Method of Improving the Accuracy of In-Situ Detection of Cyanobacteria Using Anti-fluorescence Interference Decoupling Algorithm

Abstract

The invention discloses a method of improving blue algae in-situ detection precision by using an anti-fluorescent interference decoupling algorithm. The method depends on a fluorescent analysis method, and measurement can be achieved by taking phycocyanin as a major pigment index for detecting blue algae biomass, and using a fluorescent spectrophotometer that is relatively simple to operate in a laboratory. The method can effectively avoid mutual influence of chlorophyll a, chlorophyll b and the phycocyanin; the blue algae biomass in fresh water is monitored accurately; relatively precise alga biomass data is provided for early warning of blue algae water bloom; a theoretical basis is provided for subsequent design of a blue algae biomass detection sensor; the method can be also used for avoiding interference among multiple pigments to the greatest extent when the fluorescent pigments are detected by a fluorescent method; a theoretical basis is provided for scientific and reasonable screening excitation light wavelength and emitting light wavelength in fluorescent analysis; a multivariant correcting feedback piecewise linear detection model is established when an algal pigment concentration in a water body is detected by the fluorescent method; and precise detection of the pigment concentration is achieved.

Description

technical field [0001] The invention belongs to the field of biological technology, and relates to a method for improving the in-situ detection accuracy of cyanobacteria by using an anti-fluorescence interference decoupling algorithm. Background technique [0002] Fresh water is a resource that human beings depend on for survival, but algae bloom has become one of the three major aquatic ecological environmental problems facing the world, seriously threatening the sustainable use of human water resources. Related studies have shown that about 81% of algae blooms are caused by cyanobacteria. my country is one of the countries with the most severe cyanobacterial blooms in the world, the most widely distributed and the most types of cyanobacteria. Taihu Lake, Dianchi Lake, Dongting Lake, Chaohu Lake and other inland lakes are the high-frequency areas of cyanobacteria blooms in my country. [0003] The outbreak of algae blooms has four major hazards to humans: first, a large nu...

AI Technical Summary

Problems solved by technology

However, such methods do not carry out strict screening for specific wavelengths, and the detected phycocyanin concentration results are greatly interfered by chlorophyll: through the fluorescence characteristics of the three pigments of chlorophyll a, chlorophyll b and phycocyanin, namely figure 2 , it can be seen that in the process of detecting phycocyanin by fluorescence method, the fluorescence intensity of phycocyanin will be affected by chlorophyll a and chlorophyll b

In some cases, the content of both pigments in the water body is very large, resulting in a large error in the detection of phycocyanin, and it is impossible to accurately monitor the change trend of cyanobacterial biomass

Therefore, the detection results cannot reflect the real change trend of cyanobacterial biomass

However, flow cytometry or high performance liquid chromatography requires complex and cumbersome sample processing, and the instrument requires certain operating techniques.

More importantly, it cannot meet the requirements of real-time and portable field detection; the microscope counting method not only consumes a lot of manpower, but also has certain technical requirements, and also cannot meet the requirements of real-time and portable detection.

Images