Sensory Profiling Data Research Articles

Multivariate statistical visualisation and modelling of GC–MS data for sensory quality prediction of flavoured cider as influenced by storage time and temperature

It is important to cider producers to ensure the optimal quality of their products directly after production, and after extended shelf life. Quality assessments usually involve regular and continuous sensory evaluation conducted by trained panels. The competitive cider production environment necessitates extensive sensory analysis for new product launches, as part of quality control of existing products and during the production process. This could potentially lead to panel fatigue, less accuracy in sensory evaluation and delays in product launches. This paper describes the development of a partial least squares (PLS) model for the prediction of cider quality based on multivariate correlation of sensory and gas chromatography-mass spectroscopy (GC–MS) volatile compound profile data of a flavoured cider. Clear differences between cider samples of various batches and storage conditions could be visualised using principal component analysis (PCA). However, the developed PLS model was able to predict the commercial cider’s quality irrespective of differences in batch, storage temperature or storage time. The main compounds that are strongly associated with sensory quality and its decline during shelf-life storage were identified. This model is the first quality prediction model to be developed for South African flavoured cider which could be used to facilitate fast, consistent and accurate quality assessment in the high-pressure cider production and trade environment. Furthermore, since the model captures the sensory data obtained from a trained technical panel, it can be used to facilitate the calibration of sensory panels across production sites, reduce product development time and better optimise processes that impact sensory quality.

Cluster Analysis of Short Sensory Profile Data Reveals Sensory-Based Subgroups in Autism Spectrum Disorder.

Autism spectrum disorder is a common, heterogeneous neurodevelopmental disorder lacking targeted treatments. Additional features include restricted, repetitive patterns of behaviors and differences in sensory processing. We hypothesized that detailed sensory features including modality specific hyper- and hypo-sensitivity could be used to identify clinically recognizable subgroups with unique underlying gene variants. Participants included 378 individuals with a clinical diagnosis of autism spectrum disorder who contributed Short Sensory Profile data assessing the frequency of sensory behaviors and whole genome sequencing results to the Autism Speaks' MSSNG database. Sensory phenotypes in this cohort were not randomly distributed with 10 patterns describing 43% (162/378) of participants. Cross comparison of two independent cluster analyses on sensory responses identified six distinct sensory-based subgroups. We then characterized subgroups by calculating the percent of patients in each subgroup who had variants with a Combined Annotation Dependent Depletion (CADD) score of 15 or greater in each of 24,896 genes. Each subgroup exhibited a unique pattern of genes with a high frequency of variants. These results support the use of sensory features to identify autism spectrum disorder subgroups with shared genetic variants.

Food neophobia: Higher responsiveness to sensory properties but low engagement with foods generally

AbstractFood neophobia (FN), typically defined in terms of rejection of unfamiliar foods but also associated with higher negative arousal in relation to food, has been established as an important personality variable in explaining food preferences and choices. Past research has examined responses to foods as a function of FN but not considered if there are specific sensory qualities of foods that are more important in food rejections. We propose that the concept of sensory sensitivity may help explain the origin of increased arousal in high FN adults, and conducted an online survey in Singapore with 1896 participants as a first step towards investigating this hypothesis. FN was measured using the FN scale (Pliner & Hobden, 1992), and additionally participants: (a) rated their agreement with a series of statements that reflected their attitudes towards food sensory qualities, and (b) completed The Foodie Index (Pickering & Pickering, 2022) to obtain measures of food involvement and enjoyment. The results reinforced earlier findings that FN is related to an overall lower level of enjoyment of foods, and further revealed that: (a) evaluation of food sensory qualities prior to, or during, eating or sensory reasons for rejecting a food were positively related to FN, and (b) increasing disengagement with foods in terms of knowledge, interest, time and money spent on food as FN increases. Collectively, the results underscore the centrality of FN in understanding consumers' food‐related experiences and behaviors by showing that FN is related to both sensitivity about specific sensory properties and low engagement with foods generally.Practical ApplicationsFood and sensory profiling by consumers has been increasing in recent years. The present data will assist in interpretation of consumer studies in which FN and/or food interest/engagement has been measured, since both are found to be a strong source of variation in consumer data. In particular, both product engagement and level of FN have been shown elsewhere to impact how consumers allocate their attention to sensory tasks. This suggests that sources of variation in consumer responses, whether due to general or sensory‐specific responses to foods, are crucial in interpreting sensory profiling or preference data.

Exploring sensory phenotypes in autism spectrum disorder

BackgroundAtypical reactions to the sensory environment are often reported in autistic individuals, with a high degree of variability across the sensory modalities. These sensory differences have been shown to promote challenging behaviours and distress in autistic individuals and are predictive of other functions including motor, social, and cognitive abilities. Preliminary research suggests that specific sensory differences may cluster together within individuals creating discrete sensory phenotypes. However, the manner in which these sensory differences cluster, and whether the resulting phenotypes are associated with specific cognitive and social challenges is unclear.MethodsShort sensory profile data from 599 autistic children and adults between the ages of 1 and 21 years were subjected to a K-means cluster analysis. Analysis of variances compared age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder across the resultant clusters.ResultsA five-cluster model was found to minimize error variance and produce five sensory phenotypes: (1) sensory adaptive, (2) generalized sensory differences, (3) taste and smell sensitivity, (4) under-responsive and sensation seeking, and (5) movement difficulties with low energy. Age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder were found to differ significantly across the five phenotypes.LimitationsThe results were based on parent-report measures of sensory processing, adaptive behaviour, traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder, which may limit the generalizability of the findings. Further, not all measures are standardized, or psychometrically validated with an autism population. Autistic individuals with an intellectual disability were underrepresented in this sample. Further, as these data were obtained from established records from a large provincial database, not all measures were completed for all individuals.ConclusionsThese findings suggest that sensory difficulties in autistic individuals can be clustered into sensory phenotypes, and that these phenotypes are associated with behavioural differences. Given the large degree of heterogeneity in sensory difficulties seen in the autistic population, these sensory phenotypes represent an effective way to parse that heterogeneity and create phenotypes that may aid in the development of effective treatments and interventions for sensory difficulties.

Utility of Using the Sensory Profile in a Criminal Justice Setting

Abstract Date Presented Accepted for AOTA INSPIRE 2021 but unable to be presented due to online event limitations. Incarceration exposes individuals to a negative combination of sensory deprivation and sensory overstimulation, which has serious health consequences. The Sensory Profile (SP) was administered to 345 men and women residing in a corrections facility and who participated in OT programming. This presentation will illustrate how the SP data discriminate and then discuss the implications for using the SP in justice settings and designing appropriate intervention based on SP data. Primary Author and Speaker: Sandra Rogers Additional Authors and Speakers: John White

Relationship between Anthropometric Parameters and Sensory Processing in Typically Developing Brazilian Children with a Pediatric Feeding Disorder.

In this study, we aimed to relate anthropometric parameters and sensory processing in typically developing Brazilian children diagnosed with a pediatric feeding disorder (PFD). This was a retrospective study of typically developing children with a PFD. Anthropometric data were collected and indices of weight-for-age, length/height-for-age, and body mass index-for-age (BMI-for-age) were analyzed as z-scores. Sensory profile data were collected for auditory, visual, tactile, vestibular, and oral sensory processing. We included 79 medical records of children with a PFD. There were no statistically significant (p > 0.05) relationships between the anthropometric variables (weight-, length/height-, or BMI-for-age) and the sensory variables (auditory, visual, tactile, vestibular, or oral sensory processing). In conclusion, we found no relationship between anthropometric parameters and sensory processing in the sample of typically developing Brazilian children diagnosed with a PFD under study.

An Investigation of Sensory Processing in Children and Adolescents in Congregate Foster Care

Children in congregate foster care are at great risk for behavioral manifestations resultant from trauma. This pilot study explores sensory processing patterns among 41 youth living in congregate foster care. A retrospective chart review was utilized to explore Sensory Profile data of children in two age groups. 88% of the child sample, and 92% of the adolescent group, showed atypical sensory processing. Preliminary evidence suggests an association between sensory processing patterns and constructs of attention, social emotional functioning and conduct. Understanding patterns of sensory processing can inform strategies for self-regulation and environmental adaptations to support participation in everyday activities.

Preliminary investigation of potent thiols in Cypriot wines made from indigenous grape varieties Xynisteri, Maratheftiko and Giannoudhi

Polyfunctional thiols have previously been shown to be key aroma compounds in Sauvignon blanc and more recently in Chardonnay wines. Their role in other wine varieties such as those made from three popular indigenous Cypriot grape varieties has remained unexplored. As an extension of a previous project that profiled the sensory and chemical characteristics of Cypriot wines and their comparison to Australian wines, this study aimed to investigate five potent thiols in Xynisteri, Maratheftiko, Giannoudhi, Pinot gris, Chardonnay and Shiraz wines. Wines were analysed utilising Stable Isotope Dilution Assay (SIDA) with derivatisation and High-Performance Liquid Chromatography–Tandem Mass Spectrometry (HPLC-MS/MS). The varietal thiols measured were 4-methyl-4-sulfanylpentan-2-one (4MSP) that has an aroma of “boxwood” and “cat urine” at high concentration, 3-sulfanylhexan-1-ol (3SH) which has been described as having a “grapefruit/tropical fruit” aroma, and 3-sulfanylhexyl acetate (3SHA) that has also been described as having an aroma of “passionfruit”. Additionally, two other potent thiols were measured including benzyl mercaptan (BM) that has an aroma of “smoke and meat” and furfuryl thiol (FFT) that has been described as having a “roasted coffee” like aroma. The reason these thiols are known as potent thiols are due to their very low aroma detection thresholds in the low ng/L (ppt) range. Of the thiols that were measured, 3SH was the only varietal thiol detected in the red wine samples. All of the white wine samples contained 3SH, BM and 3SHA, whereas 4MSP was only detected in Pinot gris and three Xynisteri wines. The potent thiol, FFT, was detected only in the Chardonnay and four of the Xynisteri wines. Interestingly the thiols that were present in the samples were found at concentrations above their aroma detection thresholds (determined in hydroalcoholic solutions), especially 3SH which was found in an order of magnitude above its aroma detection threshold. These findings provide early knowledge of the presence of these thiols in Cypriot wines, compared with Australian wines and establish any relationships between this chemical data with previous wine sensory profile data.

Comparing temporal sensory product profile data obtained from expert and consumer panels and evaluating the value of a multiple sip TCATA approach

Both consumer and expert panels have been used to perform Temporal Check-All-That-Apply (TCATA) descriptive analysis, but it is not clear if they both provide the same product insights. Furthermore, most sensory testing takes place on one or two sips of a beverage which is not representative of actual consumer experience which occurs over multiple sips. This research aimed to determine if data from consumer and expert TCATA panels for the same products are interchangeable, and to investigate if extending TCATA to multiple sips provides additional insights into the dynamics of the consumption experience.Three milkshakes were assessed by an expert panel (n = 9) and 104 consumers where both panels evaluating eight sips of each milkshake using TCATA for eight attributes. Temporal discrimination of sensory attributes across samples was analysed on selected time slices, across sips using generalised linear model (GLM) Analysis of Deviance (ANODE) (R 4.0.0 (R Core Team, 2020)).The expert panel were more sensitive to attribute differences enabling them to discriminate products on more, but notably different attributes to the consumer panel. Multiple-sip data revealed significant changing dynamics in the perception of several attributes over and within sips, highlighting that single-sip studies do not reflect typical consumption experiences and that multiple-sip evaluations should be more widely applied to understand the consumer product experience. Sensory dynamics also varied significantly by panel type. Clearly consumer and expert TCATA panels are not interchangeable and choice of panel type should be determined in accordance with project objectives. It was also observed that many effects were attribute and product specific indicating findings cannot be generalised across products and further research on other products is needed.

Insights into chemical and sensorial aspects to understand and manage beer aging using chemometrics.

Beer chemical instability remains, at present, the main challenge in maintaining beer quality. Although not fully understood, after decades of research, significant progress has been made in identifying "aging compounds," their origin, and formation pathways. However, as the nature of aging relies on beer manufacturing aspects such as raw materials, process variables, and storage conditions, the chemical profile differs among beers. Current research points to the impact of nonoxidative reactions on beer quality. The effect of Maillard and Maillard intermediates on the final beer quality has become the focus of beer aging research, as prevention of oxidation can only sustain beer quality to some extent. On the other hand, few studies have focused on tracing a profile of whose compound is sensory relevant to specific types of beer. In this matter, the incorporation of "chemometrics," a class of multivariate statistic procedures, has helped brewing scientists achieve specific correlations between the sensory profile and chemical data. The use of chemometrics as exploratory data analysis, discrimination techniques, and multivariate calibration techniques has made the qualitatively and quantitatively translation of sensory perception of aging into manageable chemical and analytical parameters. However, despite their vast potential, these techniques are rarely employed in beer aging studies. This review discusses the chemical and sensorial bases of beer aging. It focuses on how chemometrics can be used to their full potential, with future perspectives and research to be incorporated in the field, enabling a deeper and more specific understanding of the beer aging picture.

Consumer perception and sensory profile of probiotic yogurt with added sugar and reduced milk fat

The objective of this study was to determine the effect of different milk fat (MF, 0%, 1.5%, 3.3% (w/w)) or added sugar (AS, 0%, 3.5%, 7% (w/w)) levels on the sensory properties and consumer acceptability of probiotic set yogurts fermented by Streptococcus thermophilus, Bifidobacterium bifidum, and Lactobacillus delbrueckii subsp. bulgaricus. The experimental yoghurt samples were compared with a control containing AS, 7% and MF, 3.3%. A quantitative descriptive analysis was conducted using 12 semi-trained panelists to evaluate the sensory profile of yogurts by rating the intensity of sensory descriptors on a 10 unit scale. Consumer preferences was determined using a group untrained individuals (n = 31) by applying the hedonic test for preference. Sensory mapping and Principal Component Analysis (PCA) were conducted to obtain a comprehensive understanding of the consumer behavior. Partial Least Squares Regression (PLSR) was conducted to compare the sensory profiling, consumer preference and instrumental data. Descriptive data showed significant differences (p < 0.05) among the samples for 8 of the 15 attributes amalyzed, including flavor and texture parameters. PCA showed that more than 80% of consumers highly preferred the low-fat yogurt, basically due to its firmness. Overall, consumer preference decreases with the AS reduction. The sample containing zero sugar is the least preferred sample. The reduction of added sugar below 3.5% is a challenge in terms of retaining product quality.

Volatile and sensory analysis to discriminate meat from lambs fed different concentrate-based diets

Context Diet is one the most important pre-slaughter factors that potentially influences meat quality, but its effect on flavour quality remains equivocal. Aim The aim of the present study was to investigate the effect of diet composition on the flavour and sensory quality of meat from Texel × Scottish Blackface ram lambs. Methods Groups of 11 lambs were assigned to one of the following four dietary treatments for 54 days before slaughter: a concentrate containing barley, maize and soybean (C treatment); C supplemented with a saturated fat source (Megalac®); C supplemented with protected linseed oil; a by-product-based diet containing citrus pulp, distillers grain and soybean. Samples of cooked M. longissimus thoracis et lumborum were subjected to volatile analysis involving solid-phase microextraction followed by gas chromatography–mass spectrometry and to sensory analysis performed by a trained panel. Key results Univariate analysis of volatile data and sensory data showed few differences due to dietary treatments. However, multivariate analysis of the volatile data, and to a lesser extent the sensory profile data, showed potential to discriminate between lamb meat samples, on the basis of the different dietary treatments. Conclusions The inclusion of certain dietary ingredients in the diets of lambs to enhance the nutritional profile of lamb meat (through increasing n-3 fatty acid content) or to reduce feed-formulation costs (through the use of by-products) has minor effects on sensory quality but permits some discrimination between dietary treatments following the application of multivariate analysis. Implications The application of the findings is in allowing lamb producers to use alternative feed types without affecting the sensory quality of lamb negatively, but with the potential to discriminate lamb meat on the basis of its dietary background.

Beyond principal component analysis (PCA) of product means: Toward a psychometric view on sensory profiling data

AbstractPrincipal component analysis (PCA) has its origin in psychology, where it was developed as a psychometric tool to measure latent variables of human cognition, personality, or behavior. This psychometric approach is also suitable to measure human perception based on sensory profiling data. To do so, we apply the PCA to a matrix that maintains the individual panelist's judgments, the matrix structure is in line with the “Tucker‐1 common loadings model.” Our approach (“Tucker‐1 PCA”) differs from the routine method of analyzing sensory profiling data, where PCA is applied to the matrix of mean scores of the product‐by‐attribute table (“Means‐PCA”). This article discusses the specific properties of the Tucker‐1 PCA and compares it to the Means‐PCA via a meta‐analysis on 422 datasets from Sensobase, a collection of sensory profiling studies. Tucker‐1 PCA provides advantages over Means‐PCA in terms of dimensionality, interpretability, and replicability of the factor structures.Practical ApplicationsTucker‐1 PCA is an easily applicable variant of PCA for sensory profiling data. Like Means‐PCA, it can be used to create product maps. It provides, however, more stable and easier interpretable axes. As a psychometric tool, Tucker‐1 PCA provides a measurement of products on underlying sensory dimensions.

Sensory Processing in Children With a History of Maltreatment

Abstract Date Presented 04/05/19 This poster will present a study that gathered sensory profile data for 408 children who experienced early adversity. Results characterize sensory processing behaviors of this population, offering participants insights about sensory characteristics and type of maltreatment, as well as length of exposure to maltreatment. Findings can help guide OT assessment and intervention for children who experience early adversity. Primary Author and Speaker: Amy Lynch Contributing Authors: David Cross, Casey Call, Amanda Howard

Capturing key sensory moments during biscuit consumption: Using TDS to evaluate several concurrent sensory modalities

AbstractIn an industrial context focusing on fat reduction in biscuits, the temporal dominance of sensations (TDS) evaluation method was applied to six biscuits differing in fat level (full, 30% fat reduced, or 50% fat reduced) and fat quality (butter or margarine). A list of 10 attributes for texture, taste, and olfactive modalities was produced based on a previously undertaken sensory profile (data not shown). TDS curves, pairwise comparison curves, and sensory trajectories were valuable tools for identifying the main dominance differences according to fat levels. The 50% fat‐reduced products were clearly discriminated from full‐fat products. Inclusion of the three sensory modalities within the attribute list was anticipated as a complex task. Nevertheless, specific sensory phases were identified and key flavor dominances defined. Dynamic sensory profiling opens the door to the creation of tailor‐made flavor compositions that compensate for part of the identified olfactive and taste losses.Practical ApplicationsThis work highlights the added value of considering several sensory modalities: taste, olfaction, and texture, at the same time, into TDS study. The definition of specific sensory phases over the food consumption will guide products developers to create specific flavors or combinations of flavors and taste compounds to cover the sensory gap observed in fat, sugar, or salt reduction context.

The Mixed Assessor Model and the multiplicative mixed model

A novel possibility for easy and open source based analysis of sensory profile data by a formal multiplicative mixed model (mumm) with fixed product effects and random assessor effects is presented by means of the generic statistical R-package mumm. The package is using likelihood principles and is utilizing newer developments within Automatic Differentiation by means of the Template Model Builder R-package. We compare such formal likelihood based analysis with the Mixed Assessor Model (MAM) analysis, where MAM is a linear approximation of the multiplicative mixed model. We use real sensory data as examples together with simulated data. We found that the formal mumm approach for hypothesis testing more resembles the MAM than the standard 2-way mixed model, and that both the mumm approach and the MAM give a higher power to detect product differences than the 2-way mixed model, when a “scaling effect” is present. We also validated that the novel contrast confidence limit method suggested previously for the MAM performs well and in line with the formal likelihood based confidence intervals of the mumm. Finally, the likelihood based mumm approach suggests that the more proper test for product difference would be a test that has a “joint product and scaling effect” interpretation.

Analysis and clustering of multiblock datasets by means of the STATIS and CLUSTATIS methods. Application to sensometrics

The STATIS method has been successfully applied to the analysis of sensory profiling data and other kinds data in sensometrics. We discuss its use and benefits and compare its outcomes to alternative methods for the analysis of multiblock data arising in situations such as projective mapping and free sorting experiments. More importantly, a method of clustering a collection of datasets measured on the same individuals, called CLUSTATIS, is introduced. It is based on the optimization of a criterion and consists in a hierarchical cluster analysis and a partitioning algorithm akin to the K-means algorithm. The procedure of analysis can be seen as an extension of the cluster analysis of variables around latent components (CLV, Vigneau & Qannari, 2003) to the case of blocks of variables. Alongside the determination of the clusters, a latent configuration is determined by the STATIS method. The interest of CLUSTATIS in sensometrics is discussed and illustrated on the basis of two case studies pertaining to the projective mapping also called Napping and the free sorting tasks, respectively.

Reference samples guide variable selection for correlation of wine sensory and volatile profiling data

The relationship between wine flavour and wine volatile composition is well recognised, however with thousands of compounds in wine the exact nature of individual contributions may be hard to determine due to synergistic and masking effects. Untargeted chemical analyses coupled with descriptive sensory and partial least squares regression modelling can help unravel interactions to identify groups of compounds that contribute to sensory properties. Variable selection is often applied prior to modelling to eliminate irrelevant variables. In this study, sensory references used to train the sensory panel were chemically analysed and employed to reduce the number of variables used to construct the models. This novel variable selection approach was compared against the inclusion of all variables and the most commonly applied variable selection method – analysis of variance. Models constructed from variables present in sensory references performed similarly to other models and identified interesting groups of compounds to investigate further.

ComDim: From multiblock data analysis to path modeling

ComDim (Common Dimensions) analysis was initially introduced within the context of sensometrics to analyze conventional and free choice sensory profiling data, and more generally multiblock datasets. Thereafter, it has gained some popularity in chemometrics and has been extended in different ways to meet specific needs. Recently, this strategy of analysis has been adapted to the supervised case, under the name of P-ComDim. Going further, we propose herein to extend ComDim to Path-ComDim where the datasets at hand are assumed to have a specific pattern of directed relations among them reflecting, for instance, a chain of influence. The aim of Path-ComDim is to analyze these datasets taking into account the structural connections among them. After a brief review of alternative path modeling approaches, Path-ComDim is detailed encompassing both methodological and algorithmic aspects. In the particular case of a single block to be predicted, it is shown that Path-ComDim is equivalent to P-ComDim analysis. Path-ComDim analysis is illustrated on the basis of a case study involving instrumental, sensory and preference data. Finally, the outcomes are compared to those obtained from alternative path modeling methods.

Blockwise simple component analysis via rotation, constraints or penalties, with an application to product × attribute × panelist data

Sensory profiling data consisting of judgements on a number of products with respect to a number of attributes by a number of panelists can be summarized in various ways. Besides finding components describing the main product features, there is an interest in individual panelist behavior. Earlier methods identify this by means of separate PCAs, Procrustes analyses, or three-way component methods, but these give only global comparisons of panelists. In the present paper, methods that can distinguish panelist behavior related to separate attributes, are described. These methods model the data in such a way that blocks of loadings pertaining to the attributes are either small or large. At the same time, one can zoom in on the loadings for panelists within each block of loadings associated with an attribute to inspect differences in panelist behavior. Two types of methods have been proposed for this earlier (rotation to simple blocks and penalizing blocks of loadings), and a third one is proposed in the present paper (constraining blocks of loadings to zero). The new approach is compared here to the other two methods. It is found that the rotation and constraints approaches work about equally well and better than the penalty approach. However, the rotation approach offers richer panelist behavior information, as is illustrated by the analysis of empirical data. It is also shown how, in this example, the reliability of idiosyncratic panelist behavior indicators can be evaluated.