基于矿质元素指纹分析技术的烟叶产区判别

目的:探讨应用矿质元素指纹分析技术进行烟叶产区判别的可行性，筛选出可判别烟叶产区的有效指标，构建烟叶产区判别模型。方法:利用电感耦合等离子体—质谱法(ICP-MS)同时测定11个产地烟叶20种矿质元素含量，并对数据进行方差分析、聚类分析、主成分分析及判别分析。结果:16种元素含量在产地间差异显著，主成分分析得到6个主成分，其累计方差贡献率超过89%;应用逐步判别筛选出K、Mn、Se及Ba 4种元素指标，建立了西南烟区和长江中上游烟区的烟叶产区判别模型，该模型可对烟叶产区进行准确判别。结论:不同产地烟叶矿质元素含量差异显著，K、Mn、Se及Ba 4种元素是烟叶产区判别的重要指标，矿质元素指纹分析技术可用于烟叶产区判别。

Producing area discrimination of tobacco leaves based on mineral element fingerprinting technology

Objective: This paper discusses the feasibility of using mineral element fingerprinting technology of to identify tobacco producing areas, screens out the effective indicators, and constructs the discrimination model of tobacco producing areas. Methods: The contents of 20 mineral elements in tobacco leaves from 11 producing areas were simultaneously determined by ICP-MS, and the data were analyzed by variance analysis, cluster analysis, principal component analysis and discriminant analysis. Results: The contents of 16 elements were significantly different among producing areas, and principal component analysis resulted in 6 principal components, with the cumulative variance contribution of 89.253%. Using linear discriminant analysis, four elementsmineral, K, Mn, Se and Ba, were screened as the effective indicators to discriminate the geographical origin of tobacco leaves. The established discriminant model could accurately distinguish tobacco leaf samples from different tobacco producing areas. Conclusion: Significant differences were showed in the contents of mineral elements in tobacco leaves from 11 producing areas. Four elements, K, Mn, Se and Ba, are important indicators for distinguishing tobacco producing areas. Mineral element fingerprinting technology can be used for distinguishing tobacco producing areas.