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Article

Modelling the nitrogen loadings from large yellow croaker (Larimichthys crocea) cage aquaculture

Citation
Cai H, Ross L, Telfer T, Wu C, Zhu A, Zhao S & Xu M (2016) Modelling the nitrogen loadings from large yellow croaker (Larimichthys crocea) cage aquaculture. Environmental Science and Pollution Research, 23 (8), pp. 7529-7542. https://doi.org/10.1007/s11356-015-6015-0

Abstract
Large yellow croaker (LYC) cage farming is a rapidly developing industry in the coastal areas of the East China Sea. However, little is known about the environmental nutrient loadings resulting from the current aquaculture practices for this species. In this study, a nitrogenous waste model was developed for LYC based on thermal growth and bioenergetic theories. The growth model produced a good fit with the measured data of the growth trajectory of the fish. The total, dissolved and particulate nitrogen outputs were estimated to be 133, 51 and 82kgNtonne−1of fish production, respectively, with daily dissolved and particulate nitrogen outputs varying from 69 to 104 and 106 to 181mgNfish−1, respectively, during the 2012 operational cycle. Greater than 80% of the nitrogen input from feed was predicted to be lost to the environment, resulting in low nitrogen retention (85%) of the dissolved nitrogen generated from cage farming. This nitrogen loading assessment model is the first to address nitrogenous output from LYC farming and could be a valuable tool to examine the effects of management and feeding practices on waste from cage farming. The application of this model could help improve the scientific understanding of offshore fish farming systems. Furthermore, the model predicts that a 63% reduction in nitrogenous waste production could be achieved by switching from the use of trash fish for feed to the use of pelleted feed.

Keywords
Dynamic modelling; Large yellow croaker; Nitrogen loadings; Ammonia; Urea; Cage aquaculture

Journal
Environmental Science and Pollution Research: Volume 23, Issue 8

StatusPublished
Author(s)Cai, Huiwen; Ross, Lindsay; Telfer, Trevor; Wu, Changwen; Zhu, Aiyi; Zhao, Sheng; Xu, Meiying
Publication date30/04/2016
Publication date online05/01/2016
Date accepted by journal22/12/2015
URLhttp://hdl.handle.net/1893/24078
PublisherSpringer
ISSN0944-1344
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