• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>African Journal of Biotechnology >Rapid and non-destructive discrimination of tea varieties by near infrared diffuse reflection spectroscopy coupled with classification and regression trees
【24h】

Rapid and non-destructive discrimination of tea varieties by near infrared diffuse reflection spectroscopy coupled with classification and regression trees

机译：近红外漫反射光谱结合分类树和回归树对茶叶品种的快速无损鉴别

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The current study attempted to rapidly and non-destructively discriminate the diverse varieties of tea (that is, Biluochun, Longjing, Maojian, Qihong, Tieguanyin, and Yinzhen) via utilizing near infrared (NIR) diffuse reflectance spectroscopy coupled with pattern recognition strategies. Before the recognition analysis, the original NIR spectra were pre-processed by second derivative treatment followed by informative wavenumber interval location. And then, non-linearity detection and outlier diagnosis were performed. When pattern recognition referred, principal component analysis (PCA) was firstly applied to ascertain the discrimination possibility with the NIR spectra. Classification and regression trees (CART), compared with linear discriminant analysis (LDA), and partial squares-discriminant analysis (PLS-DA), was then employed for establishing the discrimination rule. Experimental results showed that the tea quality could be accurately, rapidly, and non-invasively identified via NIR spectroscopy coupled with CART.
机译：当前的研究试图通过利用近红外（NIR）漫反射光谱结合模式识别策略来快速，无损地区分茶的不同品种（即碧螺春，龙井，毛尖，旗红，铁观音和银镇）。在识别分析之前，先通过二阶导数处理对原始的近红外光谱进行预处理，然后再进行有意义的波数间隔定位。然后，进行非线性检测和异常诊断。当提到模式识别时，首先应用主成分分析（PCA）来确定具有近红外光谱的辨别可能性。然后，将分类和回归树（CART）与线性判别分析（LDA）和部分平方判别分析（PLS-DA）进行比较，以建立判别规则。实验结果表明，通过NIR光谱法和CART可以准确，快速且无创地鉴定茶叶质量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号