摘要
为了考察烤烟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0.396 7、0.403 4和0.352 1,与游离氨基酸中的半胱氨酸、谷氨酸、精氨酸MIC也分别达0.388 7、0.326 3和0.353 7,含氮化合物含量显著影响烟气氢氰酸的释放量。
To explore the relationship between HCN yields in smoke stream and main nitrogen compounds in flue-cured tobacco leaf, 60 samples were selected from main tobacco-planting areas in China. The new machine learning algorithm named MINE（maximal information-based nonparametric exploration） was used to study the relationship between the HCN and the main nitrogen compounds. The results showed that HCN yields in smoke stream exhibited close relationship with nitrogen compounds, the relationship strength（MIC） with protein, nicotine and total content of amino acid reached 0.396 7,0.403 4 and 0.352 1, respectively; and the MIC with cysteine, glutamic acid and arginine reached 0.388 7,0.326 3 and 0.353 7, respectively; indicating these nitrogen compounds significantly influence the HCN yields in smoke stream.
出处
《湖南农业大学学报（自然科学版）》
CAS
CSCD
北大核心
2015年第5期496-502,共7页
Journal of Hunan Agricultural University(Natural Sciences)
基金
安徽中烟工业有限责任公司项目(20121006)
关键词
烤烟
氢氰酸
含氮化合物
MINE
flue-cured tobacco
HCN
nitrogen components
maximal information based nonparametric exploration（MINE）
