Descriptive Panels

Descriptive sensory analysis is conducted using 8-12 panelists who are trained to detect and quantify appearance, flavor and texture attributes in dairy products. This type of evaluation can be very useful in identifying and tracking specific changes among samples. Data collected is statistically robust.

Qualitative descriptive profiling

Descriptive profiling involves generating a lexicon of attributes to fully describe a product. These attributes are used to produce a full sensory picture of the product which can be useful for marketing purposes or further testing (see quantitative descriptive analysis).

Table 1. Example lexicon from descriptive profiling.

ATTRIBUTE DEFINITION
Appearance
Color Hue of the product’s surface
Sheen Shiny-ness of the product surface
Free Moisture Amount of free water seen through packaging material
Surface Texture Visual roughness of the product surface
Body/Texture
Hand Firmness Amount of force required to compress product using thumb and forefinger
Cohesiveness Degree to which chewed mass holds together
Chewiness Total amount of energy needed to break up the sample
Particle Size Size of particles after set number of chews
Taste/Flavor/Aroma
Salt Taste elicited by sodium chloride
Acid Taste elicited by lactic acid
Bitter Taste elicited by caffeine
Sweet Taste elicited by sucrose
Buttery Flavor associated with butter or diacetyl
Milky Flavor associated with fresh whole milk (lactones)
Sour/Citrus Flavor associated with citric acid
Fruity Flavor associated with fruit, e.g. roasted pineapple

Quantitative descriptive analysis

The CDR Sensory Group utilizes both the Quantitative Descriptive Analysis (QDA®) and Spectrum® methods for quantifying appearance, body/texture, aroma and flavor. Our panels employ 15-point scales while evaluating product attributes; 0 = absent, 15 = extreme. Attributes can be chosen by the client, by the panel, or a combination of both. All collected data is statistically analyzed to highlight significant differences between products. This information can help you to better understand subtle differences in products. Please see below for examples of data collected from quantitative descriptive analysis panels.

Figure 1. Flavor descriptor comparison across four products evaluated.

(Note: all data shown here are fabricated for demonstrative purposes, we will never share client data with outside parties)

Table 2. Attribute means and pairwise analysis results. (α<0.05) Columns with different letters are statistically different.

ATTRIBUTE PRODUCT 1 PRODUCT 2 PRODUCT 3 PRODUCT 4
Salt 5.3b 4.3b 3.9ab 7.2c
Bitter 2.3a 1.4a 5.1b 2.3a
Sulfur 3.6b 3.4b 8.8c 1.9a
Acid 7.3b 6.5b 6.7b 5.5a
Buttery 5.7b 8.4d 2.3a 6.7c
Brothy 1.1b 0.5a 0.5a 4.1c

Changes during shelf-life

Quantitative descriptive analysis can be employed to monitor sensorial changes in a product over time. This can be useful for understanding changes during shelf-life and also aid in determining shelf-life end point. Products are evaluated at periodic intervals and target attributes are assessed.

Figure 2. Changes in bitter taste over 6 months (180 days). Errors bars show panel standard deviation. Asterisks above data points indicate statistically significant differences between products (α<0.05).