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首页> 外文期刊>Harmful Algae >Determination of the filamentous cyanobacteria Planktothrix rubescens in environmental water samples using an image processing system
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Determination of the filamentous cyanobacteria Planktothrix rubescens in environmental water samples using an image processing system

机译：使用图像处理系统测定环境水样中的丝状蓝细菌浮游生物

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摘要

Cyanobacteria occur in surface waters worldwide. Many of these produce peptides and/or alkaloids, which can present a risk for animal and human health. Effective risk assessment and management requires continuous and precise observation and quantification of cyanobacterial cell densities. In this respect, quantification of filamentous Planktothrix species is problematic. The aim of this study was to develop an automated system to count filamentous Planktothrix rubescens using image processing. Furthermore, this study aimed to assess optimum sample volumes and filament density for measurement precision and to validate image processing measurement of P. rubescens for an effective risk assessment. Three environmental samples and one cultured sample of P. rubescens were collected by filtration onto nitrocellulose filters. Filament lengths were determined using fluorescence microscopy combined with an image processor. Cell density could be calculated from the resulting images. Cyanobacteria could easily be discriminated from algae via their fluorescence properties. The results were found to be independent of the mode of image acquisition. The precision of total filament length determination was dependent on the total filament length on the filter, i.e. analyses of highest precision could be expected for filters containing 2000-20,000 μm filaments per mm~2. When using suitable filtration volumes, the detection limits of the described method are sufficient for an effective risk assessment. To summarise, this procedure is a fast, easy and accurate method to determine cell densities of filamentous P. rubescens in water samples without costly and tedious manual handling.
机译：蓝细菌在全世界的地表水中发生。其中许多产生肽和/或生物碱，可能对动物和人类健康构成威胁。有效的风险评估和管理要求对蓝细菌细胞密度进行连续，精确的观察和定量。在这方面，量化丝状浮游物种种类是有问题的。这项研究的目的是开发一种自动系统，使用图像处理技术来对丝状浮游生物进行计数。此外，本研究旨在评估最佳样品量和细丝密度以提高测量精度，并验证风信子的图像处理测量以进行有效的风险评估。通过过滤到硝酸纤维素滤膜上，收集3个环境样品和1个红景天培养样品。使用荧光显微镜结合图像处理器来确定丝的长度。可以从所得图像计算细胞密度。蓝藻很容易通过其荧光特性与藻类区分开。发现结果与图像采集模式无关。总细丝长度确定的精度取决于过滤器上的总细丝长度，即，对于每mm〜2包含2000-20,000μm细丝的过滤器，可以期待最高精度的分析。当使用合适的过滤量时，所描述方法的检测极限足以进行有效的风险评估。综上所述，该程序是一种快速，简便，准确的方法，无需花费昂贵且繁琐的人工操作即可确定水样中丝状紫茎泽兰的细胞密度。

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