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机构地区:[1]清华大学深圳研究生院,广东深圳518055 [2]海南大学机电工程学院,海南海口570228 [3]暨南大学光电工程系,广东广州510632
出 处:《分析测试学报》2014年第10期1189-1193,共5页Journal of Instrumental Analysis
基 金:国家自然科学基金资助项目(61078040;11374179)
摘 要:利用傅立叶变换红外光谱( FTlR)和衰减全反射( ATR)技术,建立了人血清葡萄糖的快速定量分析方法。根据葡萄糖水溶液与纯净水差谱得到葡萄糖的指纹吸收波段(1200-900 cm-1),分别在全谱(4000-600 cm-1)和指纹波段建立偏最小二乘法( PLS)模型,指纹波段的预测效果明显好于全谱。选择指纹波段后,提出一种根据浓度分段分别建模然后进行组合的建模方法。按照全部样品、低浓度样品、高浓度样品分别建立模型后,根据3个模型进行综合决策。应用独立的检验集对样品进行测试表明,按葡萄糖浓度范围分段建立组合模型的预测效果优于基于全部样品建模的预测效果。对于分段阈值附近的样本,低浓度和高浓度模型的预测效果差别不大。浓度分段组合模型的预测均方根偏差( RMSEP)和预测相关系数( Rp )分别为0.732 mmol/L和0.948。The rapid quantification method of human serum glucose was established by using the Fou-rier transform infrared spectroscopy( FTlR ) and attenuated total reflection( ATR ). The subtracted spectrum between glucose solution and water was calculated which was 1 200-900 cm-1 and named fingerprint region. Both partial least squares( PLS)models of whole spectrum(4 000 -600 cm-1 ) and fingerprint spectrum were built. The predicted result of fingerprint region was better than that of the whole spectral. Three PLS models for all samples,low concentration samples and high concentra-tion samples were built. Based on this,compound decision of three models was carried on. Finally, the independent test set was performed for model verification. The results showed that the prediction bias of the combination model for human serum glucose was obviously better than that of the whole spectral or the fingerprint region,and for the samples whose value were nearby threshold,the differ-ence of prediction errors for low concentration model and high concentration model was small. RM-SEP and RP were 0. 732 mmol/L and 0. 948,respectively,by the concentration section model.
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