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Sustainable aquaculture requires environmental‐friendly treatment strategies for fish diseases
Open accessAbstract
Many classical therapeutants are going to be banned in Europe, and an urgent need for alternatives is emerging. This issue can be exemplified by one major parasitic disease in aquaculture and ornamental fish breeding: velvet disease. This disease, caused by dinoflagellates of the genera Amyloodinium and Piscinoodinium, is an important infection affecting cultured freshwater and marine ornamental and food fish, and consistently causes great financial loss to the associated industries. Therapeutants available contain copper, malachite green, or methylene blue, and which can be toxic to non‐target organisms in the surrounding environment. As a result, these chemicals are banned for use by the aquaculture industry in several countries, and a prohibition for commercial ornamental fishkeeping is likely to follow in most countries. Increasing development of resistance to therapeutants, and growing public awareness for animal welfare and environmental protection, have prompted research in the areas of alternative treatment options and immunostimulants. Hydrogen peroxide and peracetic acid are possible ‘green’ therapeutants which do not contribute residues to the environment. Natural feed supplements such as pre‐ and probiotics can increase animal welfare and prevent stress and/or infections. Humic substances are another promising, natural immunostimulants which will be considered in depth. The aim of this review is to provide an overview of risks and benefits of current treatment options and new approaches to replace harmful therapeutants and minimize the number of toxic residues discharged into the environment. Treatments will be discussed on various parasitic infections and focus, where available, on Amyloodinium and Piscinoodinium.
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Bliznakov, E. G., & Adler, A. D. (2008) · Pathologia et Microbiologia · doi:10.1159/000162456 · Cited by 37
Modulation of stress and innate immune response by corticosteroids in pacu (Piaractus mesopotamicus)
Zanuzzo, F. S., Sabioni, R. E., Marzocchi-Machado, C. M., & Urbinati, E. C. (2019) · Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology · doi:10.1016/j.cbpa.2019.01.019 · Cited by 35
Gau, R., Yang, H., Chow, S., Suen, J., & Lu, F. (2000) · Toxicology and Applied Pharmacology · doi:10.1006/taap.2000.8954 · Cited by 33
Won, K.-M., KIM, P. K., Lee, S. H., et al. (2008) · Fisheries Science · doi:10.1111/j.1444-2906.2008.01568.x · Cited by 27
Negm, R. M. K., Cobcroft, J. M., Brown, M. R., et al. (2013) · Aquaculture · doi:10.1016/j.aquaculture.2013.11.008 · Cited by 16
Metadata
- Authors
- Lieke, T., Meinelt, T., Hoseinifar, S. H., Pan, B., Straus, D. L., & Steinberg, C. E. W.
- Venue
- Reviews in Aquaculture
- Publisher
- Wiley
- Published
- 2019-07-23
- Volume
- 12
- Issue
- 2
- Pages
- 943-965
- ISSN
- 1753-5123 (ISSN-L)
- 1753-5131
- OpenAlex
- W2963862221
- Cited by
- 363
- References
- 121
- FWCI
- 9.21
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.