Setting meaningful attribute targets for feedback training of descriptive panellists
Compusense FCM® (feedback calibration method) has been shown to be an effective tool to train descriptive analysis panels. The key to making this method work is providing “true” information, feedback, to panellists at the time they evaluate the attribute. This permits immediate calibration of the response. If the feedback is either trivial or incorrect, the panellist may be confused and the desired learning will not take place. To establish meaningful targets for feedback it is important to understand the shape of the psychometric function and the portion of the curve that describes the attribute intensity for the product being studied.
A specific attribute may be identified and defined in a range of the different products. The perception of the attribute will be dependent upon the product being tested. In simplest terms, the perceived sweetness of the same concentration of sucrose will be quite different in a citrus drink than in water. Both the just noticeable difference (JND) and the threshold values will be influenced by the components that make up any system. Sensory attributes can be assigned to several categories that can assist in applying the most appropriate strategy for both training and the collection of data.
The results from three large studies on wine will be used to illustrate the factors that influence the selection of both targets and ranges. The 76 to 130 attributes found in both red and white wines will be used to explain the feedback strategy for setting meaningful targets. By understanding the sensory dynamics of attributes, it is possible for sensory analysts and panel leaders to refine the process of training optimal panels.
Findlay, C.J., Phipps, K., & Castura, J.C. (2005). Setting meaningful attribute targets for feedback training of descriptive panellists. In: 6th Pangborn Sensory Science Symposium. August 7-11. Harrogate, Yorkshire, UK.