Dataset of verbal evaluation of umami taste in Europe

التفاصيل البيبلوغرافية
العنوان: Dataset of verbal evaluation of umami taste in Europe
المؤلفون: Maria Paola Cecchini, Thomas Hummel, Antti Knaapila, Emilia Iannilli
المساهمون: Department of Food and Nutrition, Food Sciences, Senses and Food
المصدر: Data in Brief
بيانات النشر: Elsevier, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Bar chart, media_common.quotation_subject, Salt, Umami perception, Class (philosophy), Umami, computer.software_genre, law.invention, German, 03 medical and health sciences, 0302 clinical medicine, Flavors, law, familiarity, flavors, food palatability, glutamate, salt, synergism, taste, umami perception, Research article, Food palatability, 030304 developmental biology, media_common, 0303 health sciences, Multidisciplinary, business.industry, Taste (sociology), Synergism, Familiarity, language.human_language, 416 Food Science, Taste, language, Artificial intelligence, Glutamate, Psychology, business, computer, 030217 neurology & neurosurgery, Natural language processing, Neuroscience
الوصف: The data presented here includes verbal descriptors used by Finnish, German and Italian subjects to express the quality of an umami taste solution offered in a blind fashion. The dataset refers to the research article “A cross-cultural survey of Umami Familiarity in European Countries” [1]. Data shows that a total of 106 different classes of words, including synonyms, were used by the Finnish group, 64 different classes of words, including synonyms, were used by the German group, and a total of 70 different classes of words, including synonyms, were used by the Italian group. The descriptors are reported in Excel tables and visualized in a bar graph where the length of the bars indicates the number of given answers for each class.
اللغة: English
تدمد: 2352-3409
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79eb561c646db6586867dae41f5174ec
http://europepmc.org/articles/PMC6961172
Rights: OPEN
رقم الانضمام: edsair.doi.dedup.....79eb561c646db6586867dae41f5174ec
قاعدة البيانات: OpenAIRE