食品科学 ›› 2019, Vol. 40 ›› Issue (16): 213-219.doi: 10.7506/spkx1002-6630-20181008-029

• 成分分析 • 上一篇    下一篇

基于无机元素的花椒产地溯源和品种聚类分析

吴 振,李 红,杨 勇,谭红军,詹 永,贾凤霞,李孝彬,王福强   

  1. 1.重庆市中药研究院,中药健康学重庆市重点实验室,重庆 400065;2.重庆市食品药品检验检测研究院,重庆 401121;3.重庆市中药大健康工程技术研究中心,重庆 400065;4.四川省广元市旺苍县农业局,四川 广元 628200
  • 出版日期:2019-08-25 发布日期:2019-08-26
  • 基金资助:
    重庆市集成示范计划项目(cstc2015jcsf-kjfp80014);重庆市重点产业共性关键技术创新专项(csct2017zdcy-zdyfX0013)

Geographical Origin Traceability and Varietal Classification of Zanthoxylum Based on Mineral Profile

WU Zhen, LI Hong, YANG Yong, TAN Hongjun, ZHAN Yong, JIA Fengxia, LI Xiaobin, WANG Fuqiang   

  1. 1. Chongqing Academy of Chinese Materia Medica, Chongqing Key Laboratory of Chinese Medicine and Health Science, Chongqing 400065, China; 2. Chongqing Institute for Food and Drug Control, Chongqing 401121, China; 3. Chongqing Engineering Technology Research Center of Materia Medica Health, Chongqing 400065, China; 4. Agricultural Bureau of Wangcang County, Guangyuan 628200, China
  • Online:2019-08-25 Published:2019-08-26

摘要: 采用电感耦合等离子体原子发射光谱法,对红花椒(陕西韩城、四川汉源、四川茂汶、甘肃武都)和青花椒(云南昭通、贵州关岭、四川金阳、四川汉源、重庆江津)9 大主产地的80 个样品中21 个无机元素含量进行测定。采用主成分分析(principal component analysis,PCA)和偏最小二乘判别分析(partial least squaresdiscrimination analysis,PLS-DA)对红花椒和青花椒中无机元素进行综合评价,PCA和PLS-DA将80 个花椒聚为9组,PLS-DA分类效果更佳,并能将红花椒和青花椒有效区分,从元素组成角度揭示了红花椒和青花椒的亲缘关系和地域分布特征。研究证明多元素分析结合PLS-DA可作为一种花椒品种和产地识别的有效工具,对于产地溯源和品种鉴定具有重要意义。

关键词: 红花椒, 青花椒, 元素, 偏最小二乘判别分析, 品种, 产地

Abstract: The concentrations of 21 mineral elements (Al, B, Ba, Ca, Cd, Co, Cu, Na, K, Fe, Mg, Mn, Zn, Ni, Pb, As, Se, Hg, Cr, V and Sr) of 80 Zanthoxylum samples collected from 9 main producing regions in China (Z. bungeanum Maxim: Hancheng in Shaanxi, Hanyuan in Sichuan, Maowen in Sichuan and Wudu in Gansu; Z. schinifolium Sieb. et Zucc: Zhaotong in Yunnan, Guanling in Guizhou, Jinyang in Sichuan, Hanyuan in Sichuan, and Jiangjin in Chongqing) were determined by principal component analysis (PCA) and partial least squares-discrimination analysis (PLS-DA) were used to analyze the data obtained. The 80 samples were classified into nine groups by PCA and PLS-DA, agreeing with the actual grouping. The classification ability of PLS-DA was better than that of PCA and could effectively distinguish between Z. bungeanum Maxim. and Z. schinifolium Sieb. et Zucc. This study demonstrated that the combination of multi-element analysis and PLSDA can be an effective tool for identifying the geographical origin and variety of Zanthoxylum.

Key words: Zanthoxylum bungeanum Maxim., Zanthoxylum schinifolium Sieb. et Zucc., element, partial least squaresdiscrimination analysis, variety, geographical origin

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