Cao Hong, Qu Wen-Tai, Yang Xiang-Long, Jia Sheng-Yao, Wang Chun-Long, Lu Chen
Guang Pu Xue Yu Guang Pu Fen Xi. 2014 Nov;34(11):3015-9.
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 collected turtle breeding water samples were scanned for UV/Vis spectrum, uninformative variable elimination (UVE) and successive projections algorithm (SPA) were combined as a mixed variable selection method to perform characteristic wavelength selection 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 x L(-1) for root mean square error of prediction (RMSEP)) than full wavelengths did (0.88 for r and 15.71 mg x L(-1) for RMSEP). The comprehensive 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 water quality parameters.
研究了紫外可见(UV/Vis)光谱法用于快速测定化学需氧量(COD),化学需氧量是衡量水产养殖水中有机物浓度的指标。对总共135个采集的龟类养殖水样进行UV/Vis光谱扫描,将无信息变量消除(UVE)和连续投影算法(SPA)结合作为混合变量选择方法,从全波长光谱中进行特征波长选择,从201个UV/Vis光谱变量中选择了7个特征波长,仅占全范围光谱数量的3.48%,大大减少了建模的校准时间和复杂度。使用最小二乘支持向量机(LS-SVM)校准得到的预测结果表明,特征波长比全波长取得了更好的结果(相关系数(r)为0.89,预测均方根误差(RMSEP)为15.46 mg·L⁻¹)(全波长的r为0.88,RMSEP为15.71 mg·L⁻¹)。综合结果表明,通过UVE-SPA变量选择方法获得的UV/Vis特征波长结合LS-SVM校准可应用于水产养殖水中COD的快速准确测定。此外,本研究为进一步实现水产养殖水的在线分析和其他水质参数的快速测定奠定了基础。