Norio Tominaga, Keisuke Sugimoto, Koji Takamura, Hiroshi Matsuura
{"title":"The Statistical Analysis About Taste Of Youth In Some Beverage","authors":"Norio Tominaga, Keisuke Sugimoto, Koji Takamura, Hiroshi Matsuura","doi":"10.1109/ICBIR52339.2021.9465840","DOIUrl":null,"url":null,"abstract":"Principal Component Analysis, or PCA, is a methods of reducing the dimensionality of a data set consisting of many variables such that most of the information in the data is preserved. We measured chemically sweetness, sourness, salt and umami contained in several commercially available tomato juices and identified the principal components of a four-dimensional data set consisting of them. In result, we found that the first component of the data set has strongly positive correlation with the total estimation of sensory test by young adults around twenty years of age.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 6th International Conference on Business and Industrial Research (ICBIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBIR52339.2021.9465840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Principal Component Analysis, or PCA, is a methods of reducing the dimensionality of a data set consisting of many variables such that most of the information in the data is preserved. We measured chemically sweetness, sourness, salt and umami contained in several commercially available tomato juices and identified the principal components of a four-dimensional data set consisting of them. In result, we found that the first component of the data set has strongly positive correlation with the total estimation of sensory test by young adults around twenty years of age.
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