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Investigations into Background Correction and Retention Time Alignment to Enhance Quantitative Chemometric Analysis of Comprehensive Two-Dimensional Liquid Chromatography-Diode Array Detection Data

机译:研究背景校正和保留时间比对,以增强二维二维液相色谱-二极管阵列检测数据的定量化学计量分析

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摘要

The focus of the projects presented here was to develop possible solutions to three issues commonly encountered during chemometric analysis of comprehensive two-dimensional liquid chromatography diode array detector (LCxLC-DAD) data. The focus of the first project was to determine a means of performing background correction that removed two background ridges. The methods of simply subtracting out a mean blank sample, singular value decomposition based background correction (SVD-BC) and asymmetrically weighted least squares (AWLS) were compared. AWLS was found to be the only background correction technique to fully remove the ridges. However, AWLS was also found to attenuate the peak intensity by approximately 25% due to over fitting of the background at the lower wavelengths. The focus of the second project was the investigation of five common interpolation strategies for the reconstruction of the sampled first dimension peak. The interpolation strategy that best reproduced the original first dimension retention time was Gaussian fitting. This was expected given that the simulated data set was generated using a Gaussian model for the peak shape. An algorithm, semi-automated alignment method (SAAM), was then developed that allowed for each peak to be aligned independently of the other peaks in the data set. SAAM was validated using both simulated and experimental data. The simulated results indicated that SAAM produced percent recoveries close to 100%. SAAM was also compared to iterative key set factor analysis-alternating least squares (IKSFA-ALS) for the analysis of phenytoin in a waste water treatment plant effluent. SAAM produced a concentration of 26±3 ppb compared to 39±9 ppb from IKSFA-ALS. While these results are very different, the result produced by SAAM is still within the experimental error of the reference 2D-LC/MS/MS method, 42±19. Finally, SAAM was compared to two existing literature methods. A mixture of simulated and experimental data sets was used to measure the accuracy and precision of the results. SAAM was found to be impacted less by intra- and inter-sample retention time shifting then PARAFAC2. SAAM and shifted candecomp/PARAFAC were found to produce very similar results. However, SAAM was found to experience some difficulty producing accurate and precise results with some of the experimental data sets.
机译:此处介绍的项目的重点是为全面二维液相色谱二极管阵列检测器(LCxLC-DAD)数据的化学计量分析过程中遇到的三个问题开发可能的解决方案。第一个项目的重点是确定执行背景校正的方法,该方法可以消除两个背景脊。比较了简单减去平均空白样本的方法,基于奇异值分解的背景校正(SVD-BC)和不对称加权最小二乘(AWLS)的方法。发现AWLS是唯一一种可以完全去除凸脊的背景校正技术。但是,由于在较低波长下背景的过度拟合,还发现AWLS使峰值强度衰减了大约25%。第二个项目的重点是研究五种常见的插值策略,以重构采样的一维峰。最能重现原始一维保留时间的插值策略是高斯拟合。鉴于使用峰形的高斯模型生成了模拟数据集,因此这是可以预期的。然后开发了一种算法,即半自动比对方法(SAAM),该算法允许每个峰独立于数据集中的其他峰进行比对。使用模拟和实验数据验证了SAAM。模拟结果表明,SAAM的回收率接近100%。还将SAAM与迭代关键设定因子分析-交替最小二乘(IKSFA-ALS)进行了比较,以分析废水处理厂废水中的苯妥英钠。 SAAM产生的浓度为26±3 ppb,而IKSFA-ALS的浓度为39±9 ppb。尽管这些结果有很大差异,但SAAM产生的结果仍在参考2D-LC / MS / MS方法的实验误差范围内,即42±19。最后,将SAAM与两种现有文献方法进行了比较。使用模拟和实验数据集的混合物来测量结果的准确性和准确性。发现样品内和样品间保留时间的变化对SAMA的影响小于对PARAMAC2的影响。发现SAAM和转移的candecomp / PARAFAC产生非常相似的结果。但是,发现SAAM在使用某些实验数据集生成准确的结果时会遇到一些困难。

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    Allen Robert;

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  • 年度 2012
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