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Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model

In this study, we developed a feeding simulation using the fish schooling behavior model to evaluate growth differences from the feeding spatial distribution. In the proposed simulation, feeding behavior was modeled using the fish schooling model to simulate the amount of feed consumed by each indiv...

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Autores principales: Takahashi, Yuki, Komeyama, Kazuyoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894463/
https://www.ncbi.nlm.nih.gov/pubmed/36730228
http://dx.doi.org/10.1371/journal.pone.0280017
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author Takahashi, Yuki
Komeyama, Kazuyoshi
author_facet Takahashi, Yuki
Komeyama, Kazuyoshi
author_sort Takahashi, Yuki
collection PubMed
description In this study, we developed a feeding simulation using the fish schooling behavior model to evaluate growth differences from the feeding spatial distribution. In the proposed simulation, feeding behavior was modeled using the fish schooling model to simulate the amount of feed consumed by each individual. Next, body mass growth was calculated based on the amount of feed consumed. A 3.0-m diameter aquaculture tank was used for the simulation. We used three feeding methods to evaluate how feeding distribution affected growth: Feeding A, B, and C. The feed was distributed in a square pattern with one side length of 1.5, 1.0, or 0.5 m for Feeding A, B, and C groups, respectively. The results revealed that individual differences in body mass resulting from each feeding method differed greatly. The individual difference was largest in the Feeding C group. Here, maximum swimming speed was assumed to be proportional to total length. The feeding area of Feeding C was narrow; therefore, the first individual to arrive in the feeding area dominated the feed. Large individuals accessed the feed more easily than did small individuals. Consequently, the growth of large individuals became more rapid, and the individual differences became large in Feeding C. A rearing test can be conducted in a short time, and the optimal aquaculture operation was easily determined using the proposed simulation method. We concluded that the proposed simulation is useful as a decision-making tool for aquaculture management.
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spelling pubmed-98944632023-02-03 Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model Takahashi, Yuki Komeyama, Kazuyoshi PLoS One Research Article In this study, we developed a feeding simulation using the fish schooling behavior model to evaluate growth differences from the feeding spatial distribution. In the proposed simulation, feeding behavior was modeled using the fish schooling model to simulate the amount of feed consumed by each individual. Next, body mass growth was calculated based on the amount of feed consumed. A 3.0-m diameter aquaculture tank was used for the simulation. We used three feeding methods to evaluate how feeding distribution affected growth: Feeding A, B, and C. The feed was distributed in a square pattern with one side length of 1.5, 1.0, or 0.5 m for Feeding A, B, and C groups, respectively. The results revealed that individual differences in body mass resulting from each feeding method differed greatly. The individual difference was largest in the Feeding C group. Here, maximum swimming speed was assumed to be proportional to total length. The feeding area of Feeding C was narrow; therefore, the first individual to arrive in the feeding area dominated the feed. Large individuals accessed the feed more easily than did small individuals. Consequently, the growth of large individuals became more rapid, and the individual differences became large in Feeding C. A rearing test can be conducted in a short time, and the optimal aquaculture operation was easily determined using the proposed simulation method. We concluded that the proposed simulation is useful as a decision-making tool for aquaculture management. Public Library of Science 2023-02-02 /pmc/articles/PMC9894463/ /pubmed/36730228 http://dx.doi.org/10.1371/journal.pone.0280017 Text en © 2023 Takahashi, Komeyama https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Takahashi, Yuki
Komeyama, Kazuyoshi
Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title_full Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title_fullStr Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title_full_unstemmed Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title_short Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
title_sort development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894463/
https://www.ncbi.nlm.nih.gov/pubmed/36730228
http://dx.doi.org/10.1371/journal.pone.0280017
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