelist stations should be well separated if possible, and testing performed under suitable taste panel room/environment conditions, see cited references for details on setting up full sensory programs, including the sensory chapter by Spedding and Aiken (2015 — second edition now in preparation) for details and many key references cited therein. After one spiked-level sample has been evaluated, move to the next higher-concentration spiked sample, and so on until all are assessed. No one must talk or emit noises or present any signs that might bias others during the exercise (See Scientific Thinking and Sensory Biases in AS issue 28, 2019.). Discussions can occur after all have completed the task. Anyone not positively identifying the component in any glass is eliminated from the set. Retrain them on the flavor note or decide if they are indeed taste blind to this component. A quick example with four panelists assessing a beer spiked with DMS shows the overall calculation here, Table 1. It is quite easy to set up a program to run the calculations on much larger sets of data. Data can be collected quickly, and the calculations done in a few minutes at quick instructional convention events/seminars, etc., with a calculator or computer at the ready, and honest replies from the audience!

TABLE 1. Panel Flavor Threshold Determination Quick Example

Final Summary

Panel Threshold = Log-1 (7.49/4) = 74.5 ppb DMS.

Column A is the concentration of the spike missed (no recognition), and Column B is the concentration where identification was made. The process is outlined nicely and succinctly in Figure 2.

Relevant literature is appearing with greater frequency to assist in establishing full sensory programs for distillers. Problems such as the one addressed at the beginning of this article can only be addressed by human sensory assessment, where trained panelists understand flavor descriptors and can assess relative concentrations of key flavor notes present within the complex matrix forming the complete flavor profile for a spirit. Machine-based sensory evaluation can only go so far in proving the acceptability of a product. A chemically “perfect” product can be rejected based on its actual taste/ flavor impression at the time of consumption. It is after all, humans, not machines, who consume their chosen favorite spirit brands. The flavor profile arises from (though is not in) the component matrix, but is generated in the mind of the beholder. How the molecules work together and stimulate the senses is all interpreted in the human brain!

FIGURE 2. A Summary of Flavor Thresholds and Their Estimation

It has been shown here that there are numerous ways in which threshold data can be obtained. Consult the cited works and publications such as the full-scale ASBC Methods Manual (latest edition) for full details of the more involved, though more reliable, methods such as Ascending Method of Limits Test, which uses the multiple triangular taste tests with increasing spike concentrations to get to threshold values.

An understanding of flavors, flavor descriptors, and how to assess relative concentrations of key flavor profile attributes including off flavors, will allow for better assessment and profiling of spirits and add to the quality control program for the modern distillery. In addition, it will enable better judging at spirit competitions. Distillers have much to learn from brewers and enologists in this regard.

All sensory stimuli have a level below which they cannot be detected even by the most sensitive person. The level at which a substance can just be detected in a media is called a Threshold Level. There are several types of threshold and two that are of importance to us here.

Detection Threshold: The lowest level of substance that can be sensed by a taster but not necessarily identified.

Recognition Threshold: The lowest level of a substance that can be sensed and positively identified by a tester.

To calculate the threshold levels the following formula applies:

The Best Estimate Threshold (BET) is calculated for each tester.

To do this the data obtained from each individual taster are evaluated. The BET is: the geometric mean of the highest concentration missed (in a series of spiked samples of increasing concentration — here “A”), and the next higher concentration (i.e. the concentration at which a Positive Identification was made — here “B”).

Geometric mean of A and B = SQUARE ROOT [SQRT] (A x B)

As an example, if a taster could not detect (identify) 100 ppb of a certain substance but could detect it at 200 ppb, their BET for that substance would be:

BET = SQRT(100 x 200) = SQRT(20,000) = 141 ppb

This is what can be figured out based on a taste session described in the text.

Group Threshold: The "maximum likelihood threshold" value for the substance for the goup as a whole (which is statistically more relevant than each BET) can be determined as follows:

1) The LOG10 (BET) values for all panelists in the tasting group are determined and then added together

2) The resulting sum is then divided by the number of panelists.

3) The antilog of the quotient from above is determined and this is the threshold level of that substance for the panel in the study.