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作者中文名	作者英文名	单位中文名	单位英文名	E-Mail
刘征辉	LIU Zheng-hui	天津市农业质量标准与检测技术研究所，天津300381	Tianjin Agricultural Quality Standards and Testing Technology Research Institute，Tianjin 300081，China
魏静娜	WEI Jing-na	天津海世达检测技术有限公司，天津300381	Tianjin High-standard Quality Testing Lab.，Tianjin 300081，China
赵琳琳	ZHAO Lin-lin	天津海世达检测技术有限公司，天津300381	Tianjin High-standard Quality Testing Lab.，Tianjin 300081，China
赵云平	ZHAO Yun-ping	天津海世达检测技术有限公司，天津300381	Tianjin High-standard Quality Testing Lab.，Tianjin 300081，China
薛天凯	XUE Tian-kai	天津市农业质量标准与检测技术研究所，天津300381	Tianjin Agricultural Quality Standards and Testing Technology Research Institute，Tianjin 300081，China
黄迪	HUANG Di	天津市农业质量标准与检测技术研究所，天津300381	Tianjin Agricultural Quality Standards and Testing Technology Research Institute，Tianjin 300081，China
郭永泽	GUO Yong-ze	天津市农业质量标准与检测技术研究所，天津300381	Tianjin Agricultural Quality Standards and Testing Technology Research Institute，Tianjin 300081，China
程奕	CHENG Yi	天津市农业质量标准与检测技术研究所，天津300381	Tianjin Agricultural Quality Standards and Testing Technology Research Institute，Tianjin 300081，China	程奕，研究员，研究方向：中药、农产品、土壤肥料等评价研究；Tel：(022)23678678，E-mail：cychengyi99@126.com

基金项目:2018年天津市重点研发专项京津冀三地协同创新研发项目（18YFSDZC00020）

中文摘要:目的：通过近红外光谱技术研究金银花和山银花在真伪鉴别中的应用。方法：本研究利用近红外光谱方法识别金银花和山银花的差异性，通过收集来自不同产地的101种金银花和山银花样品，采用近红外光谱选择5300～5550、6900～7500、8200～12 000 cm-1处光谱波段进行标准化预处理后，在主成分分析的聚类基础上通过SIMCA模式识别原理对金银花和山银花分别建立了类模型。结果：模型基本能正确识别金银花和山银花，所建立的方法可靠、快速简单，可作为金银花真伪判别的一种有效控制方法。结论：近红外光谱结合SIMCA模式识别在金银花和山银花分类识别具有可行性。

中文关键词:近红外光谱金银花山银花主成分分析 SIMCA模式识别真伪判别

Application of Near Infrared Spectroscopy in Identification of Lonicerae Japonicae Flos and Lonicerae Flos

Abstract:Objective：To study the application of Lonicerae Japonicae Flos and Lonicerae Flos in the identification of authenticity by near-infrared spectroscopy.Methods：The differences between Lonicerae Japonicae Flos and Lonicerae Flos were detected identified by near-infrared spectroscopy at 5300-5550，6900-7500，8200-12 000 cm-1，101 samples collected from different regions were detected，and after standardization preprocessing in the spectral band，based on the clustering of principal component analysis，a class model was established for Lonicerae Japonicae Flos and Lonicerae Flos by SIMCA pattern recognition principle.Results：The model correctly identified Lonicerae Japonicae Flos and Lonicerae Flos，the established method is reliable，fast and simple，and can be used as the control method for the authenticity of Lonicerae Japonicae Flos.Conclusion：Near-infrared spectroscopy combined with SIMCA pattern recognition method is feasible in the classification and identification of Lonicerae Japonicae Flos and Lonicerae Flos.

keywords:Near-infrared spectroscopy Lonicerae Japonicae Flos Lonicerae Flos principal component analysis SIMCA pattern recognition authenticity discrimination

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