基于HPLC指纹图谱技术的烤烟质量分类研究

为解决当前烤烟质量分类费时费力且主观偶然性强的问题，采用高效液相指纹图谱技术，对来自多个省份的典型烟叶产区共14批B2F下限等级烟叶进行图谱信息采集，并基于14批烟叶图谱进行主成分提取、相关性分析和聚类分析。选取前5个主成分进行分析。相关性分析表明，钾和主成分值之间呈极显著相关。聚类分析表明，来自多个省份典型烟叶产区的烟叶可大致分为3类。其中第1类样品与第2类样品的钾含量差异明显；第2类样品中氯的含量明显高于第1、3类样品。试验结果表明，烟叶的HPLC指纹图谱可以作为烟叶质量控制的新方法，此方法可以提高烟草品质判别效率，降低人工评价的个体差异。

Quality Classification of Flue-cured Tobacco Based on HPLC Fingerprint Technique

The paper aims to solve the problem of time-consuming and laborious quality classification of flue-cured tobacco. 14 batches of B2F lower limit grade tobacco leaves from typical tobacco leaf producing areas of multiple provinces were analyzed by HPLC fingerprinting technology. Meanwhile, principal component extraction, correlation analysis and cluster analysis were carried out. Based on the first five principal components, there was a significant correlation between potassium and principal component values. Cluster analysis showed that tobacco leaves could be roughly divided into three categories. The difference of potassium content between the first type and the second type of samples was obvious, while the contents of chlorine in the second type of samples were obviously higher than that in the first and third types of samples. The results showed that the HPLC fingerprint of tobacco leaves could be used as a new method for tobacco quality control, which could enhance the efficiency of tobacco quality classification, and reduce the individual differences from artificial evaluation.