食品科学

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紫外光谱结合欧氏距离和主成分分析法快速鉴别牛肝菌

杨天伟1,李 涛2,张 霁3,李杰庆1,刘鸿高1,王元忠3,*   

  1. 1.云南农业大学农学与生物技术学院,云南 昆明 650201;2.玉溪师范学院资源环境学院,云南 玉溪 653100;
    3.云南省农业科学院药用植物研究所,云南 昆明 650223
  • 出版日期:2014-08-25 发布日期:2014-08-25
  • 通讯作者: 王元忠
  • 基金资助:

    国家自然科学基金地区科学基金项目(31260496;31160409);云南省自然科学基金项目(2011FB053;2011FZ195)

Rapid Identification of Bolete Mushrooms by UV Spectroscopy Combined with Euclidean Distance and Principal Component Analysis

YANG Tian-wei1, LI Tao2, ZHANG Ji3, LI Jie-qing1, LIU Hong-gao1, WANG Yuan-zhong3,*   

  1. 1. College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, China;
    2. College of Resources and Environment, Yuxi Normal University, Yuxi 653100, China;
    3. Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650223, China
  • Online:2014-08-25 Published:2014-08-25
  • Contact: WANG Yuan-zhong

摘要:

采用紫外光谱技术建立快速鉴别不同产地、种类食用牛肝菌的方法。通过确定最佳提取试剂(0.5 mol/LNaOH溶液),最适称样量(0.100 0 g)和最佳提取时间(40 min),制备牛肝菌样品测试液;采用夹角余弦、欧氏距离和主成分分析法对牛肝菌样品的指纹图谱进行相似度比较。结果表明,牛肝菌样品NaOH提取液在10 h内稳定性相对标准偏差(relative standard deviation,RSD)在0.06%~2.33%之间,重复性RSD在0.09%~1.81%之间,精密度RSD在0.11%~1.92%之间。样品间的夹角余弦值最大为0.999、最小为0.823,夹角余弦值相差较小,不适于鉴别牛肝菌。欧氏距离最大值为873.17,最小值为31.36,样品间距离差异明显;主成分分析的前3 个主成分累积贡献率达到93.626%,能够反映样品的主要信息,说明欧氏距离和主成分分析法可用于不同产地、种类牛肝菌的快速鉴别和质量控制。

关键词: 紫外光谱, 牛肝菌, 夹角余弦, 欧氏距离, 主成分分析, 鉴别

Abstract:

In this study, an ultraviolet (UV) spectroscopic method was established for rapid identification of different species
of bolete mushrooms from different areas. For preparation of boletes extracts, the optimal extraction extraction solvent,
sample amount and extraction time were determined as 0.5 mol/L NaOH, 0.100 0 g and 40 min, respectively. The similarity
of UV spectral fingerprint of bolete samples was analyzed by included angle cosine (IAC), Euclidean distance (ED) and
principal component analysis (PCA). The results showed that, within 10 h, the RSDs of stability, repeatability and accuracy
for bolete extracts were 0.06%–2.33%, 0.09%–1.81% and 0.11%–1.92%, respectively. The difference of IAC values among
samples was small, ranging from 0.823 to 0.999. But the difference of ED values among samples was large, ranging from
31.36 to 873.17. PCA showed that the cumulative contribution rate of the first three factors was 93.626%, which could
reflect most information about the samples. These findings suggested that the ED and PCA methods can be used for rapid
identification and quality control of different specices of boletes from different areas.

Key words: ultraviolet spectroscopy, bolete, included angle cosine, Euclidean distance, principal component analysis, identification

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