117 research outputs found

    Understanding aroma release from model cheeses by a statistical multiblock approach on oral processing

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    For human beings, the mouth is the first organ to perceive food and the different signalling events associated to food breakdown. These events are very complex and as such, their description necessitates combining different data sets. This study proposed an integrated approach to understand the relative contribution of main food oral processing events involved in aroma release during cheese consumption. In vivo aroma release was monitored on forty eight subjects who were asked to eat four different model cheeses varying in fat content and firmness and flavoured with ethyl propanoate and nonan-2-one. A multiblock partial least square regression was performed to explain aroma release from the different physiological data sets ( masticatory behaviour, bolus rheology, saliva composition and flux, mouth coating and bolus moistening). This statistical approach was relevant to point out that aroma release was mostly explained by masticatory behaviour whatever the cheese and the aroma, with a specific influence of mean amplitude on aroma release after swallowing. Aroma release from the firmer cheeses was explained mainly by bolus rheology. The persistence of hydrophobic compounds in the breath was mainly explained by bolus spreadability, in close relation with bolus moistening. Resting saliva poorly contributed to the analysis whereas the composition of stimulated saliva was negatively correlated with aroma release and mostly for soft cheeses, when significant

    Contribution of temporal dominance of sensations performed by modality (M-TDS) to the sensory perception of texture and flavor in semi-solid products: A case study on fat-free strawberry yogurts

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    This study aimed to perform Temporal Dominance of Sensations by modality (M-TDS) combined with a multi-intake approach to investigate texture and flavor perception in semi-solid products. Trained panelists (n = 15) evaluated fat-free strawberry yogurts enriched with functional proteins involving texture modifications. As yogurt is a semi-solid product, its in-mouth residence time is short. A multi-intake approach was therefore expected to give more reliable information about the sensory properties perceived by panelists. The two modalities of texture and flavor were analyzed separately to characterize the effect of added proteins. Trials were made according to an experimental design with two factors (protein type and concentration) and three levels each. Different statistical treatments, taking or not the temporality of attributes into account, were performed on standardized and non-standardized data. The implementation of M-TDS was essential to highlight differences of flavor perception in addition to the more evident texture modifications. The study of sensory trajectories evidenced that texture modifications, induced by the use of different whey proteins, slightly modified the perception of flavor and sweetness. The global flavor perception of the samples varied with the number of spoons, which particularly impacted the taste attributes. This study highlighted the importance of using M-TDS when studying texture and flavor in semi-solid products, and the relevance of the multi-intake approach to characterize flavor perception. This methodology enabled panelists to evidence both marked texture differences and subtler flavor modifications, and these useful data were emphasized by combining different statistical treatments

    Simultaneous decomposition of multivariate images: Application to near infrared hyperspectral images of wheat

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    International audienceWe present here a three-way data analysis method able to reveal common latent components in a collection of multivariate images observed for different objects or scenes. The main objective is to follow the water diffusion in single wheat sections over time using Near-Infrared Hyperspectral Imaging (NIR-HSI). The study is mainly descriptive and data treatments were investigated to find the tissues common to different grains as well as to provide tissues specific to one or more samples. The algorithm proposed is based on the simultaneous decomposition of the covariance matrices calculated for each NIR image supposing that common loading vectors exist and can be weighted differently for each multivariate image. The method is illustrated by the analysis of NIR hyperspectral images acquired at regular time interval for five wheat kernel sections exposed to water. These results show that the kinetics of propagation of water and thus the germination are grain specific.Nous prĂ©sentons ici une mĂ©thode d'analyse de donnĂ©es trois voies en mesure de trouver les composants latents communs d’une collection d'images multivariĂ©es observĂ©es pour diffĂ©rents objets ou scĂšnes. L'objectif principal est de suivre la diffusion de l'eau dans des sections de blĂ© au fil du temps en utilisant l’imagerie hyperspectrale Proche-Infrarouge (NIR-HSI). L'Ă©tude est principalement descriptive et les traitements de donnĂ©es ont Ă©tĂ© dĂ©veloppĂ©s pour trouver des tissus communs Ă  diffĂ©rents grains ainsi que de fournir des tissus spĂ©cifiques Ă  un ou plusieurs Ă©chantillons. L'algorithme proposĂ© est basĂ© sur la dĂ©composition simultanĂ©e des matrices de covariance calculĂ©es pour chaque image NIR supposant que les vecteurs propres communs existent et peuvent ĂȘtre pondĂ©rĂ©es diffĂ©remment pour chaque image. La mĂ©thode est illustrĂ©e par l'analyse d’images hyperspectrales NIR acquises Ă  intervalle de temps rĂ©gulier pour cinq sections de blĂ© exposĂ©es Ă  l'eau. Ces rĂ©sultats montrent que la cinĂ©tique de la propagation de l'eau et ainsi la germination sont grain spĂ©cifique

    Chimiométrie appliquée à la spectroscopie infrarouge. Méthodes exploratoires

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    Determination of the consensus partition and cluster analysis of subjects in a free sorting task experiment

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    International audienceThe purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a con. sensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects. (C) 2013 Elsevier Ltd. All rights reserved
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