{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T18:50:07Z","timestamp":1769885407138,"version":"3.49.0"},"reference-count":17,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T00:00:00Z","timestamp":1766016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012725","name":"TecNM (Mexico) project","doi-asserted-by":"publisher","award":["21802.25-P"],"award-info":[{"award-number":["21802.25-P"]}],"id":[{"id":"10.13039\/100012725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003141","name":"CONAHCYT (SECIHTI, Mexico) project","doi-asserted-by":"publisher","award":["CF-2023-I-724"],"award-info":[{"award-number":["CF-2023-I-724"]}],"id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Aquaculture monitoring increasingly relies on computer vision to evaluate fish behavior and welfare under farming conditions. This dataset was collected in a commercial recirculating aquaculture system (RAS) integrated with hydroponics in Queretaro, Mexico, to support the development of robust visual models for Nile tilapia (Oreochromis niloticus). More than ten hours of underwater recordings were curated into 31 clips of 30 s each, a duration selected to balance representativeness of fish activity with a manageable size for annotation and training. Videos were captured using commercial action cameras at multiple resolutions (1920 \u00d7 1080 to 5312 \u00d7 4648 px), frame rates (24\u201360 fps), depths, and lighting configurations, reproducing real-world challenges such as turbidity, suspended solids, and variable illumination. For each recording, physicochemical parameters were measured, including temperature, pH, dissolved oxygen and turbidity, and are provided in a structured CSV file. In addition to the raw videos, the dataset includes 3520 extracted frames annotated using a polygon-based JSON format, enabling direct use for training object detection and behavior recognition models. This dual resource of unprocessed clips and annotated images enhances reproducibility, benchmarking, and comparative studies. By combining synchronized environmental data with annotated underwater imagery, the dataset contributes a non-invasive and versatile resource for advancing aquaculture monitoring through computer vision.<\/jats:p>","DOI":"10.3390\/data10120211","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T16:42:05Z","timestamp":1766076125000},"page":"211","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Real-World Underwater Video Dataset with Labeled Frames and Water-Quality Metadata for Aquaculture Monitoring"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4267-4786","authenticated-orcid":false,"given":"Osbaldo","family":"Arag\u00f3n-Banderas","sequence":"first","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/ITS Regi\u00f3n de Los Llanos, Guadalupe Victoria 34700, Durango, Mexico"},{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Tijuana, Tijuana 22430, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1812-5736","authenticated-orcid":false,"given":"Leonardo","family":"Trujillo","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Tijuana, Tijuana 22430, Baja California, Mexico"},{"name":"LASIGE, Department of Informatics, Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5563-2692","authenticated-orcid":false,"given":"Yolocuauhtli","family":"Salazar","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Durango, Durango 34080, Durango, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guillaume J. V. E.","family":"Baguette","sequence":"additional","affiliation":[{"name":"Granja la Familia Tilapia, San Crist\u00f3bal 76246, Quer\u00e9taro, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9204-5860","authenticated-orcid":false,"given":"Jes\u00fas L.","family":"Arce-Valdez","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/ITS Regi\u00f3n de Los Llanos, Guadalupe Victoria 34700, Durango, Mexico"},{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Tijuana, Tijuana 22430, Baja California, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1093\/af\/vfae027","article-title":"Global issues in aquaculture","volume":"14","author":"Dunshea","year":"2024","journal-title":"Anim. Front."},{"key":"ref_2","unstructured":"FAO (2024). The State of World Fisheries and Aquaculture 2024\u2014Blue Transformation in Action, FAO."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"eabg0677","DOI":"10.1126\/sciadv.abg0677","article-title":"Animal welfare risks of global aquaculture","volume":"7","author":"Franks","year":"2021","journal-title":"Sci. Adv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"735508","DOI":"10.1016\/j.aquaculture.2020.735508","article-title":"Automatic recognition methods of fish feeding behavior in aquaculture: A review","volume":"528","author":"Li","year":"2020","journal-title":"Aquaculture"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1080\/23308249.2021.1886240","article-title":"Engineering design of aquaponics systems","volume":"30","author":"Colt","year":"2021","journal-title":"Rev. Fish. Sci. 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