A novel qPCR-based method to quantify seven phyla of common algae in freshwater and its application in water sources

藻类 水华 布鲁姆 绿藻门 生物 富营养化 预警系统 环境科学 生态学 浮游植物 计算机科学 营养物 细菌 电信 遗传学
作者
Jingjing Li,Xinyan Xiao,Lizheng Guo,Hui Chen,Mingbao Feng,Xin Yu
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:823: 153340-153340 被引量:7
标识
DOI:10.1016/j.scitotenv.2022.153340
摘要

The light microscope is widely used to count algae, however, there are some disadvantages associated with this method, such as time consuming and laborious. In this study, a qPCR-based method was established for quantifying seven phyla of common algae in freshwater, including Cyanophyta, Chlorophyta, Euglenophyta, Bacillariophyta, Dinophyta, Cryptophyta, and Chrysophyta. The accuracy of qPCR in estimating algal cells was confirmed by comparing it with the microscopic counting. The qPCR was used to detect the cell concentration of seven phyla of algae in Longhu Reservoir, showing that green algal blooms occurred during the monitoring period. The intensity of algal blooms was further evaluated according to the classification standard, which suggested that the grade of this bloom was mild. An early warning system was proposed to early warn the occurrence of algal blooms in two water sources, Longhu Reservoir and Dongzhang Reservoir. The qPCR method developed in this study could be a useful tool in the monitoring of algae. The early warning system reported here will have important implications for the effective warning of algal blooms.
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