紫外可见光谱的水产养殖水体有机物浓度快速检测研究

摘要

Ultraviolet/visible (UV/Vis) spectroscopy was investigated for the rapid determination of chemical oxygen demand (COD) which was an indicator to measure the concentration of organic matter in aquaculture water .A total number of 135 col-lected turtle breeding water samples were scanned for UV/Vis spectrum ,uninformative variable elimination (UVE) and succes-sive projections algorithm (SPA) were combined as a mixed variable selection method to perform characteristic wavelength selec-tion from the full wavelength spectrum ,7 characteristic wavelengths were selected from full 201 UV/Vis spectral variables , which were just 3 .48% number of the full range spectrum ,and the calibration time and complexity of the modeling were greatly reduced .The predicted results which were obtained by using least squares-support vector machine (LS-SVM) calibration showed that the characteristic wavelengths achieved better results (0.89 for correlation coefficient (r) ,15.46 mg · L -1 for root mean square error of prediction (RMSEP)) than full wavelengths did (0.88 for r and 15.71 mg · L -1 for RMSEP) .The comprehen-sive results revealed that the UV/Vis characteristic wavelengths which were obtained by UVE-SPA variable selection method , combined with LS-SVM calibration could apply to the rapid and accurate determination of COD in aquaculture water .Moreover , this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other w ater quality parameters .%应用紫外可见（ultraviolet/visible ，UV/Vis）光谱技术对表征水产养殖水体中有机物浓度的指标化学需氧量（chemical oxygen demand ，COD）进行快速测量，对采集到的135份甲鱼养殖水样进行 UV/Vis波段全光谱扫描，采用无信息变量消除（uninformative variable elimination ，UVE）和连续投影算法（successive projections algorithm ，SPA）相结合的变量选择算法选取全波段光谱中的特征波长，从201个 UV/Vis光谱变量中选取了7个特征波长，只占全波段光谱变量的3.48％，降低了建模的时间和模型的复杂度。结合最小二乘支持向量机（least-square support vector machine ，LS-SVM ）算法进行COD预测建模，结果表明：使用特征波长建模的预测效果（相关系数 r（correlation coefficient）＝0.89，预测均方根误差（root mean square error of prediction ，RMSEP）＝15.46 mg · L -1）好于使用全波段光谱建模的预测效果（r＝0.88，RMSEP ＝15.71 mg · L -1）。使用UVE-SPA变量选择算法获取UV/Vis光谱特征波长，结合LS-SVM建模，可以快速、准确的测量水产养殖水体中的COD浓度，为进一步实现水产养殖水质的在线检测以及其他水质参数的快速测定奠定了基础。