Aquaculture is one of the fastest-growing food production sectors globally, with the market projected to increase from $262 billion in 2024 to $277 billion in 2025, driven by rising seafood demand and urbanization. However, rapid and often unregulated expansion has negatively impacted fish health, leading to increased disease outbreaks and excessive antibiotic use. Because only two antibiotics are approved for aquaculture, their overuse has accelerated antibiotic resistance, complicating disease management. This underscores the urgent need for alternative disease prevention and treatment strategies to ensure sustainable aquaculture growth. The present work aims to apply time-lapse photography in rural communities to help improve fish health.
An annular temperature preference tank (ATPT)—a circular, barrier-free system that enables fish to freely select among discrete water temperatures (13, 14, 15, 16, and 17°C)—was utilized to establish a defined thermal gradient. Nineteen rainbow trout (Oncorhynchus mykiss) were introduced to the system and acclimated for at least three hours. Subsequently, fish behavior was continuously recorded for 72 hours, including the acclimation period, using a high-resolution, infrared-equipped camera.
Following acclimation, each fish was challenged via intraperitoneal injection with 0.1 mL of an inactivated vaccine against Aeromonas salmonicida to induce behavioral fever responses. Prior to challenge, live video was streamed to a computer, and the Auto Screen Capture program was used to automatically acquire screenshots every five minutes throughout the experimental period.
At 68 hours post-challenge, recorded image files were exported. Thermal zones within the tank were delineated using an annotation tool, enabling manual counts of fish distributed across thermal areas.
Thermal preference data extracted from the 5-minute interval images were subsequently averaged and aggregated into larger time bins using R software. This approach facilitated comparative graphical analyses and improved the visualization of behavioral fever progression.
We conclude while shorter time intervals can capture finer details of fish thermal preferences post-in vivo challenge, longer intervals (8 h) effectively illustrate the behavioral fever progression. Considering each of the existing pathogens, future work should compare these methods and explore time-lapse devices suitable for rural settings and different pathogen agents as challenges.