Fluorescence spectroscopy and absorption spectroscopy are common physical methods used for water quality monitoring and analysis. However, in terms of sensitivity and selectivity, the absorption spectroscopy is still inferior; limited categories of organic contaminants can emit fluorescence, which constrains the analytical range. Here in, a novel feature extraction method is proposed in conjoint analysis of fluorescence and absorption spectroscopy to predict the category of water contaminants. The three-dimensional fluorescence spectra and absorption spectra of eight typical substances were studied. We extracted the outline of every three-dimensional fluorescence spectrum along the emission wavelengths axis, and then transformed it into a wavenumber spectrum. The symmetry axis and Stokes shift between fluorescence emission peak and absorption peak in their wavenumber spectra were set as two features. Theoretically, they depend only on the molecular structures of different substances. Moreover, four integral parameters in different absorption spectral ranges corresponding to functional groups were introduced to expand the analytical coverage of diverse contaminants including some non-fluorescent substances. Furthermore, we conducted long-term monitoring of river water near a dyeing and printing plant to demonstrate the prediction potential of this method. As an early warning system, the rapid prediction results can provide guidance for more targeted and detailed analysis and treatment.
In this paper, a novel approach was implemented to image the marine plankton using the in-line digital holographic technology. the digital holography can image all plankton in a certain volume and more information can be recorded including the intensity and phase information. Moreover, the lensless system cases no aberrations and reduces the complexity of structure. In the process of hologram reconstruction, numerical algorithms were developed based on the angle spectrum theory. In the experiments of marine plankton, some technical issues, such as reconstruction algorithm, numerical refocusing, zero-order term suppression, were discussed. We can obtain the reconstructing image layer by layer at different distances by changing the distance step, which demonstrates that digital holographic imaging is capable of digital refocusing. Digital holographic imaging has clear advantages over other optical methods for the analysis of marine plankton, which contributes to further microorganism identification in the oceanographic observation by using the digital image processing and microscopy techniques.