Mathematical Modeling of the Growth of Chinese Shrimp (Fenneropenaeus chinensis) in High Density Stocking Pond

DOI

10.2991/msbda-19.2019.2How to use a DOI?

Keywords

Fenneropenaeus chinensis, simulated modeling, shrimp aquaculture, sensitivity parameter

Abstract

Shrimp aquaculture is evolving from traditional open low stocking density to closed high stocking density in China. However, high density closed stocking ecosystem with eutrophication deteriorates the stocking environment of shrimps. A dynamic model simulating the growth of Chinese shrimps (Fenneropenaeus chinensis) was constructed based on the experimental data on field shrimp stocking to simulate and reflect the relationship among shrimp growth, pond ecosystem and artificial control to predict the potential risks and intervention of artificial control in macroscopic view in the production of shrimps in high density stocking pond using the ecological modeling software STELLA® 5.1.1. Seven growth parameters of shrimp were established; of which, two sensitive parameters, manual feeding and water temperature, were identified after parameter sensitivity test by Single Factor Analysis. The model was verified experimentally in the field. The model demonstrated that the growth of Fenneropenaeus chinensis was successfully simulated in a 90-day stocking circle in a high density pond. The two sensitive parameters indicated that the handling and manipulation of the manual feeding at different water temperature directly influenced the shrimp growth and production.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuepeng Su
AU  - Kuopeng Cui
AU  - Shen Ma
AU  - Shuanglin Dong
AU  - Meiyi (Daphne) Wu
PY  - 2019/08
DA  - 2019/08
TI  - Mathematical Modeling of the Growth of Chinese Shrimp (Fenneropenaeus chinensis) in High Density Stocking Pond
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
PB  - Atlantis Press
SP  - 6
EP  - 14
SN  - 2352-538X
UR  - https://doi.org/10.2991/msbda-19.2019.2
DO  - 10.2991/msbda-19.2019.2
ID  - Su2019/08
ER  -