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首页> 外文期刊>Journal of Biochemical and Biophysical Methods >Evaluation of data produced by optode arrays under flow injection analysis (FIA) conditions using a partial least squares method (PLS2).
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Evaluation of data produced by optode arrays under flow injection analysis (FIA) conditions using a partial least squares method (PLS2).

机译:使用偏最小二乘方法(PLS2)对在流动注射分析(FIA)条件下由光电二极管阵列产生的数据进行评估。

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摘要

Transient diffuse reflectance spectra in the visible wavelength region from an enzyme optode were evaluated to determine artificial mixtures consisting of penicillin and ampicillin simultaneously. In order to achieve a discrimination of the samples the optode operated at two different working pH values. Using an appropriate FIA modus a linear range in the increase and decrease of the time-dependent signal was registered which could be easily fitted by means of ordinary linear regression. In this way characteristic static and dynamic features of the enzyme catalyzed reaction could be extracted for the evaluation by partial least-squares (PLS). The pre-processed raw data were differently weighted and the optimal number of primary factors was each selected by full cross validation. The interpretation of the spectral loadings and the correlation matrix identifies redundant variables resulting in a model with an optimal number of variables. The results obtained with this model show that the straightforward linear regression can be a sufficient approach to avoid the introduction of systematic errors in on-line pre-processing of data.
机译:评估了来自酶optode的可见光波长范围内的瞬态漫反射光谱,以确定同时由青霉素和氨苄西林组成的人工混合物。为了区分样品,光电二极管在两个不同的工作pH值下运行。使用适当的FIA方法,可以记录随时间变化的信号的增加和减少的线性范围,这可以通过普通的线性回归轻松地拟合。以此方式,可以提取酶催化反应的静态和动态特征,以通过偏最小二乘(PLS)进行评估。对预处理的原始数据进行不同的加权,并通过全交叉验证分别选择最佳的主要因子数量。频谱负荷和相关矩阵的解释可以识别出冗余变量,从而得到具有最佳变量数量的模型。通过该模型获得的结果表明,直接的线性回归可以成为避免在线预处理数据时引入系统错误的充分方法。

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