Online-monitoring Cyclotella sp. concentrations in lake water using an automated fluorescence microscopy method†

IF 3.1 4区 环境科学与生态学 Q3 ENGINEERING, ENVIRONMENTAL
Sandrine Boivin and Takahiro Fujioka
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Abstract

Algal proliferation in source water presents significant challenges to drinking water utilities owing to the release of taste and odor compounds and algal organic matter associated with the formation of disinfection byproducts. Cyclotella sp., a diatom, can cause undesirable fishy or grassy odors, and its algal organic matter can be a precursor of toxic disinfection byproducts in drinking water. This study aimed to establish an automated method for determining the Cyclotella sp. concentration in surface water. First, an auto-counting method was developed to quantify specific algal concentrations among many other algae based on autofluorescence intensity and morphological characteristics such as dimensions and circularity. The auto-counting of Cyclotella sp. was accurate, with an overall accuracy of 98% and an F1 score of 96%, and the automated and manual counts of Cyclotella sp. were highly correlated (rs = 0.989). Second, an automated online monitoring system, which can be installed along with a water-containing pipeline and provide concentration measurements within 20 min, was developed by integrating the time-lapse capture module of a fluorescence microscope with a flow cell and pump. Changes in Cyclotella sp. concentrations between 170 and 1661 cells per mL were successfully monitored for 42 h without personnel intervention. The automated method developed in this study can detect rapid changes in algal communities and allow water utilities to take immediate countermeasures against them.

Abstract Image

利用自动荧光显微镜法在线监测湖水中环孢菌的浓度
源水中藻类的增殖对饮用水公用事业提出了重大挑战,因为它们释放出味道和气味化合物以及与消毒副产物形成相关的藻类有机物。Cyclotella sp.,一种硅藻,可以引起不受欢迎的鱼腥味或草腥味,其藻类有机物可以成为饮用水中有毒消毒副产物的前体。本研究旨在建立地表水中Cyclotella sp.浓度的自动测定方法。首先,基于自身荧光强度和形态特征(如尺寸和圆度),开发了一种自动计数方法来量化许多其他藻类中的特定藻类浓度。自动计数准确,总体准确率为98%,F1评分为96%,自动计数与人工计数高度相关(rs = 0.989)。其次,将荧光显微镜的延时采集模块与流动池和泵相结合,开发了一套自动在线监测系统,该系统可与含水管道一起安装,并在20分钟内提供浓度测量。在没有人员干预的情况下,成功地监测了每毫升170到1661个细胞之间的Cyclotella sp浓度变化42小时。本研究开发的自动化方法可以检测藻类群落的快速变化,并允许水务公司立即采取对策。
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来源期刊
Environmental Science: Water Research & Technology
Environmental Science: Water Research & Technology ENGINEERING, ENVIRONMENTALENVIRONMENTAL SC-ENVIRONMENTAL SCIENCES
CiteScore
8.60
自引率
4.00%
发文量
206
期刊介绍: Environmental Science: Water Research & Technology seeks to showcase high quality research about fundamental science, innovative technologies, and management practices that promote sustainable water.
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