An intelligent IoT-based control and traceability system to forecast and maintain water quality in freshwater fish farms

2019 ◽  
Vol 166 ◽  
pp. 105013 ◽  
Author(s):  
Guandong Gao ◽  
Ke Xiao ◽  
Miaomiao Chen
1995 ◽  
Vol 31 (10) ◽  
pp. 73-84 ◽  
Author(s):  
T. M. Iversen

The main environmental problems associated with fish farming in Denmark are attributable to the dam, the “dead reach” and nutrient and organic matter discharge. The environmental regulation of fish farming in Denmark started with the Environmental Protection Act of 1974, the Statutory Order of 1985 forbidding wet feed, and the Action Plan on the Aquatic Environment of 1987. In the case of freshwater fish farms, the latter was implemented through the measures stipulated in the 1989 Statutory Order on Fish Farms. The impact of Danish legislative measures to reduce and regulate the environmental effects of freshwater fish farms can be summarized as follows: - the number of fish farms has been reduced from about 800 in 1974 to about 500 at present; - production has tripled since 1974 and has been stable since 1989; - a change from wet to dry feed has reduced the environmental impact of the farms; - the national goals of the Action Plan on the Aquatic Environment of 1987 for reducing fish farm discharges of organic matter, nitrogen and phosphorus have been fulfilled. The main remaining problems are that: - the local impact of fish farms on downstream stream quality is still much too high in about 15% of cases; - the problem of the passage of migrating invertebrates and fish is still unsolved at some farms; - the problems posed by “dead reaches” are still unsolved. It is concluded that sustainable fish farming is possible in Denmark, but with the present technology production will have to be significantly reduced.


2020 ◽  
Vol 41 (2) ◽  
pp. 105
Author(s):  
Javier Fernando Melo-Bolívar ◽  
Ruth Yolanda Ruiz-Pardo ◽  
Michael E Hume ◽  
Hanna E Sidjabat ◽  
Luisa Marcela Villamil-Diaz

Probiotic products are viewed as an alternative to the use of antibiotics in freshwater fishes farming. Probiotic organisms include bacteria, yeast, and filamentous fungi offering different benefits to fish including growth promotion, inhibition of pathogen colonisation, and improvement of nutrient digestion, water quality, and stress tolerance, as well as enhancement of reproduction. For these reasons, this review aims to identify the main trends in probiotic amendment in freshwater fishes. Strategies to incorporate the probiotic strains in the fish feed or pellets to allow optimal viability of the strains as they reach the fish gastrointestinal tract (GIT) are crucial in probiotic research and commercial applications for freshwater fish.


2019 ◽  
Vol 23 (2) ◽  
Author(s):  
Victoria Quimpang ◽  
◽  
Maricris Cudal ◽  
Einstine Opiso ◽  
Romeo Tubongbanua, Jr. ◽  
...  

freshwater fish, introduced, native, turbidity, water quality


2011 ◽  
Vol 102 (4) ◽  
pp. 329-340 ◽  
Author(s):  
B.C. Oidtmann ◽  
C.N. Crane ◽  
M.A. Thrush ◽  
B.J. Hill ◽  
E.J. Peeler
Keyword(s):  

2021 ◽  
Author(s):  
Amandine Declerck ◽  
Matthias Delpey ◽  
Thibaut Voirand ◽  
Ioanna Varkitzi

<p>Keywords: eutrophication; high resolution ocean modeling ; Chla satellite data ; biogeochemistry</p><p>Maliakos Gulf corresponds to mesotrophic waters that can reach eutrophic conditions and are occasionally subject to Harmful Algal Blooms (HAB) (Varkitzi et al. 2018). At the same time, it is an important fish farming and aquaculture production area. A large issue is thus related to the monitoring and forecasting of the risk of occurrence of algae blooms in the Gulf. For this purpose, the present study couples predictions from a high-resolution numerical ocean model with satellite observation to improve the monitoring and anticipation of threats for the local fish farms induced by occasional eutrophication.</p><p>This solution is developed in the frame of the MARINE-EO project (https://marine-eo.eu/). It combines satellite observation with high-resolution ocean modelling to provide detailed information as a support to fish farms management and operations. It is implemented in an operational platform, which provides continuous information in real time as well as short term predictions. The deployed solution uses CMEMS physical products as an input data and offers to refine this solution in order to provide a local information on site using a downscaling strategy. High resolution satellite products and ocean modelling allow to include the impact of local coastal processes on currents and water quality parameters to provide a proper monitoring and forecasting solution at the scale of a specific fish farm.</p><p>To model specific eutrophication processes, a NPZD (Nutrients-Phytoplankton-Zooplankton-Detritus) biogeochemical model is used. Included in the MOHID Water modelling system, the water quality module (Mateus, 2006) considering 18 properties: nutrients and organic matter (nitrogen, phosphorus and silica biogeochemical cycles), oxygen and organisms (phytoplankton and zooplankton) was deployed in the western Aegean Sea. The simulated chlorophyll a concentrations are used to compute a risk level for the eutrophication occurrence. To complete this indicator, another risk level was based on the eutrophication variation following Primpas et al. (2010) formulation. In addition to model forecasts, ocean color observations from the Sentinel-2 MSI and Landsat-8 OLI sensors are used to provide high resolution chlorophyll a concentrations maps in case of bloom events. The processing chain uses the sixth version of the Quasi-Analytical Algorithm initially developed by Lee et al. (2002) and an empirical relation based on a database built using the HydroLight software to compute chlorophyll a concentration.</p><p>Two past eutrophication events monitored in situ (Varkitzi et al. 2018) were studied to assess the accuracy of the developed tool. Although few in situ data were available on environmental input (as rivers flow and nutrient concentrations), it was possible using statistics to reproduce qualitatively these blooms. Finally, an operational demonstration was conducted during 2 months of the 2020 autumn season, to showcase real time monitoring and predictive perspectives.</p>


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