藻团2维投影特征值定量水源水库中优势藻种  

Quantification of dominant algal species in water reservoir by measuring two-dimensional projection characteristic values of algal clusters

作　　者：苏青青 郦春蓉 王先云[2] 张东[2] 黄鑫[1] SU Qingqing;LI Chunrong;WANG Xianyun;ZHANG Dong;HUANG Xin(School of Environmental and Chemical Engineering,Shanghai University,Shanghai 200444,China;National Engineering Research Center of Urban Water Resources,Shanghai 200082,China)

机构地区：[1]上海大学环境与化学工程学院,上海200444 [2]城市水资源开发利用(南方)国家工程研究中心,上海200082

出　　处：《上海大学学报（自然科学版）》2020年第6期980-988,共9页Journal of Shanghai University:Natural Science Edition

基　　金：国家自然科学基金资助项目(51678351)。

摘　　要：2015年3~7月对华东某水源水库开展了藻种类、密度与显微镜检藻团2维投影特征值调查.结果表明,该水库藻种分布的季节性演替规律明显,春季黄藻门的黄丝藻为优势藻种,占比达到78.9%~92.6%.黄丝藻藻团特征明显,2维投影面积与藻密度有较高的相关性(R^2=0.712).采用分类回归树(classification and regression tree,CART)方法开展实际水样中典型藻种(黄丝藻、小环藻和伪鱼腥藻)的统计回归分类,识别率分别达到83%、68%和86%.藻团2维投影特征度量方法结合图像识别技术,有望实现水中藻团的快速识别与特征测量.From March to July 2015,a microscopic survey on species,density,and twodimensional projection characteristic values of algal clusters showed the obvious seasonal succession pattern of algal species distribution in the reservoir.Tribonema(Xanthophyta)was the dominant algae in spring,accounting for 78.9%to 92.6%of algal clusters,with high correlation between two-dimensional projection area and cell density(R^2=0.712).Classification and regression tree(CART)method was used to identify Tribonema,Cyclotella,and Pseudanabaena,with effective recognition rates of 83%,68%,and 86%,respectively.The two-dimensional projection and image recognition technology were expected to realize rapid identification and characterization of algal clusters in water.

关 键 词：藻团 2维投影特征值 水源水库 

分 类 号：X835[环境科学与工程—环境工程]