基于神经网络的菠萝香气成分色谱保留值研究  

Quantitative structure-retention relationship studies of aroma components from pineapple based on neural network

作　　者：秦正龙 冯长君[2] QIN Zheng-long;FENG Chang-jun(College of Chemistry and Materials Science,Jiangsu Normal University,Xuzhou,Jiangsu 221116,China;College of Chemistry&Chemical Engineering,Xuzhou Institute of Technology,Xuzhou,Jiangsu 221008,China)

机构地区：[1]江苏师范大学化学与材料科学学院,江苏徐州221116 [2]徐州工程学院化学化工学院,江苏徐州221008

出　　处：《食品与机械》2021年第1期30-33,155,共5页Food and Machinery

基　　金：国家自然科学基金资助项目(编号:21075138);江苏省高校品牌专业建设工程资助项目(编号:PPZY201992)。

摘　　要：为了研究菠萝香气成分色谱保留时间与其结构之间的定量构效关系,在分子拓扑理论基础上,计算了44种菠萝香气成分的分子价连接指数(mXtV)、分子形状指数(nK)和电拓扑状态指数(Ei)。优化筛选了分子价连接性指数2XVp和4XcV、分子形状指数1K和2K、电拓扑状态指数的E8和E13共6个参数,将其作为BP神经网络的输入层变量,香气成分的色谱保留时间作为输出层变量,采用6∶3∶1的网络结构,获得了令人满意的QSRR神经网络预测模型,模型总相关系数为0.995,计算得到的色谱保留时间的预测值与试验值吻合较好。结果表明,菠萝香气成分色谱保留时间与6种结构参数之间呈现良好的非线性关系,模型能较好地揭示香气成分色谱保留时间的递变规律。In order to study chromatographic retention time(RT)of aroma components from pineapple,molecular valence connectivity index(mXtV),molecular shape index(nK)and electrotopological state index(Ei)of 44 aroma components were calculated.2XpV and 4XcV of the molecular valence connectivity indices,and 1K and 2K of the molecular shape indices,E8 and E13 of the electrotopological state indices were optimized. The six parameters were used as input variables of neural network and the chromatographic retention time was used as output variable,and the 6∶3∶1 network structure was adopted and BP neural network method was used to establish a satisfying QSRR prediction model.The total correlation coefficient was 0.995.The predicted values by the model were in agreement those of the experiment values.A good nonlinear relationship between the chromatographic retention time and the six molecular structure parameters was found.The model could better elucidate the changing rule of chromatography retention time of the aroma components.

关 键 词：菠萝 香气成分 分子拓扑参数 定量结构—色谱保留关系 神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TS255.7[自动化与计算机技术—控制科学与工程]