Accessible quantitation of surface water phytoplankton with ARTiMiS
Start Date
23-5-2022 11:30 AM
End Date
23-5-2022 11:45 AM
Abstract
Access to accurate real-time data on the presence of target phytoplankton can enable timely, proactive, and data-driven decision making to protect drinking water systems from harmful algal blooms (HABs). These decisions can include initiating targeted actions such issuing public health advisories or changes in raw water access/treatment strategies. Measurements of parameters such as Chlorophyll a provide bulk estimates of photosynthetic biomass but are unable to provide taxonomic resolution to differentiate between toxin-producing species and their benign counterparts. Taxonomic data is primarily determined by two methods: microscopic inspection and genetic sequencing. Both require extensive laboratory infrastructure, operational expertise, and considerable time investment for sample characterization. Existing automated commercial instruments are exceedingly cost prohibitive for wide-scale adoption. These barriers to access have motivated development of ARTiMiS: the Autonomous Real-Time Microbial Scope. ARTiMiS is designed for order-of-magnitude instrument cost reduction, enabling use at the point of sampling with real-time data acquisition and machine learning-based processing to enable species-level phytoplankton characterization. This talk will highlight the research team’s efforts adapting ARTiMiS towards a plug-and-play algal monitoring system that can be deployed for phytoplankton monitoring in the Detroit River (water treatment intake source waters for the Detroit metropolitan area) as an early HAB detection device.
Accessible quantitation of surface water phytoplankton with ARTiMiS
Access to accurate real-time data on the presence of target phytoplankton can enable timely, proactive, and data-driven decision making to protect drinking water systems from harmful algal blooms (HABs). These decisions can include initiating targeted actions such issuing public health advisories or changes in raw water access/treatment strategies. Measurements of parameters such as Chlorophyll a provide bulk estimates of photosynthetic biomass but are unable to provide taxonomic resolution to differentiate between toxin-producing species and their benign counterparts. Taxonomic data is primarily determined by two methods: microscopic inspection and genetic sequencing. Both require extensive laboratory infrastructure, operational expertise, and considerable time investment for sample characterization. Existing automated commercial instruments are exceedingly cost prohibitive for wide-scale adoption. These barriers to access have motivated development of ARTiMiS: the Autonomous Real-Time Microbial Scope. ARTiMiS is designed for order-of-magnitude instrument cost reduction, enabling use at the point of sampling with real-time data acquisition and machine learning-based processing to enable species-level phytoplankton characterization. This talk will highlight the research team’s efforts adapting ARTiMiS towards a plug-and-play algal monitoring system that can be deployed for phytoplankton monitoring in the Detroit River (water treatment intake source waters for the Detroit metropolitan area) as an early HAB detection device.