RV Coefficient Research Articles

Comparing preferred attribute elicitation to trained panelists' evaluations using a novel food product

AbstractThe present study compares a new rapid sensory method, preferred attribute elicitation (PAE), to a trained panelists' evaluations, using cookies containing green tea extract (GTE) as a model. The cookies contained added amounts of 0, 2, 4, 7, and 9% GTE based on the weight of flour. Ten trained panelists evaluated the cookies. The panelists were trained for 10 one‐hour sessions followed by three replicates of testing. Additionally, 43 panelists in two different sessions (n = 25 and 18), evaluated the five samples following the PAE method. RV coefficients were used to provide a numerical value for the degree of similarity between the descriptive data obtained from the PAE sessions and the descriptive analysis panel. The RV coefficient for the two PAE sessions was .843, indicating a very high similarity between the sessions. However, the RV coefficient comparing the two PAE sessions to the descriptive analysis data were .554 and .179, respectively. These results indicate that the PAE method was not comparable to the trained panelists' evaluations. Future work needs to identify when PAE is the most suitable method to use and to modify the existing methodology to make it a more efficient method.Practical applicationsPreferred attribute elicitation (PAE) is a rapid sensory analysis method that uses untrained panelists to evaluate attributes of a product and determine what attributes drive consumer liking. This study investigates how the technique (using untrained panelist) compares to a trained panel when testing baked products differing in flavor intensity. There was not a relationship between the PAE sessions and trained panel for the flavors of this particular product. More work must be done to determine why the evaluations of the flavor was not consistent if PAE is to be used in future sensory trials.

Confiabilidad de la batería de evaluación propioceptiva en personas con amputación transtibial que utilizan prótesis, en el Hospital Militar Central

BackgroundFor decades, different scales, tests, and batteries have been used to measure physical abilities such as proprioception. Although there are tests in the clinical practice for assessing proprioception, there are no valid and reliable tests for populations with special conditions, such as amputation. ObjectiveTo determine the reliability of the Proprioceptive Assessment Battery on Patients with Transtibial Amputations (BEPAT in Spanish) in patients of the Hospital Militar Central of Bogotá, Colombia. Materials and methodsA cross-sectional study was conducted using the BEPAT to assess patients undergoing rehabilitation for traumatic transtibial amputation in the Hospital Militar Central of Bogotá. A total of 30 patients were recruited using a non-probabilistic convenience approach. Inclusion criteria included: being of legal age, having unilateral transtibial amputation of traumatic origin, using a prosthesis, being able to adopt unipedal and bipedal standing, and perform a gait test. The test was applied by two evaluators with a test-retest approach. ResultsAn inter-rater reliability of 0.99 and an intra-rater reliability of 0.78 were found when using the Escoufier RV coefficient as a similarity measure. ConclusionsThe BEPAT has a very high inter-rater and intra-rater reliability. A very high statistical relationship was found between the observations made by the two evaluators in each of the two tests. This allows the BEPAT to be recommended as a reliable tool for assessing proprioception in young men with transtibial amputations.

Standardised evaluation of medicine acceptability in paediatric population: reliability of a model.

ObjectivesOur novel tool to standardise the evaluation of medicine acceptability was developed using observational data on medicines use measured in a paediatric population included for this purpose (0–14 years). Using this tool, any medicine may be positioned on a map and assigned to an acceptability profile. The present exploration aimed to verify its statistical reliability.MethodsPermutation test has been used to verify the significance of the relationships among measures highlighted by the acceptability map. Bootstrapping has been used to demonstrate the accuracy of the model (map, profiles and scores of acceptability) regardless of variations in the data. Lastly, simulations of enlarged data sets (×2; ×5; ×10) have been built to study the model's consistency.Key findingsPermutation test established the significance of the meaningful pattern identified in the data and summarised in the map. Bootstrapping attested the accuracy of the model: high RV coefficients (mean value: 0.930) verified the mapping stability, significant Adjusted Rand Indexes and Jaccard coefficients supported clustering validity (with either two or four profiles), and agreement between acceptability scores demonstrated scoring relevancy. Regarding enlarged data sets, these indicators reflected a very high consistency of the model.ConclusionsThese results highlighted the reliability of the model that will permit its use to standardise medicine acceptability assessments.

Check-All-That-Apply (CATA) with semi-trained assessors: Sensory profiles closer to descriptive analysis or consumer elicited data?

Check-All-That-Apply (CATA) is a simple and fast sensory profiling tool. Yet, its application has been mainly focused on consumer studies; the aim of this study was to evaluate the application of CATA with semi-trained (ST) individuals (N = 37). ST individuals were consumers who underwent 1 h of training with physical references on the definition of attributes included in the CATA ballot. ST-CATA results were compared, on a panel level, to Descriptive Analysis (DA) with trained panellists (N = 8) and to CATA with consumers (N = 70). Moreover, the effect of training was examined, to uncover training vs. method-related variations in CATA profiling.ST-CATA and DA exhibited the highest similarity in sample configurations (94%) for two Multiple Factor Analysis factors. For all 3 factors, similarity was over 95% for all method combinations; however the RV coefficient between consumers and DA was marginally significant (P = .08). The extent of explained sensory variations in ST-CATA was not negatively affected by the smaller panel size, compared to consumers’ CATA. Training had a positive effect on attributes’ citation frequency, identification of taste, flavour and complex attribute differences among samples. CATA results did not provide the same range of differences with DA, especially for texture.Overall results support the validity of CATA with ST assessors and suggest its potential for industrial use, when a timely and cost-efficient description of products is required. Attention should be given though when a detailed quantitative profile of sample differences is required, since intensity is not well represented by CATA derived measurements due to the method constraints.

Brain activation detection by modified neighborhood one-class SVM on fMRI data

Abstract The one-class support vector machine (OC-SVM) is a data-driven machine learning method that has been applied as a novel technique for brain activation detection. Several researchers have obtained positive preliminary results using OC-SVMs. Nevertheless, existing algorithms are either too complicated or oversimplified and their performance needs to be further improved. In this study, a modified neighborhood one-class support vector machine (MNOC-SVM) algorithm is proposed to detect brain functional activation on functional magnetic resonance imaging (fMRI) data. This method is based on two basic assumptions: (a) For task-related fMRI data, time series of only a few voxels are related to a particular functional activity or functional area, and these voxels should be identified as activated voxels, i.e., the outliers. In contrast, for resting-state fMRI data, only a small number of voxels are unrelated to any resting-state functional networks. These voxels should instead be taken as non-activated voxels, i.e., the outliers. (b) Close voxels have similarly activated or non-activated states. To improve detection accuracy, we apply the following features to each voxel: the RV coefficient between each voxel and its 26 neighborhood voxels (or fewer than 26 for voxels on the edge of the brain), a flag for isolated voxels and a flag for isolated areas. For both task-related and resting-state fMRI data, our MNOC-SVM method effectively detects activated functional areas in the whole brain.

Detecting a currency’s dominance using multivariate time series analysis

A currency exchange rate is the price of one country’s currency in terms of another country’s currency. There are four different prices; opening, closing, highest, and lowest can be achieved from daily trading activities. In the past, a lot of studies have been carried out by using closing price only. However, those four prices are interrelated to each other. Thus, the multivariate time series can provide more information than univariate time series. Therefore, the enthusiasm of this paper is to compare the results of two different approaches, which are mean vector and Escoufier’s RV coefficient in constructing similarity matrices of 20 world currencies. Consequently, both matrices are used to substitute the correlation matrix required by network topology. With the help of degree centrality measure, we can detect the currency’s dominance for both networks. The pros and cons for both approaches will be presented at the end of this paper.

Patterns of integration in the canine skull: an inside view into the relationship of the skull modules of domestic dogs and wolves

The skull shape variation in domestic dogs exceeds that of grey wolves by far. The artificial selection of dogs has even led to breeds with mismatching upper and lower jaws and maloccluded teeth. For that reason, it has been advocated that their skulls (including the teeth) can be divided into more or less independent modules on the basis of genetics, development or function. In this study, we investigated whether the large diversity of dog skulls and the frequent occurrence of orofacial disproportions can be explained by a lower integration strength between the modules of the skull and by deviations in their covariation pattern when compared to wolves. For that purpose, we employed geometric morphometric methods on the basis of 99 3D-landmarks representing the cranium (subdivided into rostrum and braincase), the mandible (subdivided into ramus and corpus), and the upper and lower tooth rows. These were taken from CT images of 196 dog and wolf skulls. First, we calculated the shape disparity of the mandible and the cranium in dogs and wolves. Then we tested whether the integration strength (measured by RV coefficient) and the covariation pattern (as analysed by partial least squares analysis) of the modules subordinate to the cranium and the mandible can explain differing disparity results. We show, contrary to our expectations, that the higher skull shape diversity in dogs is not explained by less integrated skull modules. Also, the pattern of their covariation in the dog skull can be traced back to similar patterns in the wolf. This shows that existing differences between wolves and dogs are at the utmost a matter of degree and not absolute.

Validation of projective mapping as potential sensory screening tool for application by the honeybush herbal tea industry

Honeybush herbal tea is produced from the endemic South African Cyclopia species. Plant material subjected to a high-temperature oxidation step (“fermentation”) forms the bulk of production. Production lags behind demand forcing tea merchants to use blends of available material to supply local and international markets. The distinct differences in the sensory profiles of the herbal tea produced from the different Cyclopia species require that special care is given to blending to ensure a consistent, high quality product. Although conventional descriptive sensory analysis (DSA) is highly effective in providing a detailed sensory profile of herbal tea infusions, industry requires a method that is more time- and cost-effective. Recent advances in sensory science have led to the development of rapid profiling methodologies. The question is whether projective mapping can successfully be used for the sensory characterisation of herbal tea infusions. Trained assessors performed global and partial projective mapping to determine the validity of this technique for the sensory characterisation of infusions of five Cyclopia species. Similar product configurations were obtained when comparing results of DSA and global and partial projective mapping. Comparison of replicate sessions showed RV coefficients >0.8. A similarity index, based on multifactor analysis, was calculated to determine assessor repeatability. Global projective mapping, demonstrated to be a valid method for providing a broad sensory characterisation of Cyclopia species, is thus suitable as a rapid quality control method of honeybush infusions. Its application by the honeybush industry could improve the consistency of the sensory profile of blended products.

Changes in the business model for Spanish fresh tomato trade

The business model applied to the fresh tomato trade from Almería is well known in Spain and abroad. The changes in demand are forcing export companies to change their trade strategies to become or remain competitive. The purpose of this paper is to know the business structure and its export dynamics in addition to the changes in trade strategies made by companies in Almería during the 2009-2013 period. The methodology is based on the Herfindahl-Hirshman index and the foreign trade competitiveness index, whereas the congruence analysis is based on Pearson’s correlation coefficients and the RV coefficient. We have also applied the dual multiple factor analysis to verify changes made to the trade policy in leading businesses between two periods or scenarios. The research shows that export-driven companies behave as a moderately concentrated structure and there is an increase in the number of exporters. The competitiveness map for Almería reveals the sector’s trend with regard to the most important markets. We have verified the changes made to their trade strategy to adjust to changes in foreign trade between the 2008/09 and 2012/13 campaigns. Finally, it can be pointed out that, in the analyzed period, changes in the business model for fresh tomato trade of Almería have not been significant, being its structure of moderate concentration. In addition, the great majority of variations in strategies of companies to adapt to the competitive environment have been made by leading companies.

Exploring salient dimensions in a free sorting task: A cross-country study within the elderly population

Free sorting tasks have been widely applied on different age segments to study the categorization of foods. However the method has received little attention in the investigation of older adults’ perception. Given the importance of understanding elderly perceptions in order to develop acceptable products, the main objective of this study was to investigate the factors that were able to affect the categorization of samples within different age segments of the healthy elderly consumers. Furthermore, in order to support the obtained configurations, the applicability of a free sorting task within different age segments of elderly population was investigated.The role of familiarity was considered to better understand the process of food categorization. A free sorting and a liking task were applied on French and Italian elderly to study perception and preference of familiar (peas) and less familiar (sweetcorn) vegetables. Similarities between the categorization maps, the preference maps and the sensory maps from vegetable samples were assessed through the RV coefficient and map visual inspection.Familiarity with the product was the main factor affecting the categorization among elderly. Categorization maps from a familiar vegetable were found to be suitable to obtain information on sensory and hedonic dimensions, while maps obtained from a less familiar vegetable mainly depicted sensory variability. The free sorting task was found to be a suitable method to use with healthy older adults, that allowed the detection of differences in the categorization of stimuli even among the more aged representatives of the elderly population.

Morphometric covariation between palatal shape and skeletal pattern in Class II growing subjects.

To evaluate the patterns of covariation between palatal and craniofacial morphology in Class II subjects in the early mixed dentition by means of geometric morphometrics. A cross-sectional sample of 85 Class II subjects (44 females, 41 males; mean age 8.7 years ± 0.8) was collected retrospectively according to the following inclusion criteria: European ancestry (white), Class II skeletal relationship, Class II division 1 dental relationship, early mixed dentition, and prepubertal skeletal maturation. Pre-treatment digital 3D maxillary dental casts and lateral cephalograms were available. Landmarks and semilandmarks were digitized (239 on the palate and 121 on the cephalogram) and geometric morphometric methods (GMM) were applied. Procrustes analysis and principal component analysis (PCA) were performed to reveal the main patterns of palatal shape and craniofacial skeletal shape variation. Two-block partial least squares analysis (PLS) assessed patterns of covariation between palatal morphology and craniofacial morphology. For the morphology of the palate, the first principal component (PC1) described variation in all three dimensions. For the morphology of the craniofacial complex, PC1 showed shape variation mainly in the vertical direction. Palatal shape and craniofacial shape covaried significantly (RV coefficient: 0.199). PLS1 accounted for more than 64 per cent of total covariation and related divergence of the craniofacial complex to palatal height and width. The more a Class II subject tended towards high-angle divergence, the narrower and higher was the palate. Class II high-angle patients tended to have narrower and higher palates, while Class II low-angle patients were related to wider and more shallow palates.

A fast small-sample kernel independence test for microbiome community-level association analysis.

To fully understand the role of microbiome in human health and diseases, researchers are increasingly interested in assessing the relationship between microbiome composition and host genomic data. The dimensionality of the data as well as complex relationships between microbiota and host genomics pose considerable challenges for analysis. In this article, we apply a kernel RV coefficient (KRV) test to evaluate the overall association between host gene expression and microbiome composition. The KRV statistic can capture nonlinear correlations and complex relationships among the individual data types and between gene expression and microbiome composition through measuring general dependency. Testing proceeds via a similar route as existing tests of the generalized RV coefficients and allows for rapid p-value calculation. Strategies to allow adjustment for confounding effects, which is crucial for avoiding misleading results, and to alleviate the problem of selecting the most favorable kernel are considered. Simulation studies show that KRV is useful in testing statistical independence with finite samples given the kernels are appropriately chosen, and can powerfully identify existing associations between microbiome composition and host genomic data while protecting type I error. We apply the KRV to a microbiome study examining the relationship between host transcriptome and microbiome composition within the context of inflammatory bowel disease and are able to derive new biological insights and provide formal inference on prior qualitative observations.

Estimating and interpreting more than two consensus components in projective mapping: INDSCAL vs. multiple factor analysis (MFA)

In this paper a general framework is proposed for understanding and analysing more than two consensus components in projective mapping (also known as Napping®) studies. Focus is on how two models, multiple factor analysis (MFA) and individual differences scaling (INDSCAL) based on the weighted Euclidean model (WEM), relate to each other and to the general framework. The stability of the consensus configurations of both methods are compared. The relations between the results of the two methods are investigated using the RV coefficient and an alternative index called SMI which gives equal weight to the axes regardless of the relative size of the singular values. The methods are tested and compared using three datasets and simulations.

Geometric morphometric analysis of craniofacial growth between the ages of 12 and 14 in normal humans.

There is great variation of growth among individuals. The question whether patients with different skeletal discrepancies grow differently is biologically interesting but also important in designing clinical trials. The aim of the present study was to evaluate whether growth direction depends on the initial craniofacial pattern. The sample consisted of 350 lateral cephalograms of 175 subjects (91 females and 84 males) followed during normal growth without any orthodontic treatment. The examined ages were 12 (T1) and 14 (T2) years. The cephalograms were obtained from the American Association of Orthodontists Foundation (AAOF) Craniofacial Growth Legacy Collection (Burlington, Fels, Iowa, and Oregon growth studies). We digitally traced 15 curves on each cephalogram, comprehensively covering the craniofacial skeleton, and located 127 points on the curves, 117 of which were sliding semilandmarks and 10 fixed. Procrustes alignment, principal component analysis and two-block partial least squares analysis were performed, after sliding the semilandmarks to minimize bending energy. The first 10 principal components (PCs) described approximately 71 per cent of the total shape variance. PC1 was related to shape variance in the vertical direction (low/high angle skeletal pattern) and PC2 was mainly related to shape variance in the anteroposterior direction (Class II/Class III pattern). PC3 was mainly related to the shape variance of the mandibular angle. All subjects shared a similar growth trajectory in shape space. We did not find any correlation between the initial shape and the magnitude of shape change between T1 and T2, but males showed a greater shape change than females. The direction of shape change was moderately correlated to the initial shape (RV coefficient: 0.14, P < 0.001). The initial shape of the craniofacial complex covaried weakly with the direction of shape change during growth.

Morphometric covariation between palatal shape and skeletal pattern in children and adolescents: a cross-sectional study.

To assess shape covariation of the palate and craniofacial complex (CFC) in children and adolescents. Pre-treatment lateral cephalometric radiographs and corresponding maxillary casts of 100 children (8-10 years) and 100 adolescents (15-20 years) were digitized. Exclusion criteria were previous orthodontic treatment, craniofacial syndromes, mouth breathing, finger sucking, crossbite, tooth agenesis, and tooth impaction. Palatal shape was described with 239 surface and curve semilandmarks and craniofacial shape with 10 fixed landmarks and 117 curve semilandmarks. Procrustes superimposition and principal component analysis were applied for evaluation of shape variability. Shape covariation between palate and CFC was assessed with partial least squares analysis. The first five principal components explained 77 per cent (palate) and 60 per cent (CFC) of total shape variability. The palate varied mainly in height (adolescent group) and width-length (both groups), whereas the CFC varied mainly in the vertical dimension. Significant covariation was found between the craniofacial and palatal components (RV coefficient: 0.27, children; RV: 0.23, adolescents). Variation of the CFC in the vertical and anteroposterior direction was mainly related to variation in the height-width and the width-length ratio of the palate, respectively. The use of lateral cephalometric radiographs eliminated the transverse dimension from the craniofacial shape analysis. The study was cross-sectional, so the observed intergroup differences should be interpreted with caution. Covariation strength and pattern were similar in children and adolescents. The closer a subject was to the high-angle end of the variability spectrum, the higher and narrower was the palate, and conversely.

On the comparison of the strength of morphological integration across morphometric datasets.

Evolutionary morphologists frequently wish to understand the extent to which organisms are integrated, and whether the strength of morphological integration among subsets of phenotypic variables differ among taxa or other groups. However, comparisons of the strength of integration across datasets are difficult, in part because the summary measures that characterize these patterns (RV coefficient and rPLS ) are dependent both on sample size and on the number of variables. As a solution to this issue, we propose a standardized test statistic (a z-score) for measuring the degree of morphological integration between sets of variables. The approach is based on a partial least squares analysis of trait covariation, and its permutation-based sampling distribution. Under the null hypothesis of a random association of variables, the method displays a constant expected value and confidence intervals for datasets of differing sample sizes and variable number, thereby providing a consistent measure of integration suitable for comparisons across datasets. A two-sample test is also proposed to statistically determine whether levels of integration differ between datasets, and an empirical example examining cranial shape integration in Mediterranean wall lizards illustrates its use. Some extensions of the procedure are also discussed.

Product spaces derived from projective mapping and CATA questions: Influence of replicated assessments and increased number of study participants

AbstractMethodological research is needed to support the continued popularity of sensory product characterization by consumers. The present research considers stability and reliability of such product spaces. Using data from 13 studies (n = 1332) involving check‐all‐that‐apply questions (CATA) and projective mapping tasks replicated assessments and increasing the sample size are evaluated for their impact on the product spaces derived from a base group of consumers. In each study, a group of consumers (41–95 participants) completed a sensory characterization task twice under identical conditions (“replication” condition), and additional consumers (49–93 participants) completed the task (“increased sample size” condition). The stability of product spaces was evaluated using a bootstrapping resampling approach. Both experimental conditions had a small but positive impact as evidenced by small increases in average RV coefficients across simulations. Additionally, in studies using projective mapping, the confidence ellipses around sample positions were smaller than those established in product spaces with the base group of consumers. This pointed to increased sample discrimination.Practical applicationsThis research reveals that replication and increased sample size by inclusion of additional consumers can be used to increase stability of product spaces from sensory characterization based on projective mapping and CATA questions. Stability in product spaces underpins reliability of the research, and by extension internal validity.

EMMLi: A maximum likelihood approach to the analysis of modularity.

Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be accomplished through exploratory (e.g., cluster analysis) or confirmatory approaches (e.g., RV coefficient analysis). Although statistically more robust, confirmatory approaches are generally unable to compare across different model structures. For example, RV coefficient analysis finds support for both two- and six-module models for the therian mammalian skull. Here, we present a maximum likelihood approach that takes into account model parameterization. We compare model log-likelihoods of trait correlation matrices using the finite-sample corrected Akaike Information Criterion, allowing for comparison of hypotheses across different model structures. Simulations varying model complexity and within- and between-module contrast demonstrate that this method correctly identifies model structure and parameters across a wide range of conditions. We further analyzed a dataset of 3-D data, consisting of 61 landmarks from 181 macaque (Macaca fuscata) skulls, distributed among five age categories, testing 31 models, including no modularity among the landmarks and various partitions of two, three, six, and eight modules. Our results clearly support a complex six-module model, with separate within- and intermodule correlations. Furthermore, this model was selected for all five age categories, demonstrating that this complex pattern of integration in the macaque skull appears early and is highly conserved throughout postnatal ontogeny. Subsampling analyses demonstrate that this method is robust to relatively low sample sizes, as is commonly encountered in rare or extinct taxa. This new approach allows for the direct comparison of models with different parameterizations, providing an important tool for the analysis of modularity across diverse systems.

A Comparison of Two Methods for Generating Descriptive Attributes with Trained Assessors: Check‐All‐That‐Apply (CATA) vs. Free Choice Profiling (FCP)

AbstractThe quality and reliability of descriptive profiles are closely linked to an accurate selection of the attributes included therein. Descriptive profiles with trained assessors often face challenges stemming from consensual procedures and the risk of forgetting some relevant descriptors. To overcome these problems, the suitability of two nonconsensual methods performed by trained assessors, namely free choice profiling (FCP) and check‐all‐that‐apply (CATA), are examined and compared when building a sensory profile for fish.Eighteen trained panelists having similar training were randomly split into two groups of nine assessors each. One group evaluated different fish species using CATA and the other using FCP, with both groups adopting the same experimental design.Although both methodologies generated an important number of sensory descriptors for the tested products, noticeable differences among methods were observed. CATA performed better than FCP in terms of the descriptive ability and slightly better regarding the discriminant capacity. Both methods provided similar product location in the multidimensional space. The RV coefficient was significantly different from zero for all the sensory modalities except for odor and texture. However, noticeable differences were observed in product description. The main limitations of the study were also discussed.Practical ApplicationsSensory descriptive analysis is normally the first step in the characterization of a food product, thus providing valuable information for food companies when designing and/or improving a product. This study shows and compares the usefulness of two methods, namely CATA and FCP, to obtain descriptive profiles, thus avoiding some of the bias linked to consensual procedures. Both methods are suitable for product discrimination, although they provide different sensory characterization for the different samples. The use of trained assessors, both with CATA and FCP, might increase the quality of a descriptive profile by avoiding useless terms and, especially in the case of CATA, ensuring that the most relevant descriptors are included.

Perception and Description of Premium Beers by Panels with Different Degrees of Product Expertise

The present study compares subjects with varying degrees of product expertise with regards to their ability to provide a sensory profile of beverages. Eight premium beers were evaluated by three different panels using a Napping® test, followed by a descriptive task. Two panels were constituted of consumers, classified according to their self-assessed product expertise into “Novices” (N = 14) and “Enthusiasts” (N = 26). The sensory panel at a large brewery, and a group of master brewers constituted the third panel (“Experts”, N = 15). The Napping® data from the three panels were digitalized using a coordinate system, whereas attributes were entered separately and treated as frequency table crossing products and attributes. The position data were analyzed by Hierarchical Multiple Factor Analysis (HMFA). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to test differences between the three panels with regards to the use of attributes. The HMFA results showed a separation of the samples into two distinct groups on the first dimension, whereas the second dimension highlighted the specificity of two of the samples. RV coefficients between partial configurations obtained from the three panels were all above 0.90, indicating high configurational similarity. In contrast, PLS-DA showed significant differences in the use of attributes, particularly between Experts and Novices, suggesting that product expertise is more associated with descriptive, rather than perceptual, ability.