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中国精品科技期刊2020
郑艳艳, 吴雪辉. 掺伪茶油的化学模式识别方法研究[J]. 食品工业科技, 2014, (07): 115-118. DOI: 10.13386/j.issn1002-0306.2014.07.020
引用本文: 郑艳艳, 吴雪辉. 掺伪茶油的化学模式识别方法研究[J]. 食品工业科技, 2014, (07): 115-118. DOI: 10.13386/j.issn1002-0306.2014.07.020
ZHENG Yan-yan, WU Xue-hui. Study on chemical pattern recognition of camellia oil adulteration[J]. Science and Technology of Food Industry, 2014, (07): 115-118. DOI: 10.13386/j.issn1002-0306.2014.07.020
Citation: ZHENG Yan-yan, WU Xue-hui. Study on chemical pattern recognition of camellia oil adulteration[J]. Science and Technology of Food Industry, 2014, (07): 115-118. DOI: 10.13386/j.issn1002-0306.2014.07.020

掺伪茶油的化学模式识别方法研究

Study on chemical pattern recognition of camellia oil adulteration

  • 摘要: 为研究掺伪茶油的定性鉴别方法,选取折光率、碘值、皂化值、色泽和酸价等5个理化指标作为变量,对31个茶油掺菜籽油、大豆油、米糠油、玉米油和棕榈油的样品进行测定。采用主成分分析和判别分析两种方法处理数据。结果表明,主成分分析中,样品前三个主成分的累计贡献率为95.55%,已含样本的大部分信息,前三个主成分构成的三维得分图(PC1-PC2-PC3)显示,31个样品在三维空间内按照掺伪种类的不同被分为5个区域,从而对油样进行识别。通过判别分析方法推测单一样品属于各个掺伪总体的概率,可实现掺伪茶油中掺杂其它植物油的鉴别,准确率达97%。 

     

    Abstract: 31 samples of camellia oil adulterated with rapeseed oil, soybean oil, rice bran oil, corn oil and palm oil were prepared to measure their physicochemical properties, such as refractive index, iodine value, saponification value, color and acid value.Principal component analysis and discriminant analysis were used to processing the test data. According to the results, the cumulative contribution efficiency of the first three principal components accounts for 95.55%, including almost all information of the samples. From the three-dimensional score ( PC1-PC2-PC3) composed of the first three principal components, it was obvious that the 31 samples could be divided into five groups based on adulteration category.By discriminant analysis, the probability of a sample belonged to the different population was calculated, in order to predict the adulteration species of camellia oil adulteration, the accuracy rate was 97%.

     

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