In this paper, a non-destructive and efficient method for identifying gemstones of the same species based on Raman spectroscopy and pattern recognition algorithms was developed. Tianhuang stones from different origins (Shoushan (SS), Changhua (CH), and Laos (LA)) with similar composition and structure were investigated and analyzed. Raman spectra were collected by a self-developed portable Raman spectrometer. Combined with pattern recognition methods, the subtle differences between the three types of Tianhuang stones were comprehensively analyzed. Principal component analysis–latent Dirichlet allocation was used to predict the feasibility of distinguishing SS, CH, and LA Tianhuang stones by Raman spectra. Random forest analysis method was applied to establish SS/CH and SS/LA models to distinguish SS from CH and LA. The selection of characteristic variables and determination of the number of growing trees was discussed. Also, the accuracy, sensitivity, and specificity of the two models were calculated. The potential of this method for rapid and non-destructive identification of Tianhuang stones was proved. The feasibility and effectiveness of Raman spectroscopy combined with the pattern recognition method in identifying gemstones of the same species with similar composition were proved.

中文翻译：

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基于拉曼光谱和模式识别算法的田黄石产地鉴定

本文提出了一种基于拉曼光谱和模式识别算法的无损、高效的同种宝石鉴别方法。研究分析了具有相似成分和结构的不同产地（寿山 (SS)、彰化 (CH) 和老挝 (LA)）的田黄石。拉曼光谱由自主研发的便携式拉曼光谱仪采集。结合模式识别方法，综合分析了三种田黄石的细微差别。主成分分析-潜在狄利克雷分配用于预测通过拉曼光谱区分 SS、CH 和 LA 田黄石的可行性。应用随机森林分析方法建立SS/CH和SS/LA模型以区分SS与CH和LA。讨论了特征变量的选取和生长树数的确定。此外，还计算了两个模型的准确性、灵敏度和特异性。证明了该方法对田黄石进行快速无损鉴定的潜力。证明了拉曼光谱结合模式识别方法鉴别同种成分相近宝石的可行性和有效性。