000K utf8 0100 1043807829 0500 Oau 1100 2018$c2018-12-03 1208 Elektronische Ressource 1500 eng 2051 10.1186/s12898-018-0209-5 3000 Dunke, Susanne 3010 Boho, David 3010 Mäder, Patrick 3010 Wäldchen, Jana 4000 Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton [Dunke, Susanne] 4060 15 Seiten 4209 Background: Phytoplankton species identification and counting is a crucial step of water quality assessment. Especially drinking water reservoirs, bathing and ballast water need to be regularly monitored for harmful species. In times of multiple environmental threats like eutrophication, climate warming and introduction of invasive species more intensive monitoring would be helpful to develop adequate measures. However, traditional methods such as microscopic counting by experts or high throughput flow cytometry based on scattering and fluorescence signals are either too time-consuming or inaccurate for species identification tasks. The combination of high qualitative microscopy with high throughput and latest development in machine learning techniques can overcome this hurdle. Results: In this study, image based cytometry was used to collect ~ 47,000 images for brightfield and Chl a fluorescence at 60× magnification for nine common freshwater species of nano- and micro-phytoplankton. A deep neuronal network trained on these images was applied to identify the species and the corresponding life cycle stage during the batch cultivation. The results show the high potential of this approach, where species identity and their respective life cycle stage could be predicted with a high accuracy of 97%. Conclusions: These findings could pave the way for reliable and fast phytoplankton species determination of indicator species as a crucial step in water quality assessment. 4950 https://doi.org/10.1186/s12898-018-0209-5$xR$3Volltext$534 4961 http://uri.gbv.de/document/gvk:ppn:1043807829 5051 570 5051 610 5550 CNN 5550 Deep learning 5550 High throughput cytometry 5550 Image-based identification 5550 Images 5550 Imaging flow cytometry 5550 Machine learning 5550 Magnification 5550 Morphology 5550 Phytoplankton