Environmental Sample Processor

Bringing the laboratory to the ocean

Good boat shot

The Second-Generation Environmental Sample Processor is deployed from a ship in Tasman Bay, New Zealand.

What is the Environmental Sample Processor?

The MBARI Environmental Sample Processor—the ESP—provides on-site (in situ) collection and analysis of water samples from the subsurface ocean.

The instrument is an electromechanical/fluidic system designed to collect water samples and automatically apply molecular detection technology that can identify microorganisms in the water and their gene products. The ESP can also store and preserve samples for analysis after the instrument is recovered.  This movie, produced with support from NASA, provides an overview of the ESP and how it might be used in the world’s oceans and beyond.

Why build an ESP?

Whether trying to identify microorganisms or understand why certain algae produce toxins, analysis typically requires collecting water samples at sea and returning them to a fully equipped laboratory.  This can introduce a significant time-lag between sample collection and informative results.  Additionally, water collection can become very expensive if boats or ships are needed on a regular basis.

Thus in the early 2000s, MBARI initiated the development of the Environmental Sample Processor (ESP) and new techniques to allow the remote application of molecular probe technology.  The hope was to provide a “persistent presence” in the ocean, bringing the laboratory to the sea, and thus reaping cost savings in the most expensive part of microbial oceanography—sample collection.

The ESP, in the foreground, was deployed in a float in Monterey Bay near MBARI’s mooring. Several oceanographic instruments on the mooring will provide measurements of ocean conditions to complement the data gathered by the ESP.


Kevin Gomes

Information Engineering Group Lead

John Ryan

Senior Research Specialist


Solving challenges
Taking the laboratory into the ocean
Environmental Sample Processor (ESP)
In Situ Ultraviolet Spectrophotometer
Midwater Respirometer System
Mobile flow cytometer
Enabling targeted sampling
Automated Video Event Detection
Environmental Sample Processor (ESP)
Gulper autonomous underwater vehicle
Advancing a persistent presence
Aerostat hotspot
Benthic event detectors
Benthic rover
Fault Prognostication
Long-range autonomous underwater vehicle Tethys
MARS hydrophone for passive acoustic monitoring
Monterey Ocean-Bottom Broadband Seismometer
Shark Café camera
Vehicle Persistence
Wave Glider-based communications hotspot
Emerging and current tools
Aerostat hotspot
Wave Glider-based communications hotspot
Data management
Oceanographic Decision Support System
Spatial Temporal Oceanographic Query System (STOQS) Data
Video Annotation and Reference System
Apex profiling floats
Benthic event detectors
Deep particle image velocimetry
Environmental Sample Processor (ESP)
Persistent presence—2G ESP
How does the 2G ESP work?
Arrays on the 2G ESP
Printing probe arrays
Expeditions and deployments
In Situ Ultraviolet Spectrophotometer
Investigations of imaging for midwater autonomous platforms
Lagrangian sediment traps
Midwater Respirometer System
Mobile flow cytometer
SeeStar Imaging System
Shark Café camera
Smart underwater connector
Wave-Power Buoy
Vehicle technology
Benthic Rover
Gulper autonomous underwater vehicle
Imaging autonomous underwater vehicle
Seafloor mapping AUV
Long-range autonomous underwater vehicle Tethys
Mini remotely operated vehicle
ROV Doc Ricketts
ROV Ventana
Automated Video Event Detection
Deep learning
Video Annotation and Reference System
Technology publications
Technology transfer

Bowers, H.A., Marin, R.III, Birch, J.A., Scholin, C.A., and Doucette, G.J. (2016). Recovery and identification of Pseudo-nitzschia frustlules from natural samples acquired using the Environmental Sample Processor (ESP). Journal of Phycology, 52:135–140. http://doi.org/10.1111/jpy.12369

Herfort, L., Seaton, C., Wilkin, M., Roman, B., Preston, C., Marin, R., Seitz, K., Smith, M., Haynes, V., Scholin, C., Baptista, A., Simon, H. (2016). Use of continuous, real-time observations and model simulations to achieve autonomous, adaptive sampling of microbial processes with a robotic sampler.  Limnology and Oceanography: Methods, 14:50-67. http://doi.org/10.1002/lom3.10069

Full publications list