Near infrared spectroscopy and multivariate calibration for simultaneous determination of glucose, triglycerides and high-density lipoprotein in animal plasma

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• 作者：Ana Carolina de Oliveira Neves^a ; Aurigena Antunes de Araú ; jo^b ; Bruna Laí ; s Silva^b ; Patrí ; cia Valderrama^c ; Paulo Henrique Març ; o^c ; Ká ; ssio Michell Gomes de Lima^a ; ^{kassio@ufrnet.br}
• 关键词：NIR ; Glucose ; Triglycerides ; High-density lipoprotein ; Multivariate calibration
• 刊名：Journal of Pharmaceutical and Biomedical Analysis
• 出版年：2012
• 期刊代码：65_07317085
• 类别：ch
• 出版时间：July, 2012
• 卷：66
• 期：Complete
• 页码：252-257
• 文件大小：469 K

摘要

The quantitative analysis of glucose, triglycerides and high-density lipoprotein (HDL) in rat plasma without sample pre-treatment using direct near-infrared spectroscopy was studied. Comparison was made of several multivariate calibration techniques and algorithms for data pre-processing and variable selection, including partial least squares (PLS), interval partial least squares (iPLS), genetic algorithm (GA) and successive projections algorithm (SPA). Variable selection yielded good results for the correlation coefficient and Root Mean Square Error of Prediction (RMSEP) values for the three parameters, especially triglycerides. The RMSEP values for glucose, triglycerides and HDL produced by the PLS model were 6.08, 16.07 and 2.03 mg dl^鈭?, respectively. F tests and t-tests were performed to compare the results of the models with each other and with a reference method. These results suggests that the PLS method can be used to simultaneously determine the concentrations of glucose, triglycerides and HDL in complicated biological fluids with NIR spectroscopy, offering an alternative analysis in animals.