Dissolved oxygen management is one of the most critical challenges in aquaculture, particularly for channel Catfish Pond production where seasonal climate and capacity demands fuel requirements to sustain farming techniques. Channel catfish production, which represents the largest aquaculture sector in the United States, traditionally relies upon daily spot checks, or low-frequency data measurements. This widely used method of water quality management often misses rapid fluctuations that can impact fish health, feed conversion efficiency and overall pond production. The use of newer technologies that allow for rapid measurements and high-frequency data sets promote the analysis of trends and forecasting benefits.
Recent deployments of high-resolution dissolved oxygen sensors in Catfish Ponds along the Mississippi Delta have revealed patterns previously unseen during spot sampling. Data collected at 10-minute intervals highlight natural diel oxygen cycles when phytoplankton and aquatic plants photosynthesize producing oxygen during the day but consumes oxygen at night as respiration continues. The lowest oxygen levels often occur just before dawn when pond biological activity has been consuming oxygen throughout the night.
This presentation will highlight studies from production ponds where high-resolution oxygen data are helping researchers and software developers utilize trend analysis machine learning to potentially forecast anoxia several hours in advance. These insights can allow managers to adjust aeration schedules proactively and mitigate fish stress, therefore preventing mortality and preserving profits.
High-frequency data is paving the path and marks a shift from reactive crisis management towards pro-active, data-driven aquaculture.