SIMCA模式识别方法在近红外光谱识别茶叶中的应用

茶叶快速准确识别方法研究是当前茶叶行业亟待解决的一项重大课题。本研究采用一种近红外光谱结合SIMCA模式识别方法对茶叶进行识别与分类。研究结果表明,选取6500～5300cm-1波长范围内的光谱,通过标准归一化(SNV)预处理后,利用SIMCA的模式识别方法分别为龙井、碧螺春、祁红和铁观音等四类茶叶建立了类模型。主成分数分别为4、5、2和3时,类模型对未知样本的识别效果最佳。在α=5%的显著性水平下,四类模型的对未知茶叶样本的识别率分别是90%、80%、100%和100%,拒绝率全是100%。本论文为快速准确识别茶叶提供了一种新思路。

Application of Near Infrared Reflectance Spectroscopy to the Identification of Tea Using SIMCA Pattern Recognition Method

It is an urgent affair to think up a quick and precise method in the identification of tea varieties. A rapid tea identification method by near infrared reflectance spectroscopy coupled with pattern recognition based on SIMCA was proposed in this paper. In the spectra region between 6500cm-1 and 5300cm-1, four predictive models of Longjing tea, Biluochun tea, Qihong tea and Tieguanyin tea were built separately by the standard normal variate (SNV) preprocessing method with SIMCA pattern recognition method. The results showed that four models are the best when 4, 5, 2 and 3 principal components were used separately in building models. Under theα=5% significance level, the identification rates of four models for the unknown samples are 90%, 80%, 100% and 100% in turn by means of NIR wave lengths, while, the rejection rates of four models are all 100%. A new idea by the quick and precise identification of tea was offered in this paper.