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基于MINE算法的烤烟含氮化合物与HCN关系分析
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摘要
为了考察烟气氢氰酸释放量与烟叶中主要含氮化合物的关系,采集全国主要植烟区域的60份烤烟样品,运用机器学习算法新方法 MINE对氢氰酸与主要含氮化合物之间的关系进行了分析。结果表明:烟气氢氰酸的释放量与烟叶中的含氮化合物关系最为密切,与蛋白质、烟碱、游离氨基酸总量MINE算法关系强度MIC分别达到了0.3967、0.4034和0.3521,与游离氨基酸中的半胱氨酸、谷氨酸、精氨酸MIC也分别达到了0.3887、0.3263和0.3537,这些含氮化合物含量显著影响烟气成分氢氰酸的释放量。
For the purpose to explore the relationship between HCN and main nitrogen compounds in flue-cured tobacco leaf, 60 samples were selected from main tobacco-planted areas in China. Some certain new machine learning algorithm named MINE(Maximal Information-based Nonparametric Exploration) had been carried out on R open source platform(statistic software). And some conclusions had been summarized from such analysis. The results showed that the main nitrogen compounds expressed highest strength relationship with the HCN yields judge MIC which was one of the core evaluation index. Such main nitrogen compounds included total nitrogen compounds, nicotine, protein and total content of amino acid in flue-cured tobacco leaf, their MIC were 0.3967,0.4034 and 0.3521. Meanwhile some kind of amino acid indicated much more important to the HCN yields, which included cys, arg and glu;their MIC were 0.3887,0.3263 and 0.3537.Such nitrogen compounds would influence HCN yields directly. In terms of this conclusion the proper nitrogen compounds contents should be focused on raw material recipe, DPM designation, even more such point could extend to the tobacco-planted course. By this way these measures would help to reduce the hazards of cigarettes.
引文
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