In the scene of monitoring fishing boat targets at the high point of the fishing port, a fishing vessel target detection model based on improved yolov5 is proposed to solve the problems of frequent loss and detection error of fishing vessel detection. Firstly, the anchor frame is re-clustered by the Kmeans++ algorithm, and the anchor frame size suitable for the fishing vessel data set is selected; Then, the weighted bidirectional feature pyramid network (BiFPN) is used to replace the original Feature Pyramid Networks (FPN) + Pixel Aggregation Network (PAN) structure for fast multi-scale feature fusion; Finally, the detection scale of large targets is removed, the detection scale of smaller targets is added, and three new detection scales are used to improve the detection accuracy of the model for small target fishing vessels. The results show that compared with the original yolov5 algorithm, the accuracy, recall and average accuracy of the improved algorithm are improved by 29.5%, 0.5% and 4.5% respectively, and the number of detection frames per second reaches 90.6, which greatly improves the effect of fishing boat target detection.The research shows that the improved yolov5 algorithm meets the accuracy and real-time requirements of fishing vessel target detection during the fishing moratorium.

Aiming at the problems of small sample size and low detection accuracy of diseased takifugu rubripes, a detection method of diseased takifugu rubripes based on ResNet50 and migration learning was proposed. First, ResNet50 was used to pre-train the model on the ImageNet dataset; then based on the pre-training results, the takifugu rubripes detection ResNet50 network was constructed, and the model weights, which were pre-trained and contained in 16 residual blocks, were transferred to the ResNet50 network for model weight initialization to reduce the training cost; in order to further improve the accuracy of detection, a deconvolution layer was added after the last convolution layer of the constructed ResNet50 network model to learn the details of the target; finally, the data set was constructed from the images of healthy and diseased takifugu rubripes, and the data was augmented using methods such as flipping, rotation, random cropping, chromaticity changes, and adding noise to increase the diversity of data samples and improve the robustness of the detection method. Experiments were conducted on the constructed dataset, the accuracy of the detection method for disinfected puffer fish based on ResNet50 and transfer learning can reach 99%. Compared with ResNet18, ResNet34, ResNet101 and ResNet152, the detection accuracy of the proposed method was improved by 10.7%, 6.6%, 6.2% and 5.6% respectively. Compared with the ResNet50 residual network without deconvolution, the detection accuracy of the proposed method was improved by 0.4%. The results showed that the method based on ResNet50 and transfer learning could effectively solve the problems of fewer samples and low accuracy of diseased puffer fish, and provide a reference for the study of diseased puffer fish detection

Aiming at the degradation of the visual quality of underwater images and the low feature utilization of a single convolutional layer, an underwater image enhancement model based on multi-scale feature extraction is proposed. The model uses the improved multi-scale feature extraction module to extract underwater image features based on the convolutional neural network. First, a separable residual dense block (SRDB) is constructed as the basic feature extraction unit, and the SRDB module is used for residual dense connection to obtain multi-level feature information, and finally merge the multi-level feature information under three different initial receptive fields as the output of this module. Multiple sets of experimental results show that the enhanced underwater image of the model effectively improves the color distortion and low contrast while maintaining rich edge details; The PSNR and SSIM on the EUVP test set rose to 28.52 and 0.88, respectively, and the UIQM and NIQE on the real pufferfish image test set rose to 2.84 and 5.95, respectively, outperforming the comparison methods. Research shows that this model has a high FPS, which greatly improves the visual perception quality of underwater images while maintaining good real-time performance.

During fish farming, the number of fish in the ponds needs to be monitored regularly. Aiming at the problem of missing detection in the existing methods, this paper proposed a local optimization method based on the YOLOv5s model and a fish quantity statistics method with an improved output scale. By adding local information such as the head and tail of the detected fish, the category with the largest number was selected from the three categories of the whole body, head, and tail of the fish as the result of quantitative statistics to solve the problem of missing detection. At the same time, for the case that the whole body, head, and tail of fish were displayed as large-scale or mesoscale targets in the image, the feature output of these two types of targets was increased to improve the target detection ability of the model, so that the model can be suitable for quantitative detection under the current conditions. The results showed that compared with manual counting, the error of the quantity counted by this method was small, the accuracy was 96.3%, and the detection frame rate was 111 FPS. Based on the YOLOv5 model, the application of local optimization strategy increased the number of statistics by 37.4%, and the improvement of output scale increases the number of statistics by 4.9%. The study can be applied to the statistics of fish stocks in fishery and fish detection.

 Real-time detection and acquisition of the health status of farmed fish is one of the key technologies for large-scale fish farming to achieve accurate, green and sustainable development, among which, real-time identification of sick and dead fish and timely collection and treatment can constrain aquaculture water contamination, prevent disease spreading and reduce breeding risks. However, in a complex shoal environment, such as changes in illumination, overlapping targets, unstable positions, and blurring caused by water fog, it is very challenging to identify and collect sick and dead golden pomfrets in time. In this paper, an improved algorithm based on YOLOv4 is proposed. A custom Super network is integrated in the PaNet module, and the input feature is encoded and decoded to reduce the interference caused by the external environment in the fine-grained feature extraction. In addition, the activation of the tanh-v1 function enhances feature propagation and ensures the maximum information flow in the network. The Resblockbody1 module is simultaneously used to improve the positioning accuracy of the target frame. In the shoal farming scene, by analyzing the images of dead golden pomfrets and comparing the test results on different models, the YOLOv4-v1 network identified an  value of dead golden pomfrets as high as 98.31%, and the real-time detection performance reached 27FPS. Through the comparison experiment with the YOLOv4 network, YOLOv4-v1 algorithm has a basically same detection speed to the original network in the offline experiment, while the value is increased by 3.36%, the R rate increased by 2.54%, and the score (the balance between precision and recall) enhanced by 0.56%. It can be seen that the YOLOv4-v1 method has a good application potential in dead fish identification.

Aquaponics is a technology which uses aquaculture effluent to provide nutrients for plants. It produces two crops (fish and plants) from one nitrogen source (fish feed), with such characteristics as efficient use of water and nitrogen sources, no use of fertilizers and antibiotics, and environmental friendliness, which make it a sustainable way of agricultural development. This paper divides the historical process of aquaponics into four stages: the origin stage (before 1970), the beginning stage (1970-1990), the global expansion stage (1990-2010) and the rapid growth stage (2010-present), analyzes three typical systems of aquaponics, proposes the three main developing trends of aquaponics: system construction towards uncoupled, system layout towards urbanized and three-dimensional and hardware facility towards ecological and intelligent, and puts forward four suggestions for development: strengthening the research on the transformation mechanism of nitrogen and phosphorus, building a theoretical model of the system, strengthening the application of artificial intelligence technology, and strengthening the research on commercial-scale systems.

With the development of mariculture moving to the deep sea, mariculture equipment will face worse sea conditions. To ensure the safety of the equipment, it is necessary to evaluate the safety of its anchoring system. Using the traditional hydrodynamic calculation and analysis method, the accurate mooring system tension can be obtained, but the calculation time is very long. To quickly obtain the tension distribution of the mooring system of the aquaculture platform under bad sea conditions, a calculation model for the prediction and evaluation of the mooring force of the aquaculture platform (ssa-bp model) is constructed based on the machine learning method. The sparrow search algorithm is introduced into the model to optimize the weight and threshold of the BP neural network, which improves the prediction performance of the model. The model takes the regular wave height, period, and velocity as the model input index and the mooring line force as the model output index to train the BP prediction model. The sparrow search algorithm is used to optimize and train the BP model (ssa-bp model), and the prediction results of the improved ssa-bp model are compared with those of the traditional BP model. Through comparative analysis, it is found that the overall indicators of ssa-bp model are lower than the BP model, and the prediction error of the mooring force of ssa-bp model under various working conditions is also lower than the BP model and closer to the real value. Finally, it is concluded that the new ssa-bp model can give more accurate prediction results.

In order to solve the problem of feed waste and water pollution in the process of aquaculture, the study of fish feeding behavior has been paid much attention by the majority of researchers. Quantifying fish feeding behavior, extracting available parameters, and constructing a precise model are the effective ways to optimize feeding strategy. This paper summarized the main foraging sensory organs, quantitative indexes of predation and the characteristics of acoustic signals during feeding, and summarized the environmental factors that affect feeding behavior in the period of cultivation. The research progress, advantages and disadvantages of the two monitoring technologies were compared and analyzed, including computer vision based on visible and near-infrared light, and acoustic technology based on acoustic monitoring and sonar imaging. In view of the existing problems, this paper proposed methods to improve the feeding model accuracy and universality, and research potential and direction of passive acoustics, so as to provide reference for the intelligent feeding system.

The net will be contaminated by marine animals and plants and other biofouling in the process of deep-water cage culture, which will affect the water exchange in the cages and is not conducive to the growth and survival of cultured fish. In addition, the contamination of biofouling can cause the weight of the net to increase, thus making it easy to damage the culture equipment. The present paper, based on the analysis of domestic and foreign cage cleaning device and research status quo, compared the technical characteristics of mobile underwater cage cleaning device, tide power type cage cleaning device and underwater cleaning robot, and put forward the future development direction of cage cleaning technology and device with the development of big data and other emerging technologies.

In the process of tuna seiners seeking tuna schools, it incurs high cost of fuel, manpower and material resources. Currently, it has become a common concern to improve fish searching efficiency and reduce the fish catches cost. In this study, computer video intelligent aided analysis and recognition program based on YOLOv3 model was used to realize the automatic identification of tuna shoal characteristics, thus to reduce the time of finding fish and improve fishing efficiency. A characteristic data set of tuna shoal was constructed by pre-processing the characteristic video provided by the Shanghai Kaichuang Deep Sea Fishing Co. LTD and the data set was trained for recognition. The trained model was deployed on a computer with an inference task for simulation identification of tuna shoal. The results show that the recognition accuracy of the simulation was 68.6%. The study proves that the YOLOv3 based characteristic recognition model has a practical application value in the forecast of tuna fishing conditions, and the study results could be referred to for future tuna shoal features recognition.

According to the "Montreal Protocol", the R22 used in the refrigeration system of fishing vessels needs to be banned before 2030 due to its effect on the depletion of the ozone layer. Therefore, it is imminent to find an ideal alternative refrigerant. By screening and proportioning the components of the mixed refrigerants, it can not only meet the refrigeration requirements, but also meet the environmental requirements, and become the mainstream trend to replace traditional refrigerants. In this paper, a single-stage self-cascading refrigeration system is designed, and the chemical process simulation software is used to carry out the application substitution research of mixed refrigerants. Based on the characteristics of the self-cascading refrigeration system and the thermophysical properties of the mixed refrigerants, R14, R23, R134a, and R245fa, were selected for the target temperature zone of -65 ℃, which were composed of binary, ternary, and quaternary mixed refrigerants respectively. For the self-cascading refrigeration system, the thermodynamic calculation and analysis of binary, ternary and quaternary mixed refrigerants under different components and different concentrations were carried out. The results show that the refrigeration system with quaternary mixed refrigerants is better than that with binary and ternary mixed refrigerants. When the ratio of quaternary refrigerant components is R14/R23/R134a/R245fa (0.35/0.36/0.1/0.19), the COP of the refrigeration system could reach 1.037, the exhaust pressure and the suction pressure are 1590 kPa and 740 kPa respectively, the pressure ratio is less than 3, and the exhaust temperature is only 61℃. Compared with the traditional R22 refrigeration system, the COP of the mixed refrigerant system is close to the traditional R22 refrigeration system. In terms of volume refrigeration efficiency, the suction flow rate is only 26.56% of the first-stage suction flow rate of the R22 refrigeration system, which can reduce the size of the compressor in the system, making the system simpler and more cost-effective. Therefore, the new mixed refrigerants of R14/R23/R134a/R245fa have the potential to replace the traditional refrigerants of R22.

In recent years, China’s aquaculture industry has developed rapidly, and aquatic animal feeding strategies have gradually received attention. A series of related research contents of aquatic animal feeding strategies at home and abroad are enumerated and analyzed for systematic arrangement and summary. Feeding strategies are important production management factor in modern intensive aquaculture production process. Its technical connotation can be summarized as feeding frequency, feeding amount and feeding mode, etc. Different aquatic animal species and different breeding stages require different feeding strategies. The effects of feeding strategies on the growth performance, digestion and metabolism, stress immunity, behavioral response and survival rate of farmed animals are described to provide a reference for the selection of aquatic animal feeding strategies and the research on related technical theories.

In order to further explore the purification effect of seawater constructed wetland on marine aquaculture wastewater under different hydraulic conditions, the integrated vertical-flow constructed wetland was selected to treat the wastewater of Paralichthys olivaceus farming, and three HRTs (1.5h, 3.0h, 4.5h) were set under three levels of HLR (20m/d、40m/d、100m/d) to explore the removal effects of constructed wetland on nitrogen, phosphorus, COD and other main pollutants in mariculture wastewater. The relationship between microbial community structure and denitrification was analyzed by high-throughput sequencing technology. The results showed that the seawater constructed wetland system had nice effects in nitrogen and phosphorus removing, the removal rates of DIN, PO43--P and COD decreased with the increase of HLR, and the effect of HLR on DIN removal rate is greater than that of PO43--P and COD. Extending HRT could improve the removal rates of DIN, PO43--P and COD, especially on the removal rate of DIN. The discharge standard of DIN、PO43--P and COD could be met when the HLR is 20 m/d and HRT 4.5 h. Environmental conditions such as pH affect the distribution of microorganisms in constructed wetlands, and thus affect the nitrogen removal efficiency of constructed wetlands. This study provides theoretical and technical reference for the efficient purification of mariculture wastewater by constructed wetlands.

Ultraviolet light-emitting diode (UV-LED, 200-400nm) semiconductor solid-state light source is energy saving, environmentally friendly, easy to operate and small in volume. With the continuous improvement of UV-LED performance, it is expected to replace the traditional ultraviolet mercury light source in the future. This paper first introduces the development of ultraviolet (UVC-LED, 200-280 nm,) technology, the existing problems and the route for technical improvement, and compares the research results of UVC in aquaculture industry at home and abroad. Then, based on the species of microbial diseases in aquaculture, the calculating method of the dose needed to inactivate harmful microbes and the design suggestion for actual application of UVC-LED in aquacultural microenvironment are given. Finally, the trend of UVC-LED to achieve large-scale application of sterilization is prospected, so as to help the sustainable development of aquaculture.

Antarctic krill has large resources, high nutritional value, and a variety of active substances. It is a type of offshore fishery resource with great development value. Shrimp meal is one of the most important processed products of Antarctic krill. During the processing, due to the influence of heating and other factors, it will cause the loss of nutrients and the destruction of active substances, especially in the heat treatment links such as cooking and drying. Tends to destroy or degrade heat-sensitive components such as unsaturated fatty acids and astaxanthin. The characteristics of the main nutritional active substances of Antarctic krill such as protein, lipid, and astaxanthin and their changes in the process of shrimp meal processing were introduced, the influence of processing procedures and process parameters on the quality of shrimp meal was analyzed, the main evaluation indicators and basis of shrimp meal quality were summarized, The main problems in the processing of shrimp meal, such as unclear process, poor equipment performance and unstable product quality, were discussed, and the future research directions such as the flow path of nutrient active substances, structural change mechanism, process optimization, equipment innovation, technology, and equipment integration, etc. It is expected to provide a theoretical basis and technical reference for the optimization of the process and technology of shrimp meal processing.

Fish object detection is of great significance for precision aquaculture, production automation, resource investigation and fish behavior research. In order to get the position and category of fish object quickly and accurately, a fish object detection method based on improved model YOLO V4 is proposed, Based on the CIoU(complete intersection over union) loss function, a new loss term is constructed. The improved loss function makes the real box and the intersecting box regress in the same aspect ratio. At the same time, the detection effect on a specific size and area is enhanced by setting a multi anchor box mode. The results show that the mAP (mean average precision) of the improved model YOLO V4 is greatly improved compared with the original model. The mAP on the self built data set, data set Fish4 knowledge and data set NCFM reaches 94.22%, 99.52% and 92.16% respectively. The research shows that the improved model YOLO v4 can quickly and accurately detect the position and category of fish, and the detection speed meets the real-time requirements, which can provide a reference for precision aquaculture of fishery.

The data obtained from the breeding environment has defects such as blurring and occlusion, rendering poor detection of the farmed fish. To solve the above problem, the farmed fish detection model ESB-YOLO (ECBAM-SPPF-BiFPN-YOLO), based on a non-channel-downscaling attention mechanism (ECBAM) and improved YOLOv5, is proposed. ECBAM is adopted to obtain more detailed features. To alleviate the slowdown of detection speed caused by adopting ECBAM, SPPF is used to replace SPP to reduce model computation, decrease model detection time, and improve detection speed. BiFPN is used to perform weighted feature fusion to enhance feature fusion by increasing the proportion of functional features and reducing feature loss. To verify the effectiveness of the proposed modified module for YOLOv5, ablation tests were designed. The test results show that the average precision of ESB-YOLO is improved by 2.40% compared with YOLOv5 while maintaining a similar detection speed. To demonstrate the competitiveness of ESB-YOLO, comparison tests were designed. Compared with advanced underwater object detection models such as FERNet, SWIPENet, and SK-YOLOv5, the average precision of ESB-YOLO is 3.10%, 3.90%, and 0.70% higher, respectively. The study shows that the proposed model is more effective and capable of farmed fish detection.

Fish resource survey is a basic work of fishery management, and the investigation of fish resources using underwater acoustic detection technology has become a mainstream method. Aiming at the acoustic data collected by Dual-frequency Identification Sonar (DIDSON) in the reservoir, the acoustic data post-processing software Echoview and related algorithms were used to conduct fish identification and counting research. First, the Kovesi image denoising method and the background difference method were utilized to remove speckle noise and water background in acoustic images, then targets were identified according to the echo threshold, the α-β trajectory tracking algorithm was used to track moving targets to prevent double counting, and finally fish counting and length extraction were performed. The results show that, compared with munual counting, fish counting error of this method is within 10%, and the average error is 7.2%, with a very high statistical accuracy. Studies have proven that DIDSON can be used for fish identification and counting, and has a very broad application space for fish resource detection and management in shallow waters.

In the field of aquaculture production, fish density detection is a key link to production management. In view of the clustering of underwater fish, the technology based on Congested Scene Recognition Convolutional Neural Networks (CSRNet) is used to combine the VGG-16 without the full connection layer with the hollow convolutional neural network, which maintains the resolution and expand the perceptual domain, thus generating a high-quality map of the distribution density of fish. The results show that the detection accuracy of CSRNet in the simulated fish data set is over 90%. The predicted density map is similar to the real situation with a small distortion. It also performs well in predicting the real fish density. Compared with the traditional raster image-based method, CSRNet improves the accuracy by approximately 10%. In the meantime, CSRNet performs better than Faster R-CNN, which is also based on VGG-16. The research shows that the software of detection system constructed can detect in real time whether the fish density in the fixed point area is in the normal range. It is beneficial to prevent the phenomenon of high density hypoxia of fish, increase the output of fish, and achieve intelligent aquaculture.

Traditional aquatic product traceability system has problems of tampering data, opaque links, and centralized management. To address the above problems, this paper designs master-slave multi-chain storage model to manage supply chain traceability information based on the analysis of the aquatic product supply chain and key information, so as to ensure the security of private data of enterprises and reduce the storage pressure of single-chain structure. At the same time, this paper designs an on-chain management and control smart contract to intelligently monitor all links of aquatic products from breeding to sales, and manage and control from the source. On this basis, this paper designs the traceability information management system of aquatic product blockchain based on master-slave multi-chain, implements the system based on Hyperledger Fabric, and proves the applicability of the system in combination with the actual application cases. Finally, this paper makes a comparative test with the blockchain single chain architecture. The results show that the storage model proposed in this paper carries out concurrent and hierarchical storage of traceability information, takes into account the two aspects of unnecessary sharing of private data and large single chain load, ensures the authenticity of traceability data, and achieves transparency in the traceability process.

In the process of fishery transformation and development, the development of deepsea mariculture is the strategic direction to break through the challenges of ecological environment and natural resources constraint and realize the sustainable development of China’s mariculture industry in the new era. This paper defines the concept of deepsea mariculture in China with consideration of the development level of mariculture industry and marine geological conditions based on the definition of deepsea mariculture proposed by FAO. It is proposed that selecting aquaculture species, constructing aquaculture systems and planning aquaculture sea areas are important factors for the steady and orderly development of deepsea mariculture. Emphasis should be given to economic potential, adaptive temperature and aquaculture techniques in the selection of aquaculture species. The suitability, safety performance and economic feasibility of different aquaculture systems for deepsea mariculture are analyzed and compared in the construction of aquaculture systems. Aquaculture discharge, environmental carrying capacity and marine geological conditions should be mainly considered in the planning of aquaculture sea areas.

 In order to study the influence of sloshing phenomenon of ballast tank on bulkhead structural strength of aquaculture vessels, the Smoothed Particle Hydrodynamics (SPH) method was used to simulate the slight sloshing and violent sloshing of ballast tank under rolling excitation. The influence of particle truncation error on or near the solid wall boundary of SPH method was solved by introducing dynamic boundary particle method. The simulation results of the two processing methods of dynamic boundary particles were validated by comparing with related literatures. The results show that the method used in this paper is reliable and effective, and is suitable for simulating the rolling and breaking of free surface during ballast tank sloshing. For slight tank sloshing, the boundary particle fixed method has higher calculation accuracy than the boundary particle motion method; both the boundary particle motion method and the fixed boundary particle method can effectively simulate the violent tank sloshing phenomenon. The results of this study can provide a reference for the numerical simulation of sloshing in the culture tanks of aquaculture vessels.

In recent years, there has been rapid development in intelligent aquaculture and fisheries resource conservation, leading to an increased demand for fish tracking technologies. Traditional fish tracking methods rely heavily on visual observation and tag tracking, which suffer from low efficiency, limited applicability, and low accuracy, hindering their widespread adoption. With the rapid advancement of deep learning in computer vision, deep learning-based fish-tracking technologies can provide accurate, objective, scalable, and automated tracking methods. Firstly, this paper introduces the tracking objects and four deep learning-based fish tracking methods: semantic segmentation, instance segmentation, object detection, and object classification. Secondly, it describes how fish tracking technologies capture fish trajectories, postures, fish quantities, and fish lengths, which are important tracking information for fish targets. Furthermore, the application of deep learning-based fish tracking technologies in fish diseases, fish feeding behavior, and fish health status is discussed. The paper also explores the main challenges of current deep learning-based fish tracking technologies, including low contrast and texture blurring, image color distortion, occlusion, and deformation, along with some corresponding solutions. Finally, the paper concludes and provides an outlook on the future development of deep learning-based fish-tracking technologies. It suggests that deep learning-based fish tracking technologies offer higher accuracy and objectivity, providing more solutions for practical applications in different scenarios. This technology is expected to play a more significant role in aquaculture management, fish scientific research, and marine environment conservation, offering more data and support to relevant fields.

Aquaculture is the farming activity of economical aquatic plants and animals by factitious control in natural or artificial waters. Its utilizing range covers extensive water space which included ocean, intertidal zone, pond, lake, reservoir, and river. As the core part of the fishery, aquaculture plays an increasingly important role in ensuring the supply of high-quality protein, building the water ecological civilization, accelerating the fishery transformation and upgrading as well as promoting industrial economic development. With the status of comprehensive speed up the construction for fishery modernization, aquaculture has gradually from the past reliant resource factors input turned into dependent technology innovation and improving the efficiency of production, furthermore, from pursuing quantity increased into higher quality, better benefit and more sustainable development way. In recent years, over upgrading the pattern with prep facility and equipment progress in aquaculture, the industry faces a flourishing developmental opportunity and serial challenges. This paper synthetically discusses the significance of developing aquaculture, analyzes its current developmental status, and summarizes the major problems which restrict the development of aquaculture. Imperative research-intensive tasks are proposed that involve preserving the genetic resources and researching the breeding technology, improving the target traits and breeding the significant varieties, optimizing the production mode and upgrading the traditional pattern, developing the cultured facilities and creating the large equipment, exploiting the high-efficiency feed and accurately preventing the diseases as well as analyzing the quality safety and constructing the traceability system. Relevant development suggestions are also proposed, such as doing well the integrated layout for scientific and technological innovation, doing real the construction of research platform and base, optimizing the safeguard for policy and law system, doing fine building the regional typical case, which aims to provide the lesson and reference for realizing accelerating from aquaculture country to a strong one.

In order to improve the purification capacity of the purification area in the internal circulation aquaculture pond, a photosynthetic bacterium named GR01 was isolated and purified from the bottom mud of internal circulation aquaculture pond in Tongnan District, Chongqing. The strain was classified and identified by morphological observation, physiological and biochemical identification, 16S rDNA gene sequence analysis and absorption spectrum scanning. The absorbance (A660) of GR01 was measured at 660 nm under different temperature, pH and salinity, and the optimal culture conditions were determined. The ammonia nitrogen (NH3-N), nitrite nitrogen (NO2--N), total nitrogen (TN) and total phosphorus (TP) were determined to explore the decontamination ability of the strain to the water in the purification area of the inner circulation aquaculture pond under the indoor simulated conditions. The results showed that GR01 was Rhodocista pekingensis, the optimal growth temperature was 28℃, the optimal pH was 8.0, and the optimal salinity was 10‰. The removal rate of the strain to NH3-N, NO2--N, TN and TP in the tail water was 57.42%, 28.74%, 32.67% and 32.85%, respectively. The results showed that GR01 had a significant removal efficiency to nitrogen and phosphorus, and the removal efficiency to ammonia nitrogen was the highest, which provided basic data for tail water purification in internal-circulation pond aquaculture and had a potential application prospect when combined with the internal-circulation pond aquaculture mode.

Hook depth has significant influence on pelagic longline catch performance. This study conducted two-way fluid-structure coupling simulation by using the numerical simulation software ANSYS Workbench 19.2 for tuna pelagic longline which was modeled by Tauti Criterion. In addition, 42 hook depth data measured from tuna pelagic longline operations at 6 survey stations in the high seas near Polynesia Islands (4°S~15°S, 140°W~160°W) in 2016 were compared with the numerical simulation hook depth based on ANSYS Workbench. SPSS t-test was used to analyze the difference between measured hook depth and numerical simulation hook depth. The results show that, the simulated deepest hook depth of pelagic longline is 280~310m, and the hook depth is negatively correlated with velocity. When velocity is low (X=-0.11~0.05 m/s; Y=-0.05~0.03 m/s; Z=0.03~0.11 m/s）, the simulated deepest hook depth is about 310 m. When velocity is high (X=0.28~0.75 m/s; Y=-0.10~0.52 m/s; Z=0.04~0.13 m/s）, the simulated deepest hook depth is about 280 m. There is no significant difference between the simulated and measured hook depth (P=0.241 > 0.05), nor significant difference between the simulated and measured hook depth at each station (P1=0.790, P2=0.337, P3=0.476, P4=0.369, P5=0.175, P6=0.136). The results suggest that the developed longline fishing gear model based on Tauti Criterion and ANSYS Workbench numerical simulation software can be used in the study of longline hook depth.

As an important equipment in marine fisheries, Multi-beam fishery sonar makes use of sound waves to detect underwater creatures, with the beamforming algorithms being the core technology in its development process. Based on the traditional shifted sideband beamforming (SSB) algorithm, this paper proposes an improved algorithm which converts parallel processing to serial processing, and increases the signal processing speed without causing performance loss. Firstly, this improved algorithm was compared with SSB. Then the improved algorithm was implemented on the field gate array (FPGA) platform, and performance evaluation and resource consumption were analyzed for the two algorithms. Finally a directive test was conducted over the FPGA realization of the improved algorithms in an anechoic sonar pond, and the simulated beam pattern was compared with the measured beam pattern through MATLAB. The results showed no difference of the two algorithms in their performance, while the resource consumption of the improved algorithm was nearly 70% lower than SSB. Meanwhile, the measured results of the improved algorithm were roughly consistent with the theoretical simulations, and the deviation was in a reasonable range.

Net clogging by attached organisms is one of the serious problems in deep sea aquaculture cage. How to realize the safe and efficient cleaning of cage is an urgent problem. In this paper, the structure of cage underwater cleaning robot was studied，and cavitating jet technology was used to clean the attachment on the surface of cage. The cavitation flow field inside the nozzle was simulated numerically by FLUENT software according to the underwater cleaning condition of the cage. The distribution of velocity field and vapor volume fraction near the nozzle was obtained by means of mixture model, cavitation model and Realizable Ƙ - ε turbulence model. The influence of nozzle inlet pressure and cleaning depth on cavitation effect of cavitating jet was also studied. The results show that the cavitation mainly occurs on the wall of the nozzle expansion section. Increasing the nozzle inlet pressure can improve the jet speed and high-speed flow range, and effectively improve the cavitation intensity, so as to enhance the cleaning strike force. However, with the increase of water depth, cavitation will be weakened. The results can provide a theoretical reference for the application of cavitating jet in aquaculture cage.

In order to solve the common problems of low fuel efficiency and insufficient fresh-keeping ability of motor fishing vessels in China, an aqueous-ammonia absorption refrigeration system driven by recovering waste heat from the exhaust gas of diesel engines was introduced. Based on Aspen Plus, the refrigeration cycle model was built, and the refrigeration cycle processes with a cooling capacity of 15 kW, 20 kW and 25 kW were simulated. It was found that when the target cooling capacity is 20 kW and 25 kW, and the refrigerant flow increases to a certain range, the heat load of the generator appears straight, which illustrates that the heat provided by exhaust gas can’t make the refrigerant separate out enough pure ammonia to satisfy refrigeration requirements. At the same time, the “low-lying” period appears in the curve of the coefficient of performance, and for the whole refrigeration system, its economic and heat efficiency is at unfavorable level. Therefore such conditions should be avoided in actual operations. In the cycles with the target cooling capacity of 15 and 25 kW, the coefficient of performance and actual cooling capacity increases sharply when the gas flow is huge, which is harmful for the reliability and economy of the system, thus the gas flow should be properly controlled in actual operations.

Artificial reefs is one of the major means to realize sea ranching construction, marine ecology control and marine habitat restoration. The fish accumulating effect of artificial reefs depends on many factors such as reef materials, structure form, hydrodynamic features and reefs layout. This paper summarizes the advances in artificial reef engineering technology at home and abroad from the following aspects: the advantage and disadvantage of current artificial reef materials and the application potentials of new composite materials, major reef configurations and current designing methods, researches in reef hydrodynamic behaviors using hydrodynamic model test and numerical calculation methods, as well as methods of artificially induced flow field and reef layout. Then according to the present situation of artificial reefs in China, it points out the development trend and key research directions of artificial reefs design and application, in the wish to provide reference for artificial reefs construction and upgrading in China.

In this paper, high-throughput sequencing was used to analyze the diversity of water flora in the biofloc system during nitrogen transformation. A control group and a test group were set in the test. The control group had clean and disinfected seawater, and the test group was a biofloc group. The test period was 30 days. The results show that in the test group, the mass concentration of ammonia nitrogen reached its maximum (2.99 mg/L) on day 5 and then decreased to 0 mg/L; in the control group, the mass concentration reached its maximum (7.51 mg/L) on day 9 and then decreased to 0 mg/L. In the test group, the mass concentration of nitrite nitrogen reached its maximum (12.54 mg/L) on day 17 and then decreased to 0 mg/L; in the control group, it showed a rising trend during the test period and reached 13.42 mg/L on day 30. The mass concentration of nitrate nitrogen in the test group was higher than that in the control group, reaching 19.56 and 6.31 mg/L respectively on day 30. The biofloc system was obviously able to remove ammonia nitrogen and nitrite nitrogen, and the nitrogen transformation rate of the test group was higher than that of the control group. High-throughput sequencing showed that the flora abundance and diversity index of the microorganisms in the biofloc system increased significantly with the increase of the breeding cycle, and the differences were significant in different periods. During the test period, a total of 23 phylum and 549 genera were identified. At the phylum level, the relative abundance of Proteobacteria decreased with time (from 67.72% to 44.45%), while that of Bacteroidetes and Chloroflexi increased with time (respectively from 5.99% and 6.68% to 16.06% and 19.02%). The main bacteria related to nitrogen transformation included Ardenscatena and Nitrospiraceae, whose relative abundance increased with time (respectively from 0.34% and 0.07% to 12.69% and 0.2%), while that of Nitrosopumilus decreased with time. The function and microbial diversity of the biofloc system showed significant changes during the breeding cycle. This study has reference value for improving the utilization efficiency of the biofloc system breeding mode.

The pure oxygen oxygenation system with an oxygen cone as the gas-water mixing device has high oxygen dissolution efficiency, but it needs to generate a certain amount of pure oxygen and energy consumption. This paper uses relevant principles such as material balance to scientifically design the flow of pure oxygen gas into the oxygen cone and the flow of aquaculture water, analyze its operating costs, and discuss key design issues. The results show that: when the oxygen cone with a certain cone structure size is used, when the flow rate of pure oxygen gas is 14.6 L/min and the flow rate of aquaculture water is 1327.3 L/min (the water circulation volume of the aquaculture system is 79.6 m3/h), the oxygen can be 81.88%～89.07% utilized. The higher dissolved oxygen efficiency of the cone provides 1026.8-1116.9g/h of dissolved oxygen in the aquaculture system, which fully meets the dissolved oxygen demand of the recirculating aquaculture of Litopenaeus vannamei with a culture water body of 300 m3 and a culture density of 6kg/m3. The oxygen consumption of the oxygen cone is 1252.7 g/h and the power consumption is 2.9 kWh. This design provides support for improving the technical performance of the pure oxygen aeration system and promoting the wide application of pure oxygen aeration in high-density recirculating aquaculture.

With the increasing market demand for fresh fish and shellfish, the research for their keep alive transportation technology has become a hot spot. Low temperature can make fish and shellfish breathing weakened, reducing metabolism and turning into the "hibernation" state, and make waterless keep alive transport easily. The key processes of fish and shellfish ecological ice temperature waterless transport includes ecological ice temperature determination, gradient cooling, storage and transportation environment, technics of waking up, while some examples was used to explain the process. The technical points needed to pay attention for this keep alive transportation technology was also analyzed, such as the variety of fish and shellfish, transport equipment and transport links in the organic link. Finally, the existing ecological ice temperature waterless keep alive transportation technology was summarized, and the future research trend and direction of the technology were pointed out, which provided a reference for optimizing and improving the ecological ice temperature and non water transport system.

To solve the navigation and positioning problem of the underwater net inspection robot, a positioning method of the robot based on the laser array is proposed by using the advantages of high precision and low interference of the laser sensor in the underwater short-range range. Based on the physical model of the cage, by establishing an a priori map of the cage code and simulating the operation of the robot in the gazebo simulation environment, the relative sailing distance and yaw angle of the robot to the netting are calculated from the laser ranging information, and the average error is 3.72% at the distance of 0.4 m, 8.15% at the distance of 0.08 m, and 19.18% at the deflection of 0.14 rad. The error in the positioning of the 8×6 net grid is 0 mesh, It shows that this method can meet the positioning requirements of the robot in the aquaculture cage under the non inertial frame. The results show that this method can provide a reference for the further study of the underwater net inspection robot positioning in deep-sea aquaculture cages.

Aquaculture production informatization is the integration and application of information technology in the whole chain of enterprise production, which has a positive impact on   the development of aquaculture industry’s informatization in China. It can effectively change the traditional mode of fishery production and promote the development of enterprise production in the direction of precision and intelligence. From the perspective of industrial development and technology application, this paper analyzes the basic tasks of aquaculture enterprise informatization, summarizes the basic technology links of production informatization, and combs the development status and research progress of aquaculture informatization technology at home and abroad from four directions: information collection, intelligent decision-making, enterprise informatization mode and intelligent service component. Finally, in view of the difficulties and challenges encountered during the process of deep application of aquaculture intelligent technology, the development direction and Application Development Countermeasures of aquaculture production information technology were put forward from the aspects of improving information collection ability, intelligent application of knowledge and data, realizing comprehensive perception and intelligent equipment.

To explore the purification technology of the tailwater of aquaculture ponds in coastal reclamation areas, a vertical subsurface flow wetland system was designed and operated in the Tiaozini reclamation area, which was filled with Suaeda salsa as a purifying plant and weathered coal, ceramic ring, and quartz sand as combined fillers. The difference between influent and effluent was compared to analyze the purification effect. After 70 days, the different fillers were taken out for a nitrification capacity test, and high-throughput sequencing technology was used to compare the bacterial community structure. The results showed that the pH, total nitrogen (TN), total phosphorus (TP), and permanganate index (CODMn) in the tailwater of the reclamation area were 8.55-9.17, 3.58-8.53 mg/L, 0.47-1.16 mg/L, and 17.96-26.63 mg/L, respectively. After purification, the pH of the effluent was 7.34-8.79, which basically met the second-level discharge standard of water from aquaculture ponds in Jiangsu Province. The TN, TP, and CODMn were 2.75-6.65 mg/L, 0.33-0.71 mg/L, and 16.32-24.16 mg/L, basically meeting the secondary standard. The differences in pH, TP, and CODMn in influent and effluent were significant (P<0.05), with an average decrease of 8.78%, 36.26%, and 13.52%. The nitrification capacity test showed that the removal rates of total ammonia nitrogen (TAN) by the upper and lower layers of weathered coal, ceramic ring, and quartz sand were significantly different (P<0.05), which were 97.44%, 88.88%, 49.30%, and 11.47%, respectively. The bacterial community structure on different fillers was significantly different (P<0.05). As dominant bacteria, Bacteroidota and norank_f__Microscillaceae were significantly enriched on the quartz sand and the upper layer of weathered coal with Suaeda salsa root attached, respectively (P<0.05). This study confirmed the application value of the combined filler vertical subsurface artificial wetland in the treatment of pond aquaculture tailwater in coastal reclamation areas.

Modern fishery equipment is an important guarantee for realizing fishery modernization. Since the founding of the People's Republic of China 70 years ago, fishing industry in China's fishery equipment has grown from scratch and has made great progress. This paper summarizes the development history and main contributions of fishing industry in China, as well as the main innovative achievements since the 13th Five Year Plan, and highlights the development trend of fishing industry in China's fisheries and the demand for equipment and technology. Specifically, it includes: The level of aquaculture productivity needs to be improved urgently, and more efficient facility fisheries need to be developed to stabilize the Political base of supply. The new space for aquaculture urgently needs to be expanded, and innovative new aquaculture methods that integrate the entire industry chain need to be innovated, gradually becoming a new supplement to ensure supply. The requirements for green development will be higher, and it is necessary to build an ecological circular production mode to comprehensively put the fishery on the track of sustainable development. Modernization of equipment has become an important demand, requiring the development of mechanized and intelligent production technologies, and becoming an important symbol of the "big to strong" fishery industry. The integration of modern elements in society is accelerating, and modern fisheries are entering a new era of synchronous development of "industrial fisheries" and "characteristic fisheries".

Net is an important part of cage. In order to solve the problem of numerical research on the movement deformation and stress of net, this paper proposes a mesh group improved method based on Morison equation and lumped mass method. The improved method keeps the volume and quality of the net unchanged before and after the mesh group, and the hydrodynamic force of the improved net is the same as that before the mesh group by adjusting the hydrodynamic coefficient. Through the numerical simulation of the circular net, and compared with the relevant research, the volume loss rate and horizontal drag force of the circular net are analyzed. The results show that: in the flow field of uniform velocity, the horizontal drag force of circular net increases with the increase of velocity, and then reaches the steady state, and the value is basically unchanged; increasing the bottom counterweight of net can effectively reduce the deformation of net, but with the increase of counterweight, the deformation inhibition effect is gradually decreasing. The improved mesh group method is accurate and effective, and has significant simplification effect and a good reference value for improving the hydrodynamic simulation efficiency and calculation accuracy of cage.

Multi-beam fishery sonar is an important tool for efficient, accurate and selective fishing in marine fisheries. In this paper, in order to systematically analyze the detection performance of multi-beam fishery sonar and the influence of main constraints on the operating range, for the multi-beam fishery sonar based on cylindrical array, the detection performance of the fishery sonar in noise and reverberation environments is analyzed with the method of underwater acoustic system simulation, the detection performance of fish school with different noise intensity under different sea conditions is compared, the abilities of narrowband system and broadband system to reduce reverberation are analyzed, and the detection performance of the fishery sonar in the mixed environment of noise and reverberation is simulated and analyzed. Finally, from the aspects of system design, transmitting mode, receiving mode and so on, the methods to improve the detection performance of the fishery sonar are put forward, which provides an improvement direction for the development of long-distance, high-resolution multi-beam fishery sonar.

Deep sea aquaculture is an important way to expand new space for aquaculture development, and reduce the pressure on offshore ecological environment. It is of great significance to  improve the quality and efficiency of aquaculture, to modernize fisheries, to ensure world food security and to sustainable development of aquaculture. However, the equipment and technology of deep sea aquaculture are the key to support and realize the development and growth of deep sea aquaculture. This paper briefly introduces the research and application status of deep sea aquaculture vessels and deep sea aquaculture cages, and points out that there is still a big gap between China's deep-sea aquaculture and foreign fishery developed countries in the automation and intelligence of mechanical equipment. This paper discusses the current main problems and future research and development directions of deep sea aquaculture vessels and deep sea aquaculture cages, and makes corresponding discussions and thoughts on the future development of deep sea aquaculture, especially  planning objectives, function expansion, scientific and technological support of deep sea aquaculture. This study is expected to provide reference for the research and development of deep sea aquaculture equipment and technology and future marine construction in China.