By critically examining whether individual animal identities and their overall physiological state can be gleaned from rapid and comprehensive capture of biometric descriptors, we advance stated USDA research priorities. As we apply our expertise in hardware-accelerated computer vision, we will generate real time data that far exceeds the current status of aggregated population metrics. The ability to confirm identities in repeated encounters, track individual growth, behavioral engagement, and visual markers of stress or disease, should prove invaluable for optimizing the sustainability, resilience, and efficiency of production processes. Importantly, this data-driven approach will also provide managers an early warning system for detecting emerging stressors and biosecurity threats. We propose to complete three specific aims:Aim I. Identify individual animals using real-time biometric data. Recognizing individual animals without tagging is an enduring challenge that is exacerbated in aquatic environments because of the difficulty of obtaining detailed morphometrics from freely moving fish in densely populated aquaculture. First we derive a set of imaging and lighting conditions to significantly improve image quality over existing approaches. The initial research phase will situate our biometric scanner in a defined population of electronically tagged salmon for ground truthed verification of individual identities. For each fish transit we (1) capture a high-resolution image, (2) derive a comprehensive set of morphometrics, (3) cluster similarity in metrics across repeat transits, (4) construct a library with a set of individual identities, and (5) assess success of the derived classification against known identities (confirmed with PIT-tag data).Aim II. Visualize injury, health and stress in individuals using multispectral imaging. When humans blush, changes in blood flow result in noticeable changes in skin tone. A wide range of physiological, psychological, and mechanical stressors are known to affect color of the outermost integument of the animal. As a conservative first experimental approach, here we assess to what extent increased blood flow associated with minor skin injury can be detected with a ratiometric comparison across color bands, as a prelude to ultimately associating unique spectral signatures with particular pathologies and stress conditions.Aim III. Evaluate research outcomes of aims I and II at enterprise scale. Commercial RAS 'bluehouse' farms are complex environments with large populations of anonymous individuals. The ability to assign key parameters like growth, health, and wellbeing in real time to individual fish will offer a degree of insight that is currently unavailable to managers who seek to optimize operational outcomes. We will explore to what extent the solutions emerging in aims I and II can be implemented and contribute to decision making in a full-scale, commercial fish farm.
ADVANCED IMAGING TRANSFORMS RAS VIA INDIVIDUALIZED TRACKING OF SALMON GROWTH AND WELFARE
Objective
Investigators
Huber, R.
Institution
RADMANTIS LLC
Start date
2024
End date
2025
Funding Source
Project number
OHOW-2024-00152
Accession number
1031813