A COMPARISON OF CATEGORY AND LINE SCALES UNDER VARIOUS EXPERIMENTAL PROTOCOLS

Analytic-holistic cognitive styles affect consumer responses to food and beverage samples during sensory evaluation

Recent studies have shown that the analytic-holistic theory is applicable in sensory science-related areas. Analytic and holistic cognitive style groups have been found to have significantly different perceptions and behaviors within food-related scenarios. These differences were further investigated and identified within the current study, focusing on specific areas of common sensory tests and analyses where analytic and holistic cognitive style groups may differ from one another. Before the main study, 419 volunteers were classified into three groups based on their scores to the Analysis-Holism Scale (AHS). The extreme groups (65 adults for each) were identified as the "analytic" and "holistic" cognitive style groups, respectively. Participants evaluated fruit-flavored beverages and fruit samples for their impression of the intensity or hedonic aspects in the study conducted over two sessions. Each session either employed solely category or line scale for the questions. Analyses focused on the analytic and holistic group comparisons in mean, variance, penalty analysis, and pre- and post-AHS score differences. Results showed that the holistic group exhibited significantly higher mean scores and standard deviations in the hedonic ratings of fruit samples than the analytic group did. Compared to the analytic group, the holistic group showed significantly smaller mean drops in overall liking across the five Just-About-Right (JAR) questions related to flavors or tastes of the mixed-fruit flavored water. A significant difference between the AHS scores measured before and after the sensory evaluation was observed in the holistic group, but not in the analytic group. In conclusion, our findings provide empirical evidence that cognitive styles affect consumer responses to food or beverage samples during sensory evaluation tasks. This implies that sensory professionals may consider these analytic-holistic contrasts while exploring consumer responses to their target samples.

Immune status, well-being and gut microbiota in military supplemented with synbiotic ice cream and submitted to field training: a randomised clinical trial

Strenuous physical activity, sleep deprivation and psychological stress are common features of military field training. The present study aimed to evaluate the effects of supplementation with a synbiotic ice cream on salivary IgA, gastrointestinal symptoms, well-being indicators and gut microbiota in young military participants undergoing field training. Sixty-five military completed the study: one group was supplemented for 30 d with synbiotic ice cream containing: 2·1 × 108 CFU/g for Lactobacillus acidophilus LA-5 and 2·7 × 109 CFU/g for Bifidobacterium animalis BB-12 and 2·3 g of inulin in the 60 g of ice cream at manufacture, and the other with a placebo ice cream. Volunteers were evaluated at pre-supplementation (baseline), post-supplementation and after a 5-d military training. Bifidobacterium and Lactobacillus genera were measured in stool samples and both showed a higher differential abundance post-supplementation and training. Salivary IgA and gastrointestinal symptoms decreased at post-training in both groups (P < 0·05; main effect of time); however, supplementation with synbiotic did not mitigate this effect. Tenseness and sleepiness were decreased in the synbiotic-treated group, but not in the placebo group at post-military training (P = 0·01 and 0·009, respectively; group × time effect). The other well-being indicators were not affected by the synbiotic supplementation. In conclusion, 30 d of synbiotic ice cream supplementation containing inulin, L. acidophilus LA-5 and B. animalis BB-12 favourably modulated gut microbiota and improved tenseness and sleepiness in healthy young military undergoing a 5-d field training. These improvements may be relevant to this population as they may influence the decision-making process in an environment of high physical and psychological stress.

Study of the influence of line scale length (9 and 15 cm) on the sensory evaluations of two descriptive methods

The line scale is widely used in different lengths to quantify the intensity of descriptors in sensory evaluation. Since studies related to its size are still limited the objective was to determine what variables of descriptive sensory evaluation can be influenced when different scale length is considered in two different methods: Optimized Descriptive Profile (ODP) (low degree of training) and Conventional Profile (CP) (high degree of training). Five chocolate samples were evaluated by two panels, one using the 9 cm and the other using the 15 cm line scale. The panels performed the sensory analysis using the ODP and after the CP method. The following criteria were investigated: interaction between sample and evaluator, discriminative capacity, repeatability of results, and frequency of score use on the unstructured scale. The influence of scale length on sensory responses was similar in the two methods (ODP and CP). When comparing the two scales in both methods, it was observed that the 15 cm scale resulted in an improvement in discriminative capacity, reduction of interaction and the evaluators tended to distribute their ratings more evenly across this scale length. The repeatability of results showed a slight tendency to be better on the 9 cm scale.

Unstructured numerical intensity scales: Models, protocols and errors

A sample of 62 untrained subjects were assessed on their ability to use unstructured numerical 9-point and 30-point category scales along with an unstructured line scale, using both rank-rating and serial monadic protocols. Visual stimuli were used for convenience, the task being to rate the heights of 12 easily discriminable columns of mung beans held in transparent vertical cylinders. Such stimuli had no perceptual variance, which would otherwise have added uncontrolled variance to the subjects' performance. Two measures of performance were used for each of the 6 experimental conditions. First, mean number of 'scaling errors' made in each of the six experimental conditions was computed. In this experiment, a scaling error was defined as giving a taller column a score equal to or less than a shorter column. The lower the error count, the better the subjects' performance. The second measure was to match the subjects' rating scale pattern of scores to a 'true' pattern of scores, derived from the physical measurements of the 12 columns. For this, a 'dissimilarity score' was developed. This compared the sum of the Euclidean distances between standardized true scale ratings for each of the column's 12 true heights, with those obtained from each subject. This gave a measure of the mismatch between the subject's set of scores and the true set of scores. Both the scaling error counts and the dissimilarity measures, indicated that subjects performed significantly better using the rank-rating protocol than the serial monadic. This was because of the effects of forgetting the exact intensities of stimuli once they had been removed, removal of stimuli being a necessary part of the serial monadic protocol. Subjects were penalized when using the 9-point scales, because there were too few categories to represent the different heights of all 12 columns. This introduced the concept of 'sufficient space'. Using the rank-rating protocol, the 30-point and line scales, with no memory problems and sufficient space elicited the best performances; they were not significantly different.

The 9-point hedonic scale: Using R-Index Preference Measurement to compute effect size and eliminate artifactual ties

214 consumers used the verbal 9-point hedonic scale to assess 4 types of flavor coated peanuts and 4 types of flavored teas. They used the traditional ANOVA/LSD analysis to provide mean values derived from the 9-point hedonic scale along with measures of significant difference. However, these data did not provide effect sizes. They did not give direct measures of the strength of preference between the various products, which was the main interest. Accordingly, effect sizes were computed. For this, each consumer had also ranked their preferences as they made their ratings on the 9-point hedonic scale. From these, R-Index values were computed to provide the percentages of consumers, who preferred each product to every other product. These direct measures of effect size completed the analysis begun by the ANOVA analysis of the set of mean scores. Also, the measures were nonparametric and avoided issues of the validity of a parametric statistical analysis. They also avoided the problem with the traditional analysis when products in the same scale category are attributed the same scores, when they are not equally liked. Experiment 2, using 207 consumers indicated that this problem was only serious enough to reduce the power of the traditional analysis, compared with the R-Index Preference Measurement, when the number of products being tested approached a dozen say, for product optimization.

The 9-point hedonic scale and hedonic ranking in food science: some reappraisals and alternatives

The 9-point hedonic scale has been used routinely in food science, the same way for 60 years. Now, with advances in technology, data from the scale are being used for more and more complex programs for statistical analysis and modeling. Accordingly, it is worth reconsidering the presentation protocols and the analyses associated with the scale, as well as some alternatives. How the brain generates numbers and the types of numbers it generates has relevance for the choice of measurement protocols. There are alternatives to the generally used serial monadic protocol, which can be more suitable. Traditionally, the 'words' on the 9-point hedonic scale are reassigned as 'numbers', while other '9-point hedonic scales' are purely numerical; the two are not interchangeable. Parametric statistical analysis of scaling data is examined critically and alternatives discussed. The potential of a promising alternative to scaling itself, simple ranking with a hedonic R-Index signal detection analysis, is explored in comparison with the 9-point hedonic scale.

Appetite control: methodological aspects of the evaluation of foods

This report describes a set of scientific procedures used to assess the impact of foods and food ingredients on the expression of appetite (psychological and behavioural). An overarching priority has been to enable potential evaluators of health claims about foods to identify justified claims and to exclude claims that are not supported by scientific evidence for the effect cited. This priority follows precisely from the principles set down in the PASSCLAIM report. The report allows the evaluation of the strength of health claims, about the effects of foods on appetite, which can be sustained on the basis of the commonly used scientific designs and experimental procedures. The report includes different designs for assessing effects on satiation as opposed to satiety, detailed coverage of the extent to which a change in hunger can stand alone as a measure of appetite control and an extensive discussion of the statistical procedures appropriate for handling data in this field of research. Because research in this area is continually evolving, new improved methodologies may emerge over time and will need to be incorporated into the framework. One main objective of the report has been to produce guidance on good practice in carrying out appetite research, and not to set down a series of commandments that must be followed.