Convenient lake ecological health monitoring system and method based on phytoplankton communities

Abstract

The invention relates to a convenient lake ecological health monitoring method based on phytoplankton communities. The method comprises the following steps of: collecting and sorting related data of corresponding relations between different types of phytoplankton and community compositions and environmental factors, and storing the related data in a central server; collecting a to-be-detected water sample and concentrating, and putting a concentrated sample on the glass slide; shooting the concentrated sample on the glass slide by adopting a microscopic imaging device, and sending a shot picture to a central server; and performing image identification, the by the central server,on the received pictures, judging and counting phytoplankton species in the images, acquiring dominant species and community structure composition information, and comparing the dominant species and community structure composition information with collected and stored data to generate a water quality report. According to the method, sample concentration and picture shooting work can be completed on site, and a large number of water samples do not need to be carried back to a laboratory for treatment. Compared with a traditional phytoplankton identification method, the method has the advantages that the phytoplankton identification time can be greatly shortened, and related results obtained in several days before are shortened to tens of minutes.

Description

technical field [0001] The invention relates to a convenient monitoring system and method for lake ecological health based on phytoplankton communities. Background technique [0002] Water pollution is an important factor affecting water quality safety, and it is one of the hot issues that the whole society pays close attention to, especially the water quality safety of lake ecosystems is closely related to people's daily life. In the early years, people judged whether the water body was healthy by the most intuitive performance of the water body, such as the transparency of the water body, whether there was a peculiar smell, etc.; later, due to the increase in pollution incidents, people analyzed the water quality by targeted detection of the composition and concentration of certain chemical elements in the water body. For example, in the early 20th century, the United States detected the heavy metals, COD, non-metallic inorganic substances, etc. in the water bodies in resp...

AI Technical Summary

Problems solved by technology

[0015] According to the above process, it can be seen that the conventional identification and counting of phytoplankton takes a long time, and at the same time, professional and technical personnel with rich experience are required to analyze the samples

Although there are currently flow cytometers, Phyto-PAM, etc. that can analyze the composition of phytoplankton in water samples, most of them are mainly for indoor pure culture samples or very rough classification, which is difficult to meet the needs of water quality monitoring

The traditional phytoplankton analysis method is the most mature and widely used method, but because it takes a long time and requires specialized technicians to identify, and there are obvious systematic errors between different technicians, the analysis of the same water body by different personnel The results tend to have discrepancies

Although the existing new technology can achieve rapid detection, but the scope of application is small and cannot meet the needs of rapid detection of water ecosystem health

With the development of image recognition technology, there are currently corresponding inventions to identify algae pictures, but they are limited to the analysis and statistics of the species composition of algae, and cannot carry out ecological health evaluation

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