Sensory panel

The sweetness of fmctose is 1.3—1.8 times that of sucrose (10). This property makes fmctose attractive as an alternative for sucrose and other commercially available sweeteners. Fmctose is probably sweetest ia comparison with sucrose when cold and freshly made up ia low concentrations at a slightly acidic pH (5). This relative sweetness difference is commonly attributed to changes ia fmctose stmcture when cold ( P-D-fmctopyranose(l), sweet) as compared to the stmcture when the sweetener is warm ( P-D-fmctofuranose (2), less sweet). Based on nmr spectroscopy and sensory panel evaluation of sweetness, however, it has been observed that the absolute sweetness of fmctose is the same at 5°C as at 50°C, and is not dependent on anomeric distribution (11). Rather, it maybe the sweetness of sucrose, which changes with temperature, that gives fmctose sweetness the appearance of becoming sweeter at low temperatures. 

Following previous works on physico-chemical characterisation of sunflower low-methoxyl pectins (Alarc o-Silva, 1990, Leitao at al., 1995) and technological utilisation in the manufacture of low calorie gels (Alarc o-Silva et al., 1992), this investigation was carried out to test the suitability of that pectin to the confection of grape juice reduced calorie jellies in comparison with two types of commercial pectin. Aiming at the optimisation of low-calorie jelly formula, based on consumers preferences, the jellies were submitted to a sensory panel test judgement and instrumental texture-analysis. 

The jellies (20 sets) were submitted to a sensory panel (ten panellists from the laboratory staff with some experience in sensory evaluation) requested to give a score (from low to high in a non-structured 10 cm scale) to each of the following characteristics aroma (intensity), taste (sweet, acid and intensity), texture (hardness, spreadability) and overall acceptance. 

As an example consider the data presented in Tables 35.1-35.4. These tables are extracted from a much larger data base obtained in an international cooperative study on the sensory aspects of olive oils [1]. Table 35.1 gives the mean scores for 16 samples of olive oil with respect to six appearance attributes given by a Dutch sensory panel. Table 35.2 gives similar scores for the same samples as judged by a... 

Olive oils mean scores for appearance attributes from Dutch sensory panel... 

Fig. 35.3. Scatter plot of 16 olive oils scored by two sensory panels (Dutch panel lower case British panel upper case). The combined data are shown after Procrustes matching and projection onto the principal plane of the average configuration.

When many data sets for the same set of products (objects) are available it is of interest to look for the common information and to analyze the individual deviations. When the panellists in a sensory panel test a set of food products one might be interested in the answer to many questions. How are the products positioned, on the average, in sensory space Are there regions which are not well... 

S. de Jong, J. Heidema and H.C.M. van der Knaap, Generalized Procrustes analysis of coffee brands tested by five European sensory panels. Food Qual. Pref., 9 (1998) 111-114. 

Fig. 16.5 Correlation between the technical quality index and sensory score (overall judgement) in blind sensory panel tests.

In the study by Thompson, et al. (11), the ml of gel released per 100 g emulsion for the reference emuTsion without soy, with soy isolate (SIF), soy concentrate (SCF) or soy flour (SF) was 6.07, 5.83, 5.49 and 3.08, respectively, when the hydration ratios were 1 4 (flourrwater) for SIF, 1 3 for SCF and 1 2 for SF. The ml gel released per 100 g emulsion containing 10, 15, 20, and 25% soy protein was 6.70, 5.01, 3.94 and 3.57, respectively. When soy protein concentrate was incorporated into an emulsion at the 3.5% level, the processing yields, textural profile and sensory textural attributes of frankfurters were not different among the products with and without added soy concentrate (13). An objective measure of compression and shear modulus indicated that soy protein concentrate incorporated into frankfurters at the 3.5% level had no effect on batter strength or texture ( M). The addition of a cottonseed protein to frankfurters to replace 5, 10 or 15% of the meat resulted in higher pH, less cured color, less firmness of skin, softer texture and reduced desirability as judged by a sensory panel (J5J. 

When structured soy protein fiber was added to fermented salami at 15 or 30% levels, trained sensory panels found the flavor to be undesirable, whereas a 116-member untrained panel found the product containing 30% soy flour to be undesirable in flavor, tenderness and overall desirability (26). The flavor of beef patties containing 20% soy protein flour or concentrate was rated about equal to all beef patties by a 52-member panel, whereas patties containing 30% were scored lower by the panel (6). Berry et al. (7) found the characteristic "soy-like" flavor to be more... 

It is often too expensive to have or maintain an inhouse descriptive sensory panel. Therefore, other ways of measuring flavor need to be developed. Off-flavor in many foods have been measured by using gas chromatography to assess the level of lipid volatiles associated with off-flavor development Chapters 5, 6, 9) such as hexanal or by direct chemical determination of thiobarbituric acid reactive substances Chapters 5, 6) as a marker of the degree of lipid peroxidation. A new method being tested for use in the assessment of food qu ity is impedance technology. This method is showing promise for use in the seafood industry Chapter 20),... 

Two kinds of mixed solutions were provided to test the hypothesis. One was a mixed solution of D-phenylalanine and L-phenylalanine. The second was a mixed solution of sucrose and L-phenylalanine. While the chemical properties of d- and l-phenylalanine are the same, for the most part, they do possess different tastes. Sucrose has a structure and taste that is significantly different from L-phenylalanine. The sensory data obtained from a five member sensory panel is shown in Table ni. 

The author thanks Dr. B. T. Vinyard for statistical evaluations, Mr. C. James, Jr. and Mrs. C. H. Vinnett for technical assistance, members of the meat sensory panel for evaluation of samples and employees of the sensory laboratory for assistance in preparing and serving the samples. 

With the molecular descriptors as the X-block, and the senso scores for sweet as the Y-block, PLS was used to calculate a predictive model using the Unscrambler program version 3.1 (CAMO A/S, Jarleveien 4, N-7041 Trondheim, Norway). When the full set of 17 phenols was us, optimal prediction of sweet odour was shown with 1 factor. Loadings of variables and scores of compounds on the first two factors are shown in Fig es 1 and 2 respectively. Figure 3 shows predicted sweet odour score plotted against that provid by the sensory panel. Vanillin, with a sensory score of 3.3, was an obvious outlier in this set, and so the model was recalculated without it. Again 1 factor was r uired for optimal prediction, shown in Figure 4. 

Definition of taste and aroma character in sensory terms, and assigning this to precise variation in fruit composition, allows experiments with sensory panels to be limited to defining compositional componoits correlated with character changes perceived important by observers. Subsequent experimentation can then be effected by automated chromatography. 

Buet, D., Burgaud, H., Rossi, P. (1996) Electronic nose a real interface between sensory panels and fine analytical procedures in cosmetics. In Olfaction and Electronic Nose, 3rd International Symposium, Toulouse. 

In the case of pineapples, the 12 odorants listed in Table 16.7 were dissolved in water in concentrations equal to those determined in the fruit [50]. Then the odour profile of this aroma model was evaluated by a sensory panel in comparison to fresh pineapple juice. The result was a high agreement in the two odour profiles. Fresh, fruity and pineapple-like odour notes scored almost the same intensities in the model as in the juice. Only the sweet aroma note was more intense in the model than in the original sample [50]. In further experiments, the contributions of the six odorants showing the highest OAV (Table 16.7) were evaluated by means of omission tests [9]. The results presented in Table 16.8 show that the omission of 4-hydroxy-2,5-dimethyl-3(2H)-furanone, ethyl 2-methylbutanoate or ethyl 2-methylpropanoate changed the odour so clearly that more than half of the assessors were able to perceive an odour difference between the reduced and the complete aroma model. Therefore, it was concluded that these compounds are the character-impact odorants of fresh pineapple juice. 

Evaluating Synthetic Sweeteners. Evaluation of new sweeteners, unlike that of most functional food ingredients, is not possible using totally objective means, There arc no general rules leading to structurc/function relationships for all classes of sweeteners. The principal judgments must rely on human sensory panel tests. The training and administration of sensory panels for sweeteners are beyond the scope of this volume. 

Figure B5.3.4 A comparison between moisture retention for a raw sample and the binding as measured by a sensory panel for fish muscle treated with different cations. Reprinted from Regenstein (1984) with permission from the American Meat Science Association and Zwika Weinberg (Volcani Center, Agricultural Research Organization, Israel).

Expressible moisture and water uptake ability measure different properties. Figure B5.3.2 shows the very different cation and anion dependencies of these methods using fish samples. Figure B5.3.3 shows that the pH profiles are also different. It is also apparent that WUA is often >100%, while expressible moisture must, of necessity, be <100%. Figure B5.3.4 shows an example where expressible moisture was actually correlated with a separate and independent functional measurement. In this case, the binding of cooked fish muscle as determined by a subjective sensory panel pulling samples of fish apparently paralleled the moisture retention of the raw fish (moisture retention = 1 - expressible moisture). Ideally, functional properties should show such correlations with other properties of interest in food systems. 

Use a trained sensory panel to collect data when separation factors approach 1.0. The odor data can then be analyzed using statistical methods. 

Taste of amino acids was studied using the taste sensor [23]. Taste of amino acids has had the large attention so far because each of them elicits complicated mixed taste itself, e.g., L-valine produces sweet and bitter tastes at the same time. Thus, there exist detailed data on taste intensity and taste quality of various amino acids by sensory panel tests [26]. The response of the sensor to amino acids was compared with the results of the panel tests, and response potentials from the eight membranes were transformed into five basic tastes by multiple linear regression. This expression of five basic tastes reproduced human taste sensation very well. 

Shaw, P. E. Ahmed, E. M. Dennison, R. A. Orange juice flavor contribution of certain volatile components as evaluated by sensory panels. Proc. Int. Soc. Citriculture, 1977, 2, 804-807. 

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