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Rapid Classification of Citrus Fruits Based on Raman Spectroscopy and Pattern Recognition Techniques

机译：基于拉曼光谱和模式识别技术的柑橘类水果快速分类

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摘要

Citrus fruits are major agricultural products of China and they are rich sources of health beneficial substances. In this study, Raman spectroscopy as a rapid and non-destructive tool was employed to classify eight different citrus fruits. Baseline drift caused by fluorescence of organic compounds in the citrus samples interferes with the Raman signals. A polynomial fitting based method was adopted for baseline correction, which is a key factor both for Raman peaks assignment and subsequent pattern recognition. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were the two selected pattern recognition techniques. PCA showed the distribution of sweet oranges and mandarins, and HCA was a useful guide for detailed relationship between various citrus samples. The results demonstrated that Raman spectroscopy combined with pattern recognition techniques has substantial potential for discriminating varieties of citrus fruits.
机译：柑橘类水果是中国的主要农产品，是健康有益物质的丰富来源。在这项研究中，拉曼光谱法是一种快速且无损的工具，用于对8种不同的柑橘类水果进行分类。柑橘样品中有机化合物的荧光引起的基线漂移会干扰拉曼信号。采用基于多项式拟合的方法进行基线校正，这是拉曼峰分配和后续模式识别的关键因素。主成分分析（PCA）和层次聚类分析（HCA）是选择的两种模式识别技术。 PCA显示了甜橙和橘子的分布，而HCA是了解各种柑橘样品之间详细关系的有用指南。结果表明，拉曼光谱法与模式识别技术相结合具有鉴别柑橘类水果的巨大潜力。

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