USC Sensometrics and Chemometrics Laboratory

Nantes, France

USC Sensometrics and Chemometrics Laboratory

Nantes, France
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Petel C.,Soufflet Biotechnologies | Petel C.,Matrix | Courcoux P.,USC Sensometrics and Chemometrics Laboratory | Genovesi N.,AIT Ingredients | And 3 more authors.
Journal of Food Science | Year: 2017

This paper presents a new variant of the free sorting method developed to analyze the relationship between dried sourdough (DSD) and corresponding DSD-bread (bread) odors. The comparison of DSD and bread sensory characteristics is complicated due to their specific features (for example, acidity for DSD and a characteristic “baked bread” aroma for breads). To analyze them at the same time, this study introduces a new variant of the free sorting method, which adds an association task between DSD and bread after those of free sorting and verbalization. This separation makes it possible to change the product between tasks. It was applied to study the impact of 6 European commercial DSDs on their related DSD-bread. According to our results, this methodology enabled an association between different kinds of products and thus underlined the relationship between them. Moreover, as this methodology contains a verbalization task, it provides product descriptions. Compared with the standard free sorting method, free sorting with an association task gives the distance (i) between DSDs, (ii) between breads, and (iii) between DSDs and breads. The separation of product assessment through sorting and association avoids the separation of products according to their category (DSD or bread). © 2017 Institute of Food Technologists®

Rossini K.,USC Sensometrics and Chemometrics Laboratory | Rossini K.,French National Institute for Agricultural Research | Rossini K.,University of Nantes | Rossini K.,Federal University of Rio Grande do Sul | And 10 more authors.
Food Quality and Preference | Year: 2012

Several methods have been proposed in the literature to analyze conventional sensory profiling data. We focus on factor analytical methods which have been extensively used due to their ability to produce graphical displays which are both useful and easy to interpret. Available factor analytical methods include principal components analysis on averaged assessors data or on the data matrix obtained by stacking the assessors' datasets one on top of the others, and canonical variates analysis; each method has advantages and drawbacks. As an alternative it is advocated the use of PLS discriminant analysis, which is at the intersection of the methods mentioned above. This method of analysis takes account of the within and between product variations while minimizing the impact of multicolinearity. It provides statistical tools to assess on the one hand the agreement among assessors and the discrimination among products by means of the between to total variance ratio, and on the other hand the relative importance of variables by means of VIP (variable importance in the projection) indices. The VIP indices may also be useful to guide the selection of a subset of relevant attributes from the complete set of attributes. In this paper, PLS discriminant analysis is compared with other methods, and results are illustrated through a case study. In particular, the stability of the various methods is investigated using assessors' re-sampling (bootstrap) and confidence ellipses. © 2011 Elsevier Ltd.

Vigneau E.,USC Sensometrics and Chemometrics Laboratory | Vigneau E.,French National Institute for Agricultural Research | Vigneau E.,University of Nantes | Endrizzi I.,Research and Innovation Center | And 3 more authors.
Food Quality and Preference | Year: 2011

In consumer studies, liking scores for a set of products are usually collected from a panel of consumers. When additional information is available both on products and consumers, the data can be organized in an L-shaped structure. The CLV (Clustering around Latent Variables) approach which was originally designed to identify segments of consumers according to their preferences is extended in order to take account of product characteristics data or/and consumer background information. © 2011 Elsevier Ltd.

Pinto F.S.T.,Federal University of Rio Grande do Sul | Fogliatto F.S.,Federal University of Rio Grande do Sul | Qannari E.M.,USC Sensometrics and Chemometrics Laboratory | Qannari E.M.,French National Institute for Agricultural Research | Qannari E.M.,University of Nantes
Food Quality and Preference | Year: 2014

In sensory analysis attributes are measured on samples based on human judgment. The ability to detect differences is essential when selecting a panelist, as well as the repeatability in assessments and the agreement among panelists (or reproducibility), which is our definition of panel consistency. Our goal in this paper is to identify an efficient method to compare evaluation profiles from panelists measuring a given sensory attribute on different samples, assessing the panel's consistency. For that we investigate two methods available in the literature - consonance analysis (Dijksterhuis, 1995), and repeatibility and reproducibility analysis (Rossi, 2001) - and propose a new method, based on the internal consistency test and the calculation of the Cronbach's alpha coefficient (Cronbach, 1951). We tested our proposition using a dataset from a case study in which beef cubes in stew, used as combat ration by the American Army, are characterized by a sensory panel using the Spectrum protocol. Different product formulations based on military specifications yielded eight samples evaluated by nine panelists in quadruplicate. Twenty-four sensory attributes were assessed by the panelists. Results pointed to the Cronbach's alpha coefficient as best among the methods tested, which is justified threefold: (i) it allows identifying attributes better understood by panelists, (ii) it gives a ranking of panelists according to their consensus with the rest of the panel, and (iii) it is analytically simpler in comparison with other methods. © 2013 Elsevier Ltd.

Lofstedt T.,Umeå University | Hanafi M.,USC Sensometrics and Chemometrics Laboratory | Mazerolles G.,French National Institute for Agricultural Research | Trygg J.,Umeå University
Chemometrics and Intelligent Laboratory Systems | Year: 2012

OnPLS was recently presented as a general extension of O2PLS to the multiblock case. OnPLS is very similar to O2PLS in the case of two blocks, but generalises symmetrically to cases with more than two blocks, i.e. without giving preference to any one of the blocks.This article presents a straight-forward extension to this method and thereby also introduces the OPLS framework to the field of PLS path modelling. Path modelling links a number of data blocks to each other, thereby establishing a set of paths along which information is considered to flow between blocks, representing for instance a known time sequence, an assumed causality order, or some other chosen organising principle. Compared to existing methods for path analysis, OnPLS extracts a minimum number of predictive components that are maximally covarying with maximised correlation. This is a significant contribution to path modelling, because other methods may yield score vectors with variation that obstructs the interpretation. The method achieves this by extracting a set of orthogonal components that capture local phenomena orthogonal to the variation shared with all the connected blocks.Two applications will be used to illustrate the method. The first is based on a simulated dataset that shows how the interpretation is improved by removing orthogonal variation and the second on a real data process for the monitoring of protein structure changes during cheese ripening by analysing infrared data. © 2012 Elsevier B.V.

Repoux M.,University of Burgundy | Laboure H.,University of Burgundy | Courcoux P.,USC Sensometrics and Chemometrics Laboratory | Courcoux P.,University of Nantes | And 6 more authors.
Flavour and Fragrance Journal | Year: 2012

The aim of this work was to clarify the influence of the properties (firmness and fat content) of a solid processed model cheese on in vivo aroma release while considering the role of the in-mouth process during both mastication and post-swallowing steps, and the hydrophobicity of aroma compounds, on a large number of well characterized subjects. In vivo aroma release was studied on 44 subjects who freely consumed six processed model cheeses flavoured with the same concentration of nonan-2-one and ethyl propanoate. Globally, an increase in firmness induced an increase in chewing duration, amount of saliva incorporated into the food bolus, total amount of aroma released and rate of release. The kinetics of release clearly differed between the two aroma compounds. Ethyl propanoate presented a higher release rate for firmer cheese and was more released during the mastication step, whereas nonan-2-one was more released during the post-swallowing step and more persistent in the mouth, due to its higher hydrophobicity. Consuming cheeses with a higher fat content led to a higher amount of product remaining in the mouth after swallowing, a lower amount of nonan-2-one released and a longer persistence of nonan-2-one in the breath. The results could be helpful to better understand the relative influence of the parameters related to products and subjects in order to reformulate foods with good sensory acceptability. © 2012 John Wiley & Sons, Ltd.

Courcoux P.,USC Sensometrics and Chemometrics Laboratory | Courcoux P.,French National Institute for Agricultural Research | Courcoux P.,University of Nantes | Qannari E.M.,USC Sensometrics and Chemometrics Laboratory | And 5 more authors.
Food Quality and Preference | Year: 2012

Free sorting is a quick and reliable means to assess similarities among a set of stimuli by a panel of subjects. In this procedure, subjects form as many groups of stimuli as they consider necessary, with the understanding that each group is formed with stimuli that are perceived as similar. However, no information is available about the structure of the groups formed by each subject. In practice, these groups are considered as equally distant from each other. This is a questionable assumption as it may not reflect the perception of the subjects towards the stimuli. Taxonomic free sorting is designed to cope with this problem. Once the subjects have achieved the free sorting of the stimuli, they are instructed to organize, step by step, the stimuli into a hierarchical structure thus giving more insight into the similarities among products. Statistical treatments of the data thus obtained are discussed and the procedure of evaluation is illustrated on the basis of a case study. © 2011 Elsevier Ltd.

Cardinal M.,French Research Institute for Exploitation of the Sea | Baron R.,French Research Institute for Exploitation of the Sea | Kouakou C.,French Research Institute for Exploitation of the Sea | Kouakou C.,College of the Atlantic | And 5 more authors.
Journal of Sensory Studies | Year: 2014

Many papers have recently discussed the value of a free sorting method as a rapid and simple alternative to quantitative descriptive analysis, considered the reference tool for food sensorial characterization. The aim of the present paper is to evaluate whether this method of free sorting can also be used to investigate the influence of processing parameters. An experimental design was applied to production conditions of enzymatic hydrolysates from salmon by-products. The effect of four processing parameters (time and temperature of hydrolysis, sugar and antioxidant addition) on the odor of the hydrolysates was studied using a sorting task with 45 untrained panelists and a quantitative descriptive analysis carried out with 11 trained panelists. This study on 21 enzymatic hydrolysates confirms the similarity of the two sensory maps and shows the value of free sorting in the sensory characteristic description step, especially to avoid missing some descriptors. It also highlights in this example that a holistic approach as sorting can reveal more easily than profiling the significant effects of process parameters on sensory characteristics and the relationships between sensory dimensions and instrumental measurements of volatile compounds. © 2014 Wiley Periodicals, Inc.

Withers C.,University of Reading | Methven L.,University of Reading | Qannari E.M.,USC Sensometrics and Chemometrics Laboratory | Allen V.J.,University of Reading | And 2 more authors.
Journal of Sensory Studies | Year: 2014

Taxonomic free sorting (TFS) is a fast, reliable and new technique in sensory science. The method extends the typical free sorting task where stimuli are grouped according to similarities, by asking respondents to combine their groups two at a time to produce a hierarchy. Previously, TFS has been used for the visual assessment of packaging whereas this study extends the range of potential uses of the technique to incorporate full sensory analysis by the target consumer, which, when combined with hedonic liking scores, was used to generate a novel preference map. Furthermore, to fully evaluate the efficacy of using the sorting method, the technique was evaluated with a healthy older adult consumer group. Participants sorted eight products into groups and described their reason at each stage as they combined those groups, producing a consumer-specific vocabulary. This vocabulary was combined with hedonic data from a separate group of older adults, to give the external preference map. Taxonomic sorting is a simple, fast and effective method for use with older adults, and its combination with liking data can yield a preference map constructed entirely from target consumer data. © 2014 Wiley Periodicals, Inc.

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