期刊
TALANTA
卷 83, 期 4, 页码 1254-1259出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2010.07.084
关键词
Chromatography; Biodiesel; Chemometrics; Partial least squares analysis
资金
- Seattle Pacific University
- M.J. Murdock Charitable Trust
The percent composition of blends of biodiesel and conventional diesel from a variety of retail sources were modeled and predicted using partial least squares (PLS) analysis applied to gas chromatography-total-ion-current mass spectrometry (GC-TIC), gas chromatography-mass spectrometry (GC-MS), comprehensive two-dimensional gas chromatography-total-ion-current mass spectrometry (GCxGC-TIC) and comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS) separations of the blends. In all four cases, the PLS predictions for a test set of chromatograms were plotted versus the actual blend percent composition. The GC-TIC plot produced a best-fit line with slope = 0.773 and y-intercept = 2.89, and the average percent error of prediction was 12.0%. The GC-MS plot produced a best-fit line with slope = 0.864 and y-intercept = 1.72, and the average percent error of prediction was improved to 6.89%. The GCxGC-TIC plot produced a best-fit line with slope = 0.983 and y-intercept = 0.680, and the average percent error was slightly improved to 6.16%. The GCxGC-MS plot produced a best-fit line with slope = 0.980 and y-intercept = 0.620, and the average percent error was 6.12%. The GCxGC models performed best presumably due to the multidimensional advantage of higher dimensional instrumentation providing more chemical selectivity. All the PLS models used 3 latent variables. The chemical components that differentiate the blend percent compositions are reported. (c) 2010 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据