scholarly journals A High-Performance Optoelectronic Sensor Device for Nitrate Nitrogen in Recirculating Aquaculture Systems

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3382 ◽  
Author(s):  
Cong Wang ◽  
Zhen Li ◽  
Zhongli Pan ◽  
Daoliang Li
Keyword(s):  
Measurement Errors ◽  
High Performance ◽  
Nitrate Nitrogen ◽  
Living Environment ◽  
Environmental Stability ◽  
Correction Function ◽  
Synchronous Detector ◽  
Frequency Noise ◽  
Recirculating Aquaculture ◽  
Recirculating Aquaculture Systems

The determination of nitrate nitrogen (NO3-N) in recirculating aquaculture systems is of great significance for the health assessment of the living environment of aquatic animals. Unfortunately, the commonly used spectrophotometric methods often yield unstable results, especially when the ambient temperature varies greatly in the field measurement. Here, we have developed a novel handheld absorbance measurement sensor based on the thymol-NO3-N chromogenic rearrangement reaction. In terms of hardware, the sensor adopts a dual channel/dual wavelength colorimeter structure that features a modulated light source transmitter and a synchronous detector receiver. The circuit measures the ratio of light absorbed by the sample and reference containers at two LEDs with peak wavelengths at 420 nm and 450 nm. Using the modulated source and synchronous detector rather than a constant (DC) source eliminates measurement errors due to ambient light and low frequency noise and provides higher accuracy. In terms of software, we design a new quantitative analysis algorithm for absorbance by studying colloid absorbing behavior. The application of a buffer operator embedded in the algorithm makes the sensor get the environmental correction function. The results have shown that the sensitivity, repeatability, precision and environmental stability are higher than that by ordinary spectrophotometry. Lastly, we have a brief overview of future work.

scholarly journals Enriched Microbial Communities for Ammonium and Nitrite Removal from Recirculating Aquaculture Systems

2021 ◽  
Author(s):  
Alireza Neissi ◽  
Gholamreza Rafiee ◽  
Shadi Rahimi ◽  
Hamid Farahmand ◽  
Santosh Pandit ◽  
...  
Keyword(s):  
Microbial Communities ◽  
High Performance ◽  
Pathogenic Bacteria ◽  
Environmental Water ◽  
Recirculating Aquaculture ◽  
Expression Of Genes ◽  
Recirculating Aquaculture Systems ◽  
Nitrite Oxidizing Bacteria ◽  
Nitrite Removal ◽  
Aquaculture Water

Abstract Background: The aim of this study was the enrichment of high-performance microbial communities in biofilters for removal of ammonium and nitrite from aquaculture water. Methods: Ammonium oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) were enriched from different environmental water samples. The microbial communities with higher ammonium and nitrite removal activity were selected and adapted to different temperatures [9 ºC, 15 ºC, room temperature (25 ºC), and 30 ºC]. The expression of genes involved in nitrification including ammonia monooxygenase (AMO) and nitrite oxidoreductase (NXR) were measured in temperature-adapted AOB and NOB microbiomes. The microbial species present in the selected microbiomes were identified via 16s rRNA sequencing. Results: The microbial communities containing Nitrosomonas oligotropha and Nitrobacter winogradskyi showed the highest ammonium and nitrite removal activity at all temperatures used for adaptation. Furthermore, the microbial communities do not contain any pathogenic bacteria. They also exhibited the highest expression of AMO and NXR genes. Using the enriched microbial communities, we achieved a 288% and 181% improvement in ammonium and nitrite removal over the commonly used communities in biofilters at 9 °C, respectively. Conclusions: These results suggest that the selected microbiomes allowed for a significant improvement of water quality in a recirculating aquaculture system (RAS).

scholarly journals Computational Complexity Reduction of Neural Networks of Brain Tumor Image Segmentation by Introducing Fermi–Dirac Correction Functions

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 223
Author(s):  
Yen-Ling Tai ◽  
Shin-Jhe Huang ◽  
Chien-Chang Chen ◽  
Henry Horng-Shing Lu
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Computational Complexity ◽  
High Performance ◽  
Low Cost ◽  
Structural Complexity ◽  
Correction Function ◽  
Computational Time ◽  
Learning Methods ◽  
Band Theory

Nowadays, deep learning methods with high structural complexity and flexibility inevitably lean on the computational capability of the hardware. A platform with high-performance GPUs and large amounts of memory could support neural networks having large numbers of layers and kernels. However, naively pursuing high-cost hardware would probably drag the technical development of deep learning methods. In the article, we thus establish a new preprocessing method to reduce the computational complexity of the neural networks. Inspired by the band theory of solids in physics, we map the image space into a noninteraction physical system isomorphically and then treat image voxels as particle-like clusters. Then, we reconstruct the Fermi–Dirac distribution to be a correction function for the normalization of the voxel intensity and as a filter of insignificant cluster components. The filtered clusters at the circumstance can delineate the morphological heterogeneity of the image voxels. We used the BraTS 2019 datasets and the dimensional fusion U-net for the algorithmic validation, and the proposed Fermi–Dirac correction function exhibited comparable performance to other employed preprocessing methods. By comparing to the conventional z-score normalization function and the Gamma correction function, the proposed algorithm can save at least 38% of computational time cost under a low-cost hardware architecture. Even though the correction function of global histogram equalization has the lowest computational time among the employed correction functions, the proposed Fermi–Dirac correction function exhibits better capabilities of image augmentation and segmentation.

scholarly journals Anaerobic Mineralization of Recirculating Aquaculture Drum Screen Effluent for Use as a Naturally-Derived Nutrient Solution in Hydroponic Cropping Systems

Conservation ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 151-167
Author(s):  
Joseph Tetreault ◽  
Rachel Fogle ◽  
Todd Guerdat
Keyword(s):  
Nutrient Solution ◽  
Agricultural Waste ◽  
The United States ◽  
Anaerobic Treatment ◽  
Production Costs ◽  
Effluent Treatment ◽  
Limiting Factors ◽  
Fertilizer Treatment ◽  
Recirculating Aquaculture ◽  
Recirculating Aquaculture Systems

Operation and effluent treatment costs are limiting factors for the success of recirculating aquaculture systems (RAS) in meeting seafood demand in the United States. Adopting a capture-and-reuse waste management model similar to terrestrial agriculture farmers would allow RAS farmers to monetize effluent and offset production costs. The moisture content and nutrient profile of RAS effluent makes it a potential option for use as a hydroponic fertilizer. Treatment of RAS waste is needed to mineralize particulate-bound nutrients before becoming a viable hydroponic nutrient solution. Anaerobic treatment (AT), a method used by municipal and agricultural waste treatment facilities to reduce total solids, has been shown to successfully mineralize particulate-bound nutrients from RAS effluent. Continuously mixed anaerobic batch bioreactors were used to evaluate the degree to which AT may mineralize particulate-bound nutrients in solid RAS waste. Concentrations of twelve different macro- and micro-nutrients were analyzed in the waste before and after treatment. Effluent samples were analyzed to determine the fraction of each nutrient in the solid and aqueous forms. This study showed that AT is an effective method to mineralize particulate-bound nutrients in RAS effluent and the mineralization rate data may be used to design a pilot-scaled flow-through RAS effluent treatment system.

Microscreen effects on water quality in replicated recirculating aquaculture systems

2015 ◽  
Vol 65 ◽  
pp. 17-26 ◽  
Author(s):  
Paulo Fernandes ◽  
Lars-Flemming Pedersen ◽  
Per Bovbjerg Pedersen
Keyword(s):  
Water Quality ◽  
Recirculating Aquaculture ◽  
Recirculating Aquaculture Systems

The Water Quality Management for Recirculating Aquaculture System by Applying Nano Adsorption Technology

2021 ◽  
Vol 21 (7) ◽  
pp. 3975-3979
Author(s):  
Min-Jin Hwang ◽  
Jeongmin Cha ◽  
Eun-Sik Kim
Keyword(s):  
Water Quality ◽  
Water Quality Management ◽  
Reduction Rate ◽  
Fish Farming ◽  
Analytical Relationship ◽  
Pumice Stone ◽  
Recirculating Aquaculture ◽  
Recirculating Aquaculture Systems ◽  
Aquaculture Water

In a fish farm, the water quality is important to ensure fish growth and farm productivity. However, the study of the quality of water using in aquaculture has been ignored until now. Although there are several methods to treat water, nanomaterials have not yet been applied for indoor fish farming because it may difficult to supply a sufficient amount of water, and the operating parameters have not been developed for recirculating aquaculture systems. Nanotechnology can be applied to treat water, specifically through adsorption and filtration, to produce drinking water from surface water and to treat wastewater by processing a high volume of effluent. The adsorption and filtration of seawater has also progressed to allow for desalination of seawater, and this is recognized as a necessary tool for extended treatment protocols of various types of seawater. This study investigated the treatment of aquaculture water using nano-porous adsorbents (e.g., pumice stone) to control the contaminants in seawater in order to maintain the water quality required for aquaculture. The results are used to derive an analytical relationship between the ionic species in aquaculture water, and this provides empirical parameters for a batch reactor for aquaculture. The quality of the influent and effluent for aquaculture is compared using time-series analyses to evaluate the reduction rate of ionic components and thus suggest the optimum condition for fish farming using bioreactor processes.

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