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The measurement of sturgeon mass plays a remarkable role in aquaculture management. Furthermore, the measurement of sturgeon mass serves as a key phenotype, offering crucial information for enhancing growth traits through genetic improvement. Until now, the measurement of sturgeon mass is usually conducted by manual sampling, which is work intensive and time consuming for farmers and invasive and stressful for the fish. Therefore, a noninvasive volume reconstruction model for estimating the mass of swimming sturgeon based on RGB-D sensor was proposed in this paper. The volume of individual sturgeon was reconstructed by integrating the thickness of the upper surface of the sturgeon, where the difference in depth between the surface and the bottom was used as the thickness measurement. To verify feasibility, three experimental groups were conducted, achieving prediction accuracies of 0.897, 0.861, and 0.883, which indicated that the method can obtain the reliable, accurate mass of the sturgeon. The strategy requires no special hardware or intensive calculation, and it provides a key to uncovering noncontact, high-throughput, and highly sensitive mass evaluation of sturgeon while holding potential for evaluating the mass of other cultured fishes.<\/jats:p>","DOI":"10.3390\/s24155037","type":"journal-article","created":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T13:57:28Z","timestamp":1722866248000},"page":"5037","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Nonintrusive and Effective Volume Reconstruction Model of Swimming Sturgeon Based on RGB-D Sensor"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9017-9638","authenticated-orcid":false,"given":"Kai","family":"Lin","sequence":"first","affiliation":[{"name":"Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China"},{"name":"Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Ministry of Agriculture and Rural Affairs, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4806-8982","authenticated-orcid":false,"given":"Shiyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Opto Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China"}]},{"given":"Junjie","family":"Hu","sequence":"additional","affiliation":[{"name":"Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China"},{"name":"School of Instrument Science and Opto Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China"}]},{"given":"Hongsong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Wenzhong","family":"Guo","sequence":"additional","affiliation":[{"name":"Intelligent Equipment Technology Research Center of Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China"}]},{"given":"Hongxia","family":"Hu","sequence":"additional","affiliation":[{"name":"Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China"},{"name":"Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Ministry of Agriculture and Rural Affairs, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"737299","DOI":"10.1016\/j.aquaculture.2021.737299","article-title":"Estimation of genetic parameters for growth and egg related traits in Russian sturgeon (Acipenser gueldenstaedtii)","volume":"546","author":"Song","year":"2022","journal-title":"Aquaculture"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yan, X., Dong, Y., Dong, T., Song, H., Wang, W., and Hu, H. 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