Development of online algae counting technique for avoiding musty odor in drinking water

建立了用于自动识别一种产生气味的藻类（产生2-MIB的蓝藻）的标准（尺寸、形状、荧光强度），并使用藻蓝蛋白自动荧光进行定量。使用藻蓝蛋白过滤器可以将蓝藻从其他藻类中分离出来。因此，对产生气味的藻类浓度的定量准确性有了很大的提高。测试了不同的供样流动池，以实现分析和样品制备的自动化。将合适的流动池集成到显微镜中。测试了不同的通量以避免藻类聚集。泵被设定了不同的间隔，以允许藻类在图像捕获之前沉淀。通过使用程序泵和显微镜的延时捕获模块，可以自动拍摄样品的图像。

The criteria (dimensions, shape, fluorescence intensity) for automatically identifying one odor-producing algae (2-MIB producing cyanobacteria) was established for quantification using phycocyanin auto-fluorescence. The use of a phycocyanin filter allows to separate cyanobacteria from the rest of algae. As a result, the accuracy for quantifying the concentrations of odor-producing algae has been considerably improved. Different flow cells for feeding samples were tested to automate the analysis and sample preparations. A suitable flow cell was integrated into the microscope. Different flux were tested to avoid algae clusters. The pump was programmed with different intervals to allow for algae settling before image capture. By using a programmed pump and the time-lapse capture module of the microscope, it was possible to take images of the samples automatically.