食品科学 ›› 2012, Vol. 33 ›› Issue (17): 122-124.

• 基础研究 • 上一篇    下一篇

基于数据挖掘技术的光皮木瓜质量分析

石文   

  1. 陕西学前师范学院
  • 收稿日期:2012-04-23 修回日期:2012-08-30 出版日期:2012-09-15 发布日期:2012-11-09
  • 通讯作者: 石文 E-mail:guoguo_nan@163.com
  • 基金资助:

    陕西省科技厅经济发展研究项目(2008K02-11)

Quality Analysis of Chinese Quince (Chaenomeles sinensis Koehne) Based on Data Mining Technology

  • Received:2012-04-23 Revised:2012-08-30 Online:2012-09-15 Published:2012-11-09

摘要: 针对陕西省白河县不同地区的光皮木瓜采用高效液相色谱法(HPLC)建立的10个不同地区光皮木瓜指纹图谱进行研究,对所获得的数据信息进行数据化处理;分析样品的相似度,用聚类分析法对不同产地光皮木瓜样品进行分析和合理的归类,将其样品分为 3 类,建立了木瓜的指纹图谱共有模型,找出了较大的 11个共有峰。通过HPLC指纹图和聚类分析法,建立了控制光皮木瓜质量的新方法。

关键词: 聚类分析, 光皮木瓜, 质量评价

Abstract: Chinese quince fruits collected from 10 growing areas in Baihe County, Shaanxi Province were analyzed by HPLC to establish fingerprint profiles. The information obtained was analyzed by digital processing. The similarity of these samples was analyzed and the different growing areas were assigned by cluster analysis to three categories. Meanwhile, a general fingerprint profile model was proposed in which 11 common peaks were found. Therefore, combined HPLC fingerprinting and cluster analysis can provide a new analytical method for quality evaluation of Chinese quince.

Key words: cluster analysis, Chinese quince, quality evaluation

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