Impact of dataset diversity on accuracy and sensitivity of parallel factor analysis model of dissolved organic matter fluorescence excitation-emission matrix.
Impact of dataset diversity on accuracy and sensitivity of parallel factor analysis model of dissolved organic matter fluorescence excitation-emission matrix.
复制标题
数据集多样性对溶解有机物荧光激发-发射矩阵平行因子分析模型准确性和灵敏度的影响
DOI：
10.1038/srep10207
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发表时间：
2015-05-11
影响因子：
4.6
通讯作者：
Li G
中科院分区：
文献类型：
--
作者：
Yu H;Liang H;Qu F;Han ZS;Shao S;Chang H;Li G
并行因子（PARAFAC）分析使得能够对激发-发射矩阵（EEM）进行定量分析。来自不同数据集的光谱变异性对PARAFAC模型的代表性的影响需要加以研究。在这项研究中，从一条河流，污水处理厂的出水和藻类分泌物样品收集和PARAFAC分析。比较了全球数据集和个体数据集的PARAFAC模型。结果发现，来自源的多样性的峰移破坏了全球模型的准确性。结果表明，建立一个通用的PARAFAC模型，可以广泛适用于拟合新的EEM将是相当困难的，但拟合EEM到现有的PARAFAC模型属于一个类似的环境将是更现实的。通过将EEM数据与由PARAFAC建模的最大荧光（Fmax）相关联来检查在线监测策略的准确性，所述在线监测策略监测PARAFAC组分的峰处的荧光强度。对于单个数据集，在峰位置周围获得了显着的相关性。然而，对混合数据集的分析表明，与当地成分光谱相似的外国成分的参与将破坏在线监测战略。
Parallel factor (PARAFAC) analysis enables a quantitative analysis of excitation-emission matrix (EEM). The impact of a spectral variability stemmed from a diverse dataset on the representativeness of the PARAFAC model needs to be examined. In this study, samples from a river, effluent of a wastewater treatment plant and algae secretion were collected and subjected to PARAFAC analysis. PARAFAC models of global dataset and individual datasets were compared. It was found that the peak shift derived from source diversity undermined the accuracy of the global model. The results imply that building a universal PARAFAC model that can be widely available for fitting new EEMs would be quite difficult, but fitting EEMs to existing PARAFAC model that belong to a similar environment would be more realistic. The accuracy of online monitoring strategy that monitors the fluorescence intensities at the peaks of PARAFAC components was examined by correlating the EEM data with the maximum fluorescence (Fmax) modeled by PARAFAC. For the individual datasets, remarkable correlations were obtained around the peak positions. However, an analysis of cocktail datasets implies that the involvement of foreign components that are spectrally similar to local components would undermine the online monitoring strategy.
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影响因子：
11.4
作者：
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影响因子：
12.8
作者：
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