PlanktonScope : Affordable modular imaging platform for citizen oceanography

Thibaut Pollina1, Adam G. Larson1, Anton Molina1, Sebastien Colin2, Colomban de Vargas2,3, Hongquan Li1 and Manu Prakash1, (1)Stanford University, Bioengineering, Stanford, CA, United States, (2)Station Biologique de Roscoff, Sorbonne Université & CNRS, Roscoff, France, (3)Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, Paris, France
Abstract:
A common narrative in biological oceanography is the systematic underestimation of morphological diversity existing at levels from the community down to the heterogeneity in a single species. This is due in part to the traditional strategy of sampling plankton through a relatively small fleet of large, costly, and high-carbon footprint oceanographic vessels. Their deployment is logistically complicated making only a few oceanographic campaigns possible each year. This prohibits accurate sampling of the extreme spatio-temporal dynamics of ocean-wide planktonic communities. There is a need to significantly scale up the global sampling strategy of plankton for robust modelling of their dynamics and evolution in a rapidly changing ocean.

By enabling a global network of mariners who are already present at sea, we could benefit from a massive citizen sampling effort providing unprecedented coverage with a sampling frequency that largely outperforms the few large expeditions. This method depends on a frugal device capable of being deployed in large numbers while generating reliable, accurate, and standardized scientific data.

As part of the ‘Plankton Planet’ initiative, we present here the PlanktonScope, a portable and low cost imaging platform capable of autonomous high-throughput quantitative imaging as well as recreative imaging. Its modular design, which allows the instrument to evolve over time, is made of detachable and versatile modules that each encapsulate functions such as illumination, lenses, camera sensor, valves, pump, and abiotic sensors (notably pH, ORP, Dissolved Oxygen, Conductivity and Temperature). This library of simple modules is linked by a single python based API enabling powerful autonomous imaging acquisition as well as a synchronized log of environmental parameters. Furthermore, we developed a standardized image processing pipeline allowing a real-time segmentation and feature extraction for each detected object creating a massive data flow. One configuration of the PlanktoScope is capable of autonomously imaging 1.7 ml per minute with a 1.2 µm resolution. The raw price of the instrument is lower than $200, enabling new capabilities for low cost bulk imaging of cultures of micro-organisms in the lab, as well as scale up for deployment on an international fleet of sailing boats.