CRFSFS : Comprehensive Reviews in Food Science and Food Safety

Flavor lexicons are a widely used tool for documenting and describing sensory perception of a selected food. Development of a representative flavor lexicon requires several steps, including appropriate product frame of reference collection, language generation, and designation of definitions and references before a final descriptor list can be determined. Once developed, flavor lexicons can be used to record and define product flavor, compare products, and determine storage stability, as well as interface with consumer liking and acceptability and chemical flavor data. Lexicon characteristics A flavor lexicon is simply a set of words to describe the flavor of a product or commodity. A lexicon is then applied or practiced using descriptive sensory analysis techniques. A lexicon, like a specific technical dictionary, provides a source list to describe a category of products, such as commodities (cheese, beef, fish) or finished products (bread, orange juice, coffee, chocolate). Although the descriptive panel generates its own list to describe the product array under study, a lexicon provides a source of possible terms with references and definitions for clarification (see ASTM lexicon comments). As a broad example, the ASTM Lexicon (Civille and Lyon 1996) provides hundreds of words that might be selected by a descriptive panel to describe any number of product categories. The clear admonition for use of the ASTM Lexicon and/or for generation of any lexicon is to: (1) collect a product frame of reference (2) generate the terms (3) review references and examples (4) develop a final descriptor list When a panel begins work in a product category, the 1st source of terminology is the wide sample set or frame of reference. The panel needs to evaluate several (25 to 100) products in the category that cover the widest array of flavor characteristics. The Aromatics, Tastes, and Feeling Factors that the samples manifest are the basis for the lexicon. After some initial attempts at organizing the terms generated by all of the panelists, the panel and panel leader organize references to provide clarification of the grouped terms. Often many terms relate to original ingredients and the processes they are subjected to in the creation of the category. Panelists need to experience these core ingredients (1) with and without process treatments and (2) in different ingredient combinations. After references, the panel goes back to the original list of terms to set the lexicon: merging like terms, eliminating redundant terms, and organizing the list in the order that the attributes appear in most products. This review will include lexicon history, methods, and applications. Descriptive Analysis Techniques The 1st published descriptive sensory technique is the Flavor Profile Method (FPM) developed in the 1950s by Arthur D. Little, Inc. (Pangborn 1989; Lawless and Heymann 1998; Meilgaard and others 1999). More recent applications emerged in the 1970s with Quantitative Descriptive Analysis (QDA) and the SpectrumTM method of descriptive analysis. The latter 2 techniques differ markedly from FPM in that they are designed to take measurements from individual panelists and then generate a panel average, rather than generation of a group consensus profile as with FPM (Piggott and others 1998). A detailed overview of all 3 techniques can be found in the Manual on Descriptive Analysis Testing for Sensory Evaluation (1992). Panelist selection is a critical aspect of descriptive analysis (Zook and Wessman 1977; Lawless and Heymann 1998; Meilgaard and others 1999). A good prospective flavor panelist should be able to describe sensations and should be able to discriminate between taste and aroma sensations. Typical screening tests include taste and aroma acuity and discriminatory ability. Good health, enthusiasm, and usage of the general product category are also characteristics of good prospective sensory panelists. All 3 techniques involve screening panelists for sensitivity to flavor and aroma and discriminatory ability followed by extensive training to generate a group of individuals who can function analogously to an instrument to evaluate flavor of products. In FPM, generally fewer panelists are used, with a minimum of 4 (Keane 1992). The panel leader is a member of the panel and works with the group to generate the language and the method for sample presentation and evaluation. Panelists are screened for sensory acuity, as well as for interest in sensory panel work. Following extensive training (approximately 60 h) panelists work as a group to generate a consensus profile of the sensory properties of the product and the intensity of each. In addition, overall amplitude of the product, as well as a measure of balance and blend are evaluated. The scale used for character (descriptor) notes is a 4 point scale (0-not present, 1-slight, 2-moderate, 3-strong) with half point designations in between, for a total of 7 points of discrimination. Attributes are evaluated in order of appearance. Aftertaste crfsfsv2ms20020013-AF-af.P65 1/27/2003, 4:03 PM 33 34 COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY—Vol. 2, 2003 CRFSFS: Comprehensive Reviews in Food Science and Food Safety may also be evaluated. The group consensus process was not designed for statistical analysis, although the scale may be modified to allow statistical analysis. In QDA, the panel leader is a sensory professional, rather than a member of the panel. During training, the panel (ideally 8 to 12 prescreened individuals) generates the language to describe the product (Stone 1992). The panel leader does not participate in the discussion to generate the flavor attributes, but facilitates the process. The panel also determines the order of appearance of the attributes and, thus, order of evaluation for each descriptor. Definitions for each descriptor are generated and additional products, which may further clarify terms, may also be used. The panel also practices rating products to become familiar with the process and to gain confidence in their abilities. Data is collected on scorecards using line scales anchored on each end. Panelists mark the scale using a dash. The marks are converted to numerical scores by measuring the responses on the scale with a ruler, digitizer, or computerized system. The data can be analyzed statistically and is traditionally graphically represented using a webplot. In the SpectrumTM method, a universal intensity scale is used (Munoz and Civille 1992; Meilgaard and others 1999). Panelists are screened for cognitive, descriptive and sensory discrimination ability, interest, and availability. The panel size is similar to QDA. By this method, panelists score intensities in the same manner across all attributes. The scales are anchored on either end and can be 15-cm line scales or, more commonly, 0 to 15 numerical scales with tenth subdivisions between, yielding 150 points. The scales and their intensities have already been established, and during training, panelists are given established examples to familiarize them with the use of the scale. Although the scale anchors end at 15, panelists can assign higher numbers if necessary. The panel leader, who should have previous experience with the SpectrumTM method, takes an active role in panel training, including scale usage and language development and application. The panel, with assistance of the panel leader, identifies the sensory language for the product, their order of appearance, and definitions for each term. While a universal intensity scale is standard for the SpectrumTM method, product specific scaling can also be applied . As with QDA, data is readily analyzed by statistical techniques. Results are normally graphically presented using histograms. Development of Flavor Lexicons Characteristics of flavor lexicons have been previously discussed by Civille and Lawless (1986) and by Lawless and Heymann (1998). One key characteristics of a good flavor lexicon is that it be discriminating and descriptive. Ideally, for a descriptive language to be discriminating (able to differentiate the products for which it was developed), the language should be developed from a broad representative sample set that exhibits all of the potential variability within the product (Meilgaard and others 1999). Defining what constitutes representative is often a challenge, particularly with foods or commodities which are diverse in flavor, source and treatment. Standard descriptive languages have been developed for commodities using representative sample sets (Janto and others 1998; Johnsen and Civille 1986; Johnsen 1986; Johnsen and others 1987; Heisserer and Chambers 1993). In an extreme example, Drake and others (2001b) collected 220 samples of Cheddar cheese varying in age, milk heat treatment, and geographical origin to identify a descriptive language for Cheddar cheese. The sample set was screened to 70 cheeses prior to language generation. Another key aspect of a flavor lexicon is for the terms to be nonredundant. That is, that multiple terms not be used to describe the same flavor or, alternatively, 1 term representing or overlapping with several other flavors. Redundancy may not be resolved during panel training. Panelists may insist that particular terms are distinct when they are not (Lawless and Heymann 1998). Statistical analysis of results from a representative selection of products is often required to clarify attribute relationships. Drake and others (2001b) reported that the use of the term “aged” in a Cheddar cheese flavor language was in fact a meta term that was comprised of 3 flavor terms and 1 basic taste. Flavor lexicon terms must also be descriptive with precise and clear meaning for consistent panel performance and for a platform from which research results can be repeated or compared in the future. Panelists may prefer to link descriptors together (for example burnt/charcoal, cooked milk/butterscotc