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Updated: Jun 12, 2026

Measurement of 3-Dimensional cAMP Distributions in Living Cells using 4-Dimensional (x, y, z, and λ) Hyperspectral FRET Imaging and Analysis

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[Water quality analysis by three-dimensional fluorescence spectra based on selective model combination].

Xiao-Li Wu¹, Yan-Jun Li, Tie-Jun Wu

¹Zhejiang University of Science and Technology, Hangzhou 310023, China. wuxiaoli@zust

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu

|June 16, 2010

Summary

This study introduces a selective model combination method to enhance water quality analysis using 3D fluorescence spectra. The new approach significantly improves prediction accuracy for total organic carbon (TOC) and chemical oxygen demand (COD) in water samples.

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Area of Science:

Environmental Science
Analytical Chemistry
Spectroscopy

Context:

Accurate water quality monitoring is crucial for environmental protection and public health.
Traditional methods for analyzing total organic carbon (TOC) and chemical oxygen demand (COD) can be time-consuming and lack precision.
Three-dimensional fluorescence (3D-EEM) spectroscopy offers a powerful tool for characterizing complex water matrices.

Purpose:

To develop a selective model combination method for improving the precision of water quality analysis using 3D fluorescence spectra.
To establish a correlation coefficient criterion for selecting optimal excitation wavelengths for sub-model construction.
To build and validate stacked models for TOC and COD prediction using ridge regression and partial least square regression.

Summary:

A novel method utilizes a correlation coefficient criterion to select optimal excitation wavelengths (e.g., 260, 280, 400 nm for TOC; 220, 280, 400 nm for COD).
Partial least square regression (PLSR) was used for sub-model building, and ridge regression (RR) for combining these sub-models into a stacked model.
The developed stacked models demonstrated significant improvements in prediction accuracy, reducing the root mean square errors of prediction (RMSEP) by 15.4% for TOC and 17.5% for COD compared to the best individual sub-models.

Impact:

The proposed method enhances the precision of water quality analysis, particularly for TOC and COD, in surface water and urban wastewater.
Achieved reductions in RMSEP by 6.1% for TOC and 10.9% for COD compared to models without wavelength selection, highlighting the effectiveness of the selective approach.
Provides a more accurate and efficient analytical tool for environmental monitoring and water resource management.