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Use of multivariate regression in spectrophotometric evaluation of chemical oxigen demand in samples of environmental relevance

机译:多元回归在分光光度法评估环境相关样品中化学需氧量中的应用

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In this work, a partial least squares regression routine was used to develop a multivariate calibration model to predict the chemical oxygen demand (COD) in substrates of environmental relevance (paper effluents and landfill leachates) from UV-Vis spectral data. The calibration models permit the fast determination of the COD with typical relative errors lower by 10% with respect to the conventional methodology.
机译:在这项工作中,使用偏最小二乘回归例程来开发多元变量校准模型,以根据UV-Vis光谱数据预测与环境相关的基材(纸废水和垃圾渗滤液)中的化学需氧量(COD)。校准模型可以快速确定COD,相对于传统方法,典型相对误差降低了10%。

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