
ABSTRACT The use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab‐ or ship‐based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality‐controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense‐type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain‐forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters.
[SDE] Environmental Sciences, regular maintenance, coincidence risk, flow cytometry, Phytoplankton, phytoplankton, best practices, detection optimization, quality control, CytoSense, Flow Cytometry, Environmental Monitoring
[SDE] Environmental Sciences, regular maintenance, coincidence risk, flow cytometry, Phytoplankton, phytoplankton, best practices, detection optimization, quality control, CytoSense, Flow Cytometry, Environmental Monitoring
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