首页> 外文期刊>Fresenius environmental bulletin >SIMULTANEOUS AND RAPID ANALYSIS OF INTRACELLULAR POLYMER DURING DENITRIFYING PHOSPHORUS REMOVAL USING NEAR INFRARED SPECTROSCOPY AND CHEMOMETRICS
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SIMULTANEOUS AND RAPID ANALYSIS OF INTRACELLULAR POLYMER DURING DENITRIFYING PHOSPHORUS REMOVAL USING NEAR INFRARED SPECTROSCOPY AND CHEMOMETRICS

机译:近红外光谱和化学计量法同时去除磷中的胞内聚合物的同时快速分析

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To realize simultaneous and rapid analysis of the intracellular polymer during denitrifying phosphorus removal, near infrared spectroscopy and BP neutral network algorithm are used to established the analytical models (BP neutral network calibration models) of the poly-β-hydroxybutyrate (PHB), polyphosphate (Poly-P) and glycogen (Gly). After the stability of denitrifying phosphorus removal process, 100 samples were used to establish BP neutral network calibration models, and 40 samples were used to test the performance of the established models. Multiple scatter correction was used as a spectral preprocessing method. The preprocessing results showed that multiple scatter correction can effectively eliminate the baseline shift and migration of near infrared spectra that result from scattering, and the signal-to-noise ratio of near infrared spectral data is improved. preprocessed spectral data were used to establish the BP neutral network calibration models of PHB, Poly-P and Gly. The BP neutral network calibration models of PHB, Poly-P and Gly showed that the correlation coefficients (rc) were respectively 0.9840, 0.9473 and 0.9283, with the root mean square errors of cross validation (RMSECV) being 0.0051, 0.0057 and 0.0063 respectively. In addition, the test results of the BP neutral network calibration models of PHB, Poly-P and Gly indicated that the correlation coefficient (rp) were respectively 0.9789, 0.9291, 0.9182, with the root mean square errors of prediction (RMSEP) being 0.0057, 0.0073 and 0.0080. It showed that BP neutral network calibration models can better analyze PHB, Poly-P and Gly during denitrifying phosphorus removal. The research suggests that near infrared spectroscopy and BP neutral network algorithm may provide a simultaneous and rapid analysis of intracellular polymer.
机译:为了实现脱氮除磷过程中细胞内聚合物的同时快速分析,使用近红外光谱和BP中性网络算法建立了聚β-羟基丁酸酯(PHB),聚磷酸盐(PHB)的分析模型(BP中性网络校准模型)。 Poly-P)和糖原(Gly)。在反硝化除磷工艺稳定之后,使用100个样本建立BP中性网络校准模型,并使用40个样本测试建立的模型的性能。多次散射校正被用作光谱预处理方法。预处理结果表明,多次散射校正可以有效消除散射引起的近红外光谱基线移动和迁移,提高了近红外光谱数据的信噪比。预处理的光谱数据用于建立PHB,Poly-P和Gly的BP神经网络校准模型。 PHB,Poly-P和Gly的BP神经网络校准模型表明,相关系数(rc)分别为0.9840、0.9473和0.9283,交叉验证的均方根误差(RMSECV)分别为0.0051、0.0057和0.0063。此外,PHB,Poly-P和Gly的BP神经网络校准模型的测试结果表明,相关系数(rp)分别为0.9789、0.9291、0.9182,预测的均方根误差(RMSEP)为0.0057。 ,0.0073和0.0080。结果表明,BP中性网络校准模型可以在反硝化除磷过程中更好地分析PHB,Poly-P和Gly。研究表明,近红外光谱和BP神经网络算法可以提供对细胞内聚合物的同时快速分析。

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