In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular simil...In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps and Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.展开更多
以清香型汾酒为研究对象,采用气相色谱/质谱联用方法,分析了汾酒中的主要香味成分,利用Steric and Electronic Descriptors(SEDs)建立了预测香味成分的定量结构-色谱保留相关模型,发现汾酒中主要香味成分酯、醇、酸、醚、烃、醛、酮的...以清香型汾酒为研究对象,采用气相色谱/质谱联用方法,分析了汾酒中的主要香味成分,利用Steric and Electronic Descriptors(SEDs)建立了预测香味成分的定量结构-色谱保留相关模型,发现汾酒中主要香味成分酯、醇、酸、醚、烃、醛、酮的保留时间分别与不同的SEDs参数有良好的相关性,建模相关系数分别为酯R=0.991、醇R=0.995、酸R=0.995、醚和烃R=0.995、醛酮R=0.969,留一法交互检验(Leave-one-out,Loo)相关系数分别为酯RLoo=0.986、醇RLoo=0.986、酸RLoo=0.991、醚和烃RLoo=0.944、醛酮RLoo=0.932。结果表明,所建模型具有良好的稳定性和预测能力,为白酒中香味成分的分离检测提供了有效的理论依据。展开更多
目的建立预测中草药挥发油成分保留指数的定量结构-色谱保留相关模型。方法以金银花挥发油为研究对象,用Steric and Electronic Descriptors(SEDs)参数表征其分子结构,采用SPSS进行逐步回归分析,建立相关模型,并用留一法对模型交互检验...目的建立预测中草药挥发油成分保留指数的定量结构-色谱保留相关模型。方法以金银花挥发油为研究对象,用Steric and Electronic Descriptors(SEDs)参数表征其分子结构,采用SPSS进行逐步回归分析,建立相关模型,并用留一法对模型交互检验评价模型的预测能力和稳定性。结果金银花挥发油成分的保留指数与建模时筛选的SEDs参数有良好的相关性,建模相关系数均大于0.907;留一法交互检验相关系数与建模相关系数接近,均大于0.896。结论所建模型具有良好的稳定性和预测能力,为中草药挥发油成分的分离检测提供有效的理论依据。展开更多
文摘In this article, generalized torsion angles of derivatives of 1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine(HEPT) were calculated, which include abundant three dimensional information of molecules. Molecular similarity matrix was built based on the calculated generalized torsion angles. These similarities were taken as the new variables, and the new variables were selected by using Leaps and Bounds regression analysis. Multiple regression analysis and neural networks were performed, and the satisfactory results were achieved by using the neural networks.
文摘以清香型汾酒为研究对象,采用气相色谱/质谱联用方法,分析了汾酒中的主要香味成分,利用Steric and Electronic Descriptors(SEDs)建立了预测香味成分的定量结构-色谱保留相关模型,发现汾酒中主要香味成分酯、醇、酸、醚、烃、醛、酮的保留时间分别与不同的SEDs参数有良好的相关性,建模相关系数分别为酯R=0.991、醇R=0.995、酸R=0.995、醚和烃R=0.995、醛酮R=0.969,留一法交互检验(Leave-one-out,Loo)相关系数分别为酯RLoo=0.986、醇RLoo=0.986、酸RLoo=0.991、醚和烃RLoo=0.944、醛酮RLoo=0.932。结果表明,所建模型具有良好的稳定性和预测能力,为白酒中香味成分的分离检测提供了有效的理论依据。
文摘目的建立预测中草药挥发油成分保留指数的定量结构-色谱保留相关模型。方法以金银花挥发油为研究对象,用Steric and Electronic Descriptors(SEDs)参数表征其分子结构,采用SPSS进行逐步回归分析,建立相关模型,并用留一法对模型交互检验评价模型的预测能力和稳定性。结果金银花挥发油成分的保留指数与建模时筛选的SEDs参数有良好的相关性,建模相关系数均大于0.907;留一法交互检验相关系数与建模相关系数接近,均大于0.896。结论所建模型具有良好的稳定性和预测能力,为中草药挥发油成分的分离检测提供有效的理论依据。
