Classification of Plankton and Particulate Matter from the North Atlantic Based on Shadowgraph Images from an Underwater Microscope

• Main Authors: Irby, Makayla S., Huang, Huanqing, Bochdansky, Alexander B.
• Format: Still Image
• Language: unknown
• Published: ODU Digital Commons 2024
• Subjects: Oceanography and Atmospheric Sciences and Meteorology; North Atlantic
• Online Access: https://digitalcommons.odu.edu/undergradsymposium/2024/posters/8

We will be presenting shadowgraph images of particles and plankton ranging in size from 190 micrometers to several millimeters obtained during a Spanish oceanographic expedition traversing a segment of the North Atlantic Ocean. The images show a number of plankton and marine particulate matter, each of which were classified according to broad taxonomic groups. The objective of this classification is to establish a training set for machine learning algorithms, with the goal of them being able to automatically categorize these particles. With our research, we aim to automate and enhance the taxonomic classification process, paving the way for more efficient analysis of marine life in our oceans. The understanding of the type and fate of plankton and other particulate matter such as marine snow and fecal pellets is important for our understanding of biogeochemical cycles in different regions of the ocean ranging from the oligotrophic gyres to upwelling systems within the Atlantic. The machine learning classification process will enable researchers to efficiently identify patterns and relationships within these ecosystems.