Perception of mealiness in apples: a comparison of consumers and trained assessors

  The Repertory Grid method was used to aid consumers in developing a vocabulary to describe the sensory characteristics perceived from samples of three varieties of apples (Cox, Jonagold and Boskoop) from three different harvest dates each (early, middle, and late harvest). The aims of this work were to study whether consumers perceived different degrees of mealiness and to compare the perceptual spaces of samples obtained from consumer data and from conventional profiling with a trained panel, using Generalized Procrustes analysis. The relative positions of samples were similar for the consumers and the trained assessors' consensus spaces but the latter resulted in a better separation of samples. Boskoop samples were perceived as more acid, astringent, crispy and hard while the Cox variety was described as sweeter and more floury. Jonagold samples were perceived as juicier and occupied an intermediate position, with the mealy Jonagold sample closer to the Cox samples. The agreement between sample spaces showed that both panels perceived the major differences between samples in a similar way but the trained panel was able to differentiate further, mainly between the texture characteristics. Received: 8 January 1998 / Revised version: 18 March 1998     

Proficiency testing for sensory ranking panels: measuring panel performance

Proficiency testing in sensory analysis is an important step towards demonstrating that results from one sensory panel are consistent with the results of other sensory panels. The uniqueness of sensory analysis poses some specific problems for measuring the proficiency of the human instrument (panel). As part of an EU supported project, ProfiSens, 14 panels undertook ranking of sweetness on five samples of apple juice. Four panels were designated ‘validation’ panels, whose data were used firstly to establish the expected ranking results, and secondly to set the performance criteria that a trained sensory panel would be expected to achieve. Four key measures of a panel’s performance were investigated: the ability to rank the samples in the correct order; the significance level associated with differences between samples; the number of pairs of samples that a panel found to be different at a specified level of significance; and the degree of agreement between assessors within a panel. For each of these criteria an ‘expected result’ was considered, as well as an overall measure of performance. The data from the remaining panels were analysed, and the level of performance was recorded for each of the stated criteria. Results indicated different levels of performance, and the research also revealed the importance of choice of validation panels and the screening of samples prior to testing. A simpler performance scheme was proposed to address issues relating to attaching arbitrary weightings to each of the performance criteria, and to address potential problems associated with combining different measurement criteria into a single performance score. While there is still potential for further development and refinement, ProfiSens has made a significant contribution to proficiency testing for sensory analysis.     

Consumer Evaluation of the Sensory Properties of Fish

A set of 13 sensory attributes for describing cooked fish were identified using data from written surveys and consumer tests. These attributes were applied to the evaluation of 18 common Atlantic species by consumers. The data showed high positive correlations with data previously reported for trained profile panels. The best correlations occurred for the most salient attributes, and cluster analysis for the two sets of data showed the greatest similarity for species possessing these salient attributes. However, regression analysis snowed that trained profile panelists used a wider range of the intensity scale than did consumers. Corresponding data from a written survey of “experts” correlated poorly with both trained and consumer panel data.     

How reliable are the consumers? Comparison of sensory profiles from consumers and experts

This study compares expert and consumer sensory profiles for the same 12 perfumes in different ways: the discriminatory ability and reproducibility are analyzed through ANOVA and the panelists’ consensus through the correlation coefficients. Next, the two product spaces are first analyzed separately for each panel, and then compared through multiple factor analysis. Finally, the two panels are compared using the confidence ellipses methodology. These analyses show that the two panels give similar results with respect to the important criteria for panels (discrimination, consensus, reproducibility). The comparison of the two products spaces shows high similarity. From the confidence ellipses, it can be concluded that no significant differences exist for a given product between the two panels. Hence, in this particular case, the use of consumers appears to be a good alternative to the classical sensory profile provided by a trained panel.     

Application of selected neuroscientific methods in consumer sensory analysis: A review

Neuromarketing or consumer neuroscience is a relatively new market research subdiscipline that has gained popularity among consumer behavior scientists in the past two decades or so. It combines neurobiology with behavioral psychology to understand consumer behavior, more specifically about their decisions related to choices/preferences and purchase. The purpose of this review is to explore the potential of using neuroscientific methods for consumer sensory science research. By no means, this is an exhaustive review hindered by the fact that there are countless articles on neuromarketing and consumer neuroscience in the literature. The author has tried to show the applicability of neuroscientific methods in consumer sensory sciences, specifically electroencephalography and eye tracking, which could potentially “complement” the sensory methodologies to gain better consumer insight. Both these techniques are relatively inexpensive, portable, and minimally invasive techniques that are already being used by some sensory scientists. They could be incorporated with ease in the research portfolio of consumer sensory researchers who would like to use them to study consumer affect. It is recommended that the researchers use proper experimental design that takes into consideration the confounding variables as much as possible. The two methods mentioned before have been proven to be relatively reliable and repeatable. Lastly, these methods would also require ethical oversight because of the involvement of human subjects.     

Assessment of commercial lamb meat quality by British and Spanish taste panels

Trained sensory panels in Britain and Spain assessed loin meat from commercial lambs purchased in Spain, which included Welsh lamb (imported from Britain) and two Spanish breeds (Merino and Rasa Aragonesa). The British panel also assessed British lamb purchased in local butcher shops and supermarkets. Sensory panels, in each country, received meat from the same lambs and used their local methods of cooking and assessment. Spanish panels used unstructured line scales to measure lamb odour intensity, tenderness, juiciness, lamb flavour intensity and two hedonic scales of flavour liking and overall liking. The British panel used 8 point category scales with the same attributes. Results from both panels in objective parameters were in agreement, hence showing that different trained sensory panels may arrive at the same conclusion. However, when panellists were allowed to make hedonic judgements (preference), the British panel preferred British lamb and the Spanish panel preferred Spanish lamb. This finding has important consequences for lamb producers who export their lambs and demonstrates that the underlying reasons for different preferences should be investigated. Production variables are discussed in relation to their influence on lamb eating quality and as a way to tailor lamb eating quality attributes familiar to consumers in the importing country.     

Interlaboratory evaluation of dry-cured hams (from France and Spain) by assessors from two different nationalities

Two panels of assessors from France and Spain assessed 41 dry-cured hams from diverse geographical origins, pig breedings and feedings. Univariate (Kolmogorov-Smirnov test and t-test) and multivariate (canonical correlation and principal component analysis) statistical procedures have been used to explain the agreement and disagreement between panels evaluating similar and dissimilar sensory attributes quantified with a 9-points structure scale. The results pointed out that there were basic agreements between panels, although some disagreements were detected in mould, acorn and crust attributes. The classification of Iberian and white dry-cured hams and the sensory attributes that characterise them are also displayed.     

Development of a Time–Intensity Evaluation System for Consumers: Measuring Bitterness and Retronasal Aroma of Coffee Beverages in 106 Untrained Panelists

In order to develop products that are acceptable to consumers, it is necessary to incorporate consumers’ intentions into products’ characteristics. Therefore, investigation of consumers’ perceptions of the taste or smell of common beverages provides information that should be useful in predicting market responses. In this study, we sought to develop a time–intensity evaluation system for consumer panels. Using our system, we performed time–intensity evaluation of flavor attributes (bitterness and retronasal aroma) that consumers perceived after swallowing a coffee beverage. Additionally, we developed quantitative evaluation methods for determining whether consumer panelists can properly perform time–intensity evaluation. In every trial, we fitted an exponential function to measured intensity data for bitterness and retronasal aroma. The correlation coefficients between measured time–intensity data and the fitted exponential curves were greater than 0.8 in about 90% of trials, indicating that we had successfully developed a time–intensity system for use with consumer panelists, even after just a single training trial using a nontrained consumer. We classified participants into two groups based on their consumption of canned coffee beverages. Significant difference was observed in only AUC of sensory modality (bitterness compared with retronasal aroma) among conventional TI parameters using two‐way ANOVA. However, three‐way ANOVA including a time course revealed significant difference between bitterness and retronasal aroma in the high‐consumption group. Moreover, the high‐consumption group more easily discriminated between bitterness and retronasal aroma than the low‐consumption group. This finding implied that manufacturers should select consumer panelists who are suitable for their concepts of new products.     

NOTES ON CONSUMER ORIENTED SENSORY EVALUATION

There are two approaches of sensory evaluation to consumer-product assessment. One can either start with (1) the taxonomy or list of different test methods, and show where these are applied, or else, (2) begin with a series of business decisions which require consumer feedback, and illustrate different sensory tests that are used to insure the adequacy of these decisions. This paper shows the second approach. It illustrates how consumer responses can be adequately gauged in situations where the result is measured by marketing decisions with dollars and cents returns.     

Prediction of consumer liking from trained sensory panel information: Evaluation of neural networks

This study was set out to establish artificial neural networks (ANN) as an alternative to regression methods (multiple linear, principal component and partial least squares regression) to predict consumer liking from trained sensory panel data. The sensory profile and acceptability of 10 market samples of beef bouillon products were measured. The products were distinct as evaluated by the trained sensory panel. A total of 100 regular beef bouillon product users from Manila measured overall liking, flavour, aftertaste and mouthfeel of the products. Curve fitting method was applied to identify sensory drivers of consumer liking. The sensory drivers of consumer liking were used as explanatory variables in artificial neural networks and regression methods. To overcome the limitations of regression methods we have used artificial neural network techniques to model consumer liking score as a function of trained sensory panel scores and achieved quite encouraging results. Our simulation experiments show that though the regression methods such as multiple linear regression (MLR), principal component regression (PCR) and partial least square (PLS) give an accurate prediction of consumer liking scores, this approach is not robust enough to handle the variations normally encountered in trained sensory panel data. ANNs were trained using the sensory panel raw data and transformed data. The networks trained with sensory panel raw data achieved 98% correct learning, the testing was in a range of 28–35%. Suitable transformation method was applied to reduce the variations in trained sensory panel raw data. The networks trained with transformed sensory panel data achieved about 80–90% correct learning and 80–95% correct testing. It is shown that due to its excellent noise tolerance property and ability to predict more than one type of consumer liking using a single model, the ANN approach promises to be an effective modelling tool.