Search results for "030309 nutrition & dietetics"

showing 10 items of 404 documents

On the consistency of liking scores : insights from a study including 917 consumers from 10 to 80 years old

2004

Preference for 7 orange juices was recorded monadically. Three of the samples were replicates of the same juice (RJ). The 4 other samples were RJ slightly spiked with either sucrose, or citric acid, or quinine or an orange flavor. Each subject then performed a paired preference test composed of RJ and the modified juice whose score was the furthest from the RJ score. Finally, subjects were asked to choose one among 8 reasons why they preferred that sample. A number of individual statistics were computed in order to compare the consistency of liking scores within session, across ages and between genders. Women were slightly more consistent than men. However, no significant effect of age nor …

0303 health sciencesNutrition and Dietetics030309 nutrition & dietetics04 agricultural and veterinary sciencesOrange (colour)[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceOrange Flavor03 medical and health sciences0404 agricultural biotechnologyPreference test[SDV.IDA]Life Sciences [q-bio]/Food engineeringPsychologySocial psychologyComputingMilieux_MISCELLANEOUSFood ScienceDemography
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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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Drivers of food waste reduction behaviour in the household context

2021

Studies on the drivers of household consumer engagement in various food waste reduction strategies have been limited. We thus address this gap by developing a research model that utilises two well-known theories, namely, the Theory of Interpersonal Behaviour (TIB) and the Comprehensive Model of Environmental Psychology (CMEP), to explain food waste reduction behaviour in household consumers. The model hypothesises positive associations between emotional, social, and cognitive factors and food waste reduction behaviour, as conceptualised using the 3Rs (reuse, reduce, and recycle). A total of 515 U.S. household consumers participated in the cross-sectional survey. The results suggest that emo…

0303 health sciencesNutrition and Dietetics030309 nutrition & dietetics:Samfunnsvitenskap: 200 [VDP]Sense of communityCognitionContext (language use)04 agricultural and veterinary sciencesInterpersonal communicationReuse040401 food sciencePeer reviewVDP::Samfunnsvitenskap: 200::Økonomi: 21003 medical and health sciencesFood waste0404 agricultural biotechnologyEnvironmental psychologyMarketingPsychologyFood Science
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Facilitators and inhibitors of organic food buying behavior

2021

Abstract Consumption patterns across the globe indicate consumers’ rising interest in purchasing organic food due to increasing personal-health consciousness. However, research on organic food shows a low translation of this interest into stated preferences for purchasing organic food. Limited academic research has explored this puzzling buying behavior of consumers, particularly in developed economies such as Japan. Our study addresses this gap by examining the factors that facilitate or inhibit Japanese consumers’ buying behavior toward organic food. We use the Stimulus-Organism-Response framework, Innovation Resistance Theory, and Dual-Factor Theory to examine these factors by analyzing …

0303 health sciencesNutrition and Dietetics030309 nutrition & dietetics:Samfunnsvitenskap: 200 [VDP]media_common.quotation_subjectNutritional contentdigestive oral and skin physiology04 agricultural and veterinary sciencesHealth consciousness040401 food sciencePurchasing03 medical and health sciences0404 agricultural biotechnologyFacilitatorVDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470ConsciousnessMarketingPsychologyWelfareFood Sciencemedia_commonFood Quality and Preference
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Impact of the information provided to consumers on their willingness to pay for Champagne : comparison with hedonic scores

2002

International audience; L'étude a été effectuée afin de comparer deux mécanismes destinés à révéler les préférences des consommateurs : une enchère Vickrey qui mesure la disposition à payer, et un test hédonique classique. A travers ces deux méthodes, l'objectif était d'estimer les effets respectifs des caractéristiques sensorielles et de l'information externe sur l'évaluation de cinq champagnes brut non millésimés. Cent-ving-trois consommateurs ont été assignés au hasard aux deux groupes et ont utilisé l'une des méthodes. Quelle que soit la méthode, ils ont évalué les champagnes à l'aveugle, puis sur la base d'une présentation des bouteilles et, enfin, après l'observation de la bouteille e…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsANALYSE DES DONNEESAdvertising04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceTest (assessment)03 medical and health sciences0404 agricultural biotechnologyWillingness to payOrder (business)INFORMATION DU CONSOMMATEUR[SDV.IDA]Life Sciences [q-bio]/Food engineeringVickrey auctionConsommation distribution et transformationWine tastingPsychologySocial psychologyConsumer behaviourAnalysis methodFood Science
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[Qualité attendue contre qualité perçue : arbitrage avec les prix]

2000

International audience; Cet article rend compte d'une étude menée afin de comparer le comportement des consommateurs qui doivent choisir des produits sous contrainte économique, selon deux conditions différentes : quand la qualité perçue est basée sur une attente générée par des images fabriquées et, à l'inverse, quand la qualité perçue est basée sur l'expérience sensorielle en présence d'images fabriquées. Les participants de l'expérience ont été choisis au hasard, dotés d'un budget réel et placés dans cinq situations différentes de prix/budget. Ils ont formulé leurs choix parmi six jus d'orange dans chaque situation prix/budget. Ce travail a été réalisé pour les deux conditions différente…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsAdvertising04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering16. Peace & justiceTrade-off040401 food science03 medical and health sciencesPerceived qualityChose0404 agricultural biotechnologyINFORMATION DU CONSOMMATEUR[SDV.IDA]Life Sciences [q-bio]/Food engineeringConsommation distribution et transformationWine tastingPsychologyFood ScienceFood Quality and Preference
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Risk tables for discrimination tests

1993

Abstract Duo-trio and triangle test are often used in the food industry for the purpose of declaring two products non-distinguishable. In that situation, it is much more important to control the power of the test rather than the type 1 error risk. This paper makes available by e-mail a SAS ® macro, called BINRISKS, for computing type 1 and type 2 risks for any one-tailed binomial test and for any level of the percentage above chance to be detected. Using this macro, two sets of tables have been compiled. The first table includes for any total number of responses below 50, for any number of correct responses and for three levels of the percentage above chance to be detected, the correspondin…

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsBinomial test04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceDiscrimination testingTest (assessment)03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringStatisticsEconometricsTable (database)MacroComputingMilieux_MISCELLANEOUSFood ScienceTriangle testMathematicsType I and type II errorsFood Quality and Preference
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Problems in time-intensity measurements. A case study-Bitterness evaluation in water solutions and in beers

1992

International audience

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsChemistryAnalytical chemistry04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceComputational physics03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringTime intensityComputingMilieux_MISCELLANEOUSFood Science
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Comments from Pascal Schlich on the Steinsholt's paper

1998

International audience

0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsComputer scienceProgramming languageVARIANT04 agricultural and veterinary sciencesPascal (programming language)[SDV.IDA] Life Sciences [q-bio]/Food engineeringcomputer.software_genre040401 food science03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringcomputerComputingMilieux_MISCELLANEOUSFood Sciencecomputer.programming_language
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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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