| 基于决策树方法的油炸型方便面品质评价研究 |
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| 引用本文： | 欧阳一非,薛丹,高海燕,赵镭,候国友,米军峰,尹京苑. 基于决策树方法的油炸型方便面品质评价研究[J]. 食品科学, 2009, 30(5): 27. DOI: 10.7506/spkx1002-6630-200905005 |
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| 作者姓名： | 欧阳一非 薛丹 高海燕 赵镭 候国友 米军峰 尹京苑 |
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| 作者单位： | 上海大学生命科学学院;中国食品工业(集团)公司;中国标准化研究院食品与农业标准化研究所;今麦郎食品有限公司食品安全研究所; |
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| 基金项目： | “十一五”国家科技支撑计划项目(2006BAK04A05); 上海大学2007年度研究生创新基金项目(2007) |
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| 摘 要： | 本实验以市场占有率为80%～90%的国内主要方便面生产厂家的12个主打品牌的205个油炸型方便面样品为研究对象,首先以8个专家感官评价项目为指标,采用K-均值法对感官品评数据进行了聚类分析;根据聚类分析结果再应用决策树分析方法,以15个物性检测项目为指标,建立感官品评和面条物性指标之间关系模型。结果表明,所建立的决策树模型吻合感官品评聚类结果的精度达到95.61%,实现了表达仪器测量值与感官品评之间关系的目的,可为油炸型方便面品质评价提供一种客观定量化的方法。
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| 关 键 词： | 方便面 感官分析 数据挖掘 决策树 |
Study on Evaluation of Fried Instant Noodle Quality Using Decision Tree |
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| OUYANG Yi-fei,,XUE Dan,GAO Hai-yan,ZHAO Lei,HOU Guo-you,MI Jun-feng,YIN Jing-yuan, Corporation,Beijing ,.Food , Agricultural St,ardization Institute,China St,ardization Institute,Beijing ,.Food Safety Research Institute,Jinmailang Food Corporation,Xingtai ,China ). Study on Evaluation of Fried Instant Noodle Quality Using Decision Tree[J]. Food Science, 2009, 30(5): 27. DOI: 10.7506/spkx1002-6630-200905005 |
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| Authors: | OUYANG Yi-fei XUE Dan GAO Hai-yan ZHAO Lei HOU Guo-you MI Jun-feng YIN Jing-yuan Corporation Beijing .Food Agricultural St ardization Institute China St ardization Institute Beijing .Food Safety Research Institute Jinmailang Food Corporation Xingtai China ) |
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| Affiliation: | OUYANG Yi-fei1,2,XUE Dan1,GAO Hai-yan1,ZHAO Lei3,HOU Guo-you4,MI Jun-feng4,YIN Jing-yuan1,(1.College of Life Sciences,Shanghai University,Shanghai 200444,China,2.China National Food Industry (Group) Corporation,Beijing 100062,3.Food and Agricultural Standardization Institute,China Standardization Institute,Beijing 100088,4.Food Safety Research Institute,Jinmailang Food Corporation,Xingtai 055350,China ) |
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| Abstract: | In this study, 205 samples of fried instant noodles from 12 main brands, which occupy 80% to 90% market in mainland China, were collected to explore a new thinking for evaluating the quality of fried instant noodles. At the first stage, K-mean algorithm was applied to analyze sensory evaluation scores of eight sensory evsory evaluation indexes. Secondly, based on the results of clustering analysis at the first stage, a model of quality evaluation with fifteen physical indexes was built by means of decision ... |
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| Keywords: | instant noodle sensory analysis data mining decision tree |
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