Abstract
A rapid and cost-effective system is vital for the detection of harmful algae that causes environmental problems in terms of water quality. The approach for algae detection was to capture images based on hyperspectral fluorescence imaging microscope by detecting specific fluorescence signatures. With the high degree of overlapping spectra of algae, the distribution of pigment in the region of interest was unknown according to a previous report. We propose an optimization method of multivariate curve resolution (MCR) to improve the performance of pigment analysis. The reconstruction image described location and concentration of the microalgae pigments. This result indicated the cyanobacterial pigment distribution and mapped the relative pigment content. In conclusion, with the advantage of acquiring two-dimensional images across a range of spectra, HSI conjoining spectral features with spatial information efficiently estimated specific features of harmful microalgae in MCR models.
Highlights
The harmful algae boom is an environmental problem which affects water quality and alters parameters such as oxygen qualification and light penetration that are crucial to other biologies [1]
The hardware consisted of an epifluorescence microscope (LYMPUS-IX73P2F, Japan), electric-motorized stage (Westage, Shanghai, China), imaging spectroscopy (PRINCETON INSTRUMENT ISOPlane-160, the United States) and data acquisition (NI USB-6361, the United States)
The microscope has two light sources (Fig 1), a halogen lamp used for transmitted light, and a light emitting diode used for excitation
Summary
The harmful algae boom is an environmental problem which affects water quality and alters parameters such as oxygen qualification and light penetration that are crucial to other biologies [1]. Rapid and reliable detection systems for algae are becoming important. Conventional methods of algae detection and analysis are time-consuming and require specialized equipment. One pigment analysis approach is to detect the fluorescent signal using UV-visible spectrophotometer [2]. The method has a preparation experiment that extracting pigment from algal. Another approach is to capture images based on specific fluorescence signatures using specialized microscope [3]. That is means that the value of fluorescent peaks is considered as the gold standard for pigment analysis
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