Search results for "Sensory analysis"

showing 10 items of 139 documents

A matching task as a potential technique for descriptive profile validation

2003

If panellists can successfully match products to the corresponding descriptive profiles, then the profiles can be regarded as product-relevant and valid. This work examined the ability of a trained panel to perform a matching task between products and their descriptive profiles. A 13-member panel, trained to assess eight cheeses in terms of 19 flavour attributes, performed the task based on their individually developed profiles. The panel's ability to match products to profiles was well above that expected by chance, and chi-square statistics for each of the products were significant (P<0.05). A correspondence analysis based on the group results indicated that all the products were relative…

0303 health sciencesMatching (statistics)Nutrition and Dietetics030309 nutrition & dietetics04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysisRegressionCorrespondence analysisCanonical analysisTask (project management)03 medical and health sciences0404 agricultural biotechnologyDiscriminantConsistency (statistics)Statistics[SDV.IDA]Life Sciences [q-bio]/Food engineeringAlgorithmComputingMilieux_MISCELLANEOUSFood ScienceMathematics
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Comparison of odour sensory profiles performed by two independent trained panels following the same descriptive analysis procedures

2000

Odour sensory profiling of 28 associations of cheese ripening micro-organisms was performed by two panels of 10 assessors on two different sites. Sample preparation, training protocols and references, tasting procedures and scoring were similar in the two laboratories. Panel 2 used 10 attributes and panel 1 used these terms plus 4 extra descriptors. Analysis of variance and multivariate methods (canonical variate analysis, generalised procrustes analysis and STATIS) exhibited differences between assessors within a panel and between panels concerning the use of the scoring scale and the strength of product discrimination by attribute. Panel 1 was more sensitive to fruity notes and panel 2 to…

0303 health sciencesMultivariate statisticsNutrition and DieteticsDescriptive statistics030309 nutrition & dieteticsSensory system04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysisGeneralised procrustes analysis03 medical and health sciences0404 agricultural biotechnologyCanonical variate analysisStatistics[SDV.IDA]Life Sciences [q-bio]/Food engineeringEconometricsWine tastingAnalysis of varianceComputingMilieux_MISCELLANEOUSFood ScienceMathematics
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FLASH table and canonical mapping of potato varieties

2000

International audience

0303 health sciencesNutrition and Dietetics030309 nutrition & dietetics04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysisCanonical analysis03 medical and health sciencesFlash (photography)0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringTable (database)Statistical analysisArithmeticComputingMilieux_MISCELLANEOUSFood ScienceMathematicsFood Quality and Preference
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The MAM-CAP table: A new tool for monitoring panel performances

2014

Abstract Assessor performances in sensory analysis are usually represented by three indicators: repeatability, discrimination and agreement. However, assessors can also differ on the range of their scores, the so-called “scaling effect”. Brockhoff, Schlich, and Skovgaard (2013) proposed the mixed assessor model (MAM) which, as the original assessor model ( Brockhoff & Skovgaard, 1994 ), takes this effect into account, but also allows for the product effect to be tested against a new interaction free of the scaling effect. The present paper proposes a unified system for monitoring assessor and panel performances based on the MAM. In addition to the product effect (tested at panel and individ…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsComputer science[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutritionscalingpanel performance04 agricultural and veterinary sciencesRepeatabilitymixed assessor model040401 food scienceSensory analysisUnified system03 medical and health sciences0404 agricultural biotechnologyScaling effectStatisticsRange (statistics)Table (database)Scaling[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood Science
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Sensory exploration of the freshness sensation in plain yoghurts and yoghurt-like products

2013

WOS: 000324008600021 ; http://www.sciencedirect.com/science/article/pii/S0950329313001092; International audience; The term "freshness sensation" is used by consumers for characterizing some plain yoghurts and yoghurt-like products. This study consisted in an investigation of this sensation aiming at determining its underlying sensory attributes. First, two focus groups of consumers were conducted to open up the framework. A set of plain yoghurts and yoghurt-like products, both commercial and experimental, was then subjected to sensory analysis. The samples were sorted by means of a free sorting task, and further scored for the intensity of their freshness sensation and their liking, by 72 …

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsFat content[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutritionfood and beveragesSensory system04 agricultural and veterinary sciences040401 food scienceSensory analysisfreshness sensation03 medical and health sciences0404 agricultural biotechnologytemporal dominance of sensationsSensationFood scienceyoghurtfree sorting[SDV.AEN]Life Sciences [q-bio]/Food and NutritionpreferencesFlavorFood ScienceMathematicsFood Quality and Preference
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Internal and external mapping of preferences for commercial lager beers : comparison of hedonic ratings by consumers blind versus with knowledge of b…

2001

Abstract The individual preferences of 170 consumers in six categories of age (20s, 30s, 40s) and gender (men, women) for 24 domestic, imported or specialty lager beers, tasted first blind and then with knowledge of brand and price, were investigated by preference mapping techniques. Internal preference mapping revealed differences in the preferences of consumers, with some consumers preferring domestic or ice beers, and others preferring specialty or imported beers. Hedonic ratings changed significantly from the blind to the informed tasting condition, particularly for consumers in their twenties, thereby documenting the significant role of non-sensory variables in the formulation of a hed…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsSCIENCE DU CONSOMMATEURJudgementProduct testingPreference mappingAdvertising04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysisPreference03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringWine tastingPsychologyConsumer behaviourComputingMilieux_MISCELLANEOUSFood Science
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What are the sensory differences among coffees? Multi-panel analysis of variance and FLASH analysis

1998

International audience

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsSensory system04 agricultural and veterinary sciencesVariance (accounting)[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysis03 medical and health sciencesFlash (photography)0404 agricultural biotechnologyPanel analysis[SDV.IDA]Life Sciences [q-bio]/Food engineeringStatisticsmedia_common.cataloged_instanceAnalysis of varianceEuropean unionComputingMilieux_MISCELLANEOUSFood ScienceDemographymedia_commonMathematicsFood Quality and Preference
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Uses of change-over designs and repeated measurements in sensory and consumer studies

1993

Abstract The paper illustrates two statistical methods, the design and analysis of sensory experiments taking into account the effects of serving order and previously assessed treatment and the analysis of experiments with time repeated measurements. Change-over design experiments balance both presentation order and carry-over effects. The proper analysis of variance allows the testing of these effects and the estimation of product means adjusted for carry-over effect. Repeated measurements occur when groups are being compared over time. Either a corrected split-plot or a multivariate analysis of variance (MANOVA) with measurements at different times forming the variable should be adopted t…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsSensory system04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysis03 medical and health sciencesVariable (computer science)0404 agricultural biotechnologyMultivariate analysis of varianceStatistics[SDV.IDA]Life Sciences [q-bio]/Food engineeringGroup effectMain effectAnalysis of variancePsychologyComputingMilieux_MISCELLANEOUSFood ScienceBalance (ability)
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Sensory methodologies and the taste of water

2009

/WOS: 000285178000010; International audience; Describing the taste of water is a challenge since drinking water is supposed to have almost no taste. In this study, different classical sensory methodologies have been applied in order to assess sensory characteristics of water and have been compared: sensory profiling, Temporal Dominance of Sensations and free sorting task. These methodologies present drawbacks: sensory profile and TDS do not provide an effective discrimination of the taste of water and the free sorting task is efficient but does not enable data aggregation. A new methodology based on comparison with a set of references and named “Polarized Sensory Positioning” (PSP) has bee…

030309 nutrition & dieteticsComputer science[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionSensory systemSensory profileMachine learningcomputer.software_genreSensory analysissensory analysis03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringProfiling (information science)0303 health sciencesCommunicationNutrition and Dieteticsbusiness.industrydrinking water[ SDV.IDA ] Life Sciences [q-bio]/Food engineering04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceData aggregatorArtificial intelligencebusinesscomputerpolarized sensory positioning[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood Science
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Salt and Aroma Compound Distributions Influence Flavour Release and Temporal Perception While Eating Hot-Served Flans.

2021

International audience; To counteract the negative effect of salt overconsumption on health, strategies have been developed to reduce the salt content in food products. Among them, two promising strategies based on odour-induced saltiness enhancement and the heterogeneous distribution of flavour compounds were combined and assessed in four-layer cream-based snacks. To investigate the relationship between saltiness enhancement, temporal release and perception of flavour compounds in hot snacks with heterogeneous distribution of salt and aroma compounds, complementary techniques were used: nose space PTR-Tof-MS (Proton Transfer Reaction-Time of Flight–Mass Spectrometry) to assess the release …

030309 nutrition & dieteticsFood HandlingFlavourPharmaceutical ScienceMass SpectrometryAnalytical Chemistrychemistry.chemical_compoundDrug DiscoveryAroma compoundsaltFood science2. Zero hungerchemistry.chemical_classification0303 health sciencesbiologyspatial distributionfood and beveragesTaste Perception04 agricultural and veterinary sciences040401 food scienceTaste intensitytemporal dominance of sensationsChemistry (miscellaneous)TasteMolecular MedicineSalt (chemistry)alternate time intensityArticlelcsh:QD241-44103 medical and health sciences0404 agricultural biotechnologylcsh:Organic chemistryHumansPhysical and Theoretical ChemistrySodium Chloride DietaryAromaflavour releaseOrganic Chemistrybiology.organism_classificationFlavoring AgentschemistryaromaFood productsOdorantsSaltsSalty tastedescriptive sensory analysisTemporal perception[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood AnalysisMolecules (Basel, Switzerland)
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