The sea cucumber industry is a pivotal sector in China's fishery economy, yet the insufficient mechanization level in aquaculture and fishing has become a critical bottleneck. This study systematically reviews the technological advancements in sea cucumber aquaculture and fishing equipment. It first analyzes the technical features of automatic feeding systems and automatic pool transfer machines in industrialized aquaculture, while comparing the efficiency, advantages, and limitations of various fishing methods and operational mechanisms in marine operations. Subsequently, the study highlights key technological innovations, elucidating how kinematic simulation technology optimizes equipment structures and demonstrating how underwater target recognition enhances fishing precision. Finally, three strategic development pathways are proposed: optimization of critical components in engineering aquaculture equipment, integrated innovation in intelligent fishing technologies, and establishment of equipment evaluation frameworks. The findings provide theoretical foundations and technical references for advancing automation and intelligence in sea cucumber aquaculture and fishing equipment.

With the development of deep learning technologies, object detection has become an important task in computer vision and has been widely applied in various fields. The YOLO (You Only Look Once) series of models, known for their efficient and fast inference capabilities, have become mainstream in the field of object detection and are widely used in various domains. In the aquaculture industry, diagnosing and treating fish diseases is crucial for preventing the spread of diseases and reducing economic losses. To address the problem of bacterial disease detection in freshwater fish, this paper focuses on the application of the YOLOv8 model in object detection and explores the role of data augmentation in improving model performance. Firstly, the basic principles and architecture of YOLOv8 are introduced, and the improvements of this model over previous YOLO versions are analyzed in detail, including the advantages of its network structure and optimization algorithms. Next, this paper proposes a fish disease detection method based on an improved YOLOv8 algorithm. This method incorporates the EMA (Efficient Multi-Scale Attention) attention mechanism into the backbone network, which not only enhances the feature extraction capability but also improves multi-scale feature extraction and cross-space learning architecture. This innovation reduces computational complexity while maintaining high-precision feature representation. Additionally, the GSConv (Grouped Shifted Convolution) operation is adopted in the Neck layer to replace traditional convolution operations, which reduces model complexity and further enhances detection speed without compromising accuracy. Experimental results show that this method achieves a 2.1 percentage point improvement in detection accuracy on our self-built freshwater fish disease dataset compared to the original YOLOv8 model. It also demonstrates significant performance improvement over other existing models. This method can be applied to fish disease detection and prevention scenarios, providing technical support for fish disease detection.

Targeting the issues of high labor intensity, uneven feed distribution, and low efficiency in aquaculture feeding, a ground - rail - based rail - type precision feeding system was designed. This system integrates mechanical design, automatic control, and upper - computer monitoring with feeding management. Key components like the traveling, silo, feeding, and weighing devices were designed and analyzed to determine structural parameters. An automatic control system using SIEMENS S7-200 SMART PLC was developed, and tests on driving speed, positioning accuracy, feeding speed, feeding accuracy, and feed crushing rate were conducted. Results show the system runs stably, starts/stops automatically, moves at 12.7 m/min, has a positioning accuracy error of 39 - 58 mm, feeds at 3.31 kg/min, with a feeding accuracy error < 0.63% and a feed crushing rate < 1%. The entire feeding process is automated, with real - time monitoring by the upper computer. This system boosts feed utilization and cuts labor and feeding costs. Its integrated design improves management and offers a viable solution for aquaculture automation.

This study aims to scientifically assess the disaster risks of ship net-type cages in wave environments, address the challenges in disaster prevention and control under extreme wave conditions, and promote the development of the offshore aquaculture industry. Numerical simulations were conducted using the AQWA hydrodynamic module in ANSYS to simulate the dynamic processes of ship-type net cages under various structural and wave conditions. After obtaining the data, a neural network algorithm was employed to construct the nonlinear relationship between disaster factors and structural damage, while the grey relational analysis method was used to identify the dominant disaster-causing factors. The results show that the structural motion responses and dynamic loads calculated by the numerical model closely match the test results, with an error of no more than 10%. The established neural network model accurately predicts the dynamic disaster situations, with a prediction error of no more than 5% and a root mean square error of no more than 0.52. It was determined that wave height is the dominant factor for mooring line breakage, and the floating frame length and wave height are the dominant factors for floating frame cracking. The research demonstrates that the neural network model can effectively predict the disaster damage for ship-type net cages and provides significant support for mooring line selection and floating frame safety assessment.

Rainbow trout (Oncorhynchus mykiss) is known for its tender, delicious, and nutritious flesh. To preserve its freshness, choosing an appropriate thawing method is crucial for maintaining fish meat quality. This study aims to identify the optimal thawing method to enhance the quality of thawed rainbow trout. To comprehensively investigate the effects of different thawing methods (hydrostatic thawing, flowing water thawing and microwave thawing) on the quality of rainbow trout, so as to screen out the most suitable thawing methods to improve the quality of thawed rainbow trout. This study employed a series of detection methods to systematically measure thawing curves, water-holding capacity, color changes, texture properties, malondialdehyde content, K value, microscopic structural characteristics, and sensory evaluation. A comprehensive comparative analysis was conducted on the quality differences of rainbow trout under different thawing methods. While hydrostatic thawing and flowing water thawing are simple to operate, they are time-consuming, taking 13.2 min and 10.5 min, respectively. Moreover, the water-holding capacity and texture properties of the fish after thawing were poor, affecting the final quality of the fish. Microwave thawing was the fastest, requiring only 4.2 min, but it had a significant drawback: the fish exhibited higher lipid oxidation, with a K value of 51.87%, significantly higher than that of other thawing methods (P<0.05), indicating a substantial impact on fish freshness. In contrast, ultrasonic thawing not only took less time (5.7 min) but also excelled in maintaining the water-holding capacity and texture properties of the fish. The thawed fish had a bright orange color, intact muscle fibers, clear microscopic structure, and effectively slowed the process of lipid oxidation, demonstrating unique advantages in preserving fish quality. Ultrasonic thawing not only meets consumers' expectations for the appearance quality of food but also aligns with the market's demand for high-quality ingredients, showing good market acceptance and potential commercial value. Therefore, ultrasonic thawing is more suitable for large-scale industrial thawing operations, as it can significantly improve thawing efficiency while better maintaining the freshness and taste of rainbow trout post-thawing. These findings provide a strong theoretical basis and practical guidance for enhancing rainbow trout product quality and processing efficiency, reducing thawing time and energy consumption, meeting the demand for high-quality aquatic products, and promoting related industry development.

This paper addresses the limitations of traditional water quality detection equipment in aquaculture, such as restricted detection range and insufficient depth, by designing a water quality detection robot and conducting structural dynamics and fluid dynamics analyses to verify the feasibility of the proposed design. First, the robot’s structural design and modeling were carried out, and the electronic cabin was subjected to static strength verification using the finite element method. Second, based on CFD, RANS and RNG k-ε turbulence models were used to analyze the robot's straight-line motion performance at speeds ranging from 0.2 to 1.0 m/s. Finally, overlapping grid technology was applied to explore the robot’s variable-speed motion characteristics. The results show that at a depth of 100 meters, the maximum equivalent stress in the electronic cabin is 50.70 MPa, with a maximum deformation of 0.0763 mm, which meets the pressure resistance requirements. Under straight-line motion, the hydrodynamic coefficients (、、、 and ) were −34.75, −37.54, −82.81, −71.16, and −93.47, respectively. In the variable-speed motion state, the corresponding inertia hydrodynamic coefficients (、 and ) were −7.32, −24.25, and −22.53, respectively. This study not only provides a novel equipment with underwater mobile detection system capable of full-range water quality monitoring,  but also offers data support for the structural optimization and motion control strategies, advancing its practical application in the field of water quality detection.

Compared with the open space of the aquaculture cage, the space of the aquaculture ship is closed and narrow, which is difficult to accommodate the huge suction pump operation equipment. At present, the centrifugal suction pump has the advantages of compact structure, flexible installation and not out of water during the whole fishing process compared with the vacuum type and jet flow, which is especially suitable for the aquaculture ship. To address the challenge of minimizing fish damage and enhancing the efficiency of fish collection in aquaculture ship, a low-damage fish suction pump with a diameter of 200 mm has been developed. The computational fluid dynamics-discrete element method (CFD-DEM) is used to analyze the flow field characteristics of the impeller and optimize the performance of the suction pump. Flow line distribution is uniform, no fish body extrusion and blockage; at the same time, the pressure distribution in the pump channel is uniform, and it will not cause too much damage to the fish. Fish suction pump test, at the outlet end with a net bag to separate the fish water, the results show that only a small number of shark sucker has slight scratches, suspected to be scratched by a mesh bag during the separation, and no trace of impeller scratches, meet the non-destructive live fish transport requirements. The results show demonstrates that fish suction pumps can be adapted to accommodate various fish species by adjusting the pump's diameter and rotational speed. This customization minimizes fish injury, reduces the physical labor required, and enhances both the efficiency of fish harvesting and the survival rate of the caught fish.

Squid is a significant aquatic product in China, yet its processing industry remains labor-intensive, leading to low efficiency and high labor intensity. This study introduces an image recognition-based soft-body modeling method to generate a 3D model of a suspended and inflated squid mantle from 2D images, providing a foundation for automated squid processing. The method uses OpenCV for image recognition to extract edge contours and geometric features of the squid mantle. MATLAB then refines these contours, deduces inner cavity contour points, and determines the mantle's rotational state. The contours are rotated around the central axis to construct a mesh model. This process accurately captures the shape of the squid mantle during processing, accounting for its deformable and flexible nature. Validation was performed using two datasets: different postures of the same squid body and five squid bodies of varying sizes. Results show that the maximum error in the model’s outer contour length compared to the actual body size is 0.66%, and geometric size errors across three postures are within 1%. This confirms the method's accuracy in generating 3D models from 2D images of squid bodies in various poses. The method ensures precise contour representation and is suitable for automated path planning in tasks like cleaning and cutting. Its non-contact nature makes it ideal for food processing, avoiding radiation issues associated with CT scanning. This study lays a foundation for automated squid processing, supporting tasks such as cleaning, cutting, and grading.

To explore the gas - liquid - solid three - phase flow characteristics during the operation of the pneumatic lift sludge suction equipment in the hatchery tank and establish a structural optimization method for the pipeline gas lift sludge suction device, the Fluent computational fluid dynamics tool was used. Based on the Euler multi - phase flow model and the dense discrete phase (DDPM) model, the influence of the structural form of the pneumatic lift pool bottom sludge suction equipment on the sludge suction performance was analyzed. The test results show that: the gas - liquid - solid three - phase flow process within the air - lift pipeline can be divided into the initial stage, pressure relief stage, lifting stage, and stable stage. The diameter, number, and spacing of the openings in the air - lift pipeline, as well as the height from the bottom, directly affect its sludge suction performance. Appropriate adjustment of the opening spacing can enhance the effectiveness of sludge suction. The optimal diameter for the openings in the air - lift pipeline is approximately 4 mm. Increasing the number of openings in the air - lift pipeline by 2.5 times results in a 27.2% decrease in the efficiency of the air - lift system. In contrast, increasing the height of the pipeline from the bottom by 3 times leads to a 31.6% reduction in system efficiency. Therefore, it is advisable to avoid increasing the number of openings and the height from the bottom in the air - lift pipeline.

As a new type of fishery cultivation equipment, the deep - sea aquaculture cage can cultivate fish with high economic value in the sea areas far away from the land. In order to explore the possible damage that the instability of the net - hanging poles may cause to the main structure of the platform, this paper takes a certain aquaculture platform in Guangdong as an example. Using finite - element software, displacements in different directions sufficient to cause fracture in the poles are applied to the free ends of the net - hanging poles. These displacements are designed to study the cracking process and ultimate bearing capacity of the typical nodes when they are subjected to forces in different directions. Different - thickness outer plates of the floating boxes are also set up to study the influence of the relative stiffness between the outer plates and the net - hanging poles on the fracture behavior and ultimate bearing capacity of the typical nodes. Through numerical calculations, it is found that when the same load is applied to the typical nodes with different plate thicknesses, the main structures of the 6 - mm and 8 - mm outer plates crack first, while for the 10 mm and 12 mm outer plates, the net - hanging poles fracture before the main structures. The results show that when the relative stiffness increases from 0.5 to 0.67, the weight increases by 8.8%, and the deformation - resistance capacity increases by 44%; when the relative stiffness increases from 0.67 to 0.83, the weight increases by 8.1%, and the deformation - resistance capacity increases by 33%; when the relative stiffness increases from 0.67 to 1, the weight increases by 7.5%, and the deformation - resistance capacity increases by 25%. It can be considered that the increase in the steel material of the typical nodes has little effect on the improvement of the ultimate bearing capacity, and an appropriate reduction in the plate thickness can be considered in the platform design stage. The analysis results show that if the stiffness of the main structure of the aquaculture cage is much greater than that of the poles, the fracture phenomenon is usually limited to the welds and the roots of the net - hanging poles and cannot extend to the main body of the aquaculture cage, resulting in only local plastic deformation of the main structure. On the contrary, when the stiffness of the main body of the aquaculture cage is lower than or close to that of the poles, the main structure of the node fractures first, and the fracture area gradually expands to the pole part. The results also show that the ultimate bearing capacity of the typical nodes of the net - hanging poles increases significantly with the increase in the thickness of the outer plates of the floating boxes. Based on this discovery, this paper proposes the calculation equations for the ultimate bearing capacity of the typical nodes in various directions, providing a theoretical basis for relevant engineering designs. 

 In order to explore the suitable light conditions of Apostichopus japonicus in indoor culture, 1680 juvenile sea cucumber (weight 0.185±0.014 g) were placed in three irradiance (1 000 mW/m2, 2 500 mW/m2, 4 000 mW/m2) in the environment of red (R)、full spectrum (W) and dark (D) for 35 days. The results showed that different spectra and irradiance could significantly affect the growth and physiological function of juvenile sea cucumber. The body weight of the red light 4 000 mW/m2 group was significantly higher than that of the full spectrum 4000 mW/m2 group (P<0.05). The body length of the red light 1 000 mW/m2 group was significantly higher than that of the full spectrum 4000 mW/m2 group(P<0.05). The specific body weight growth rate of the red light 1000 mW/m2 group was significantly higher than that of the full spectrum 4000 mW/m2 group (P<0.05). The survival rate of the red light 4000 mW/m2 group was significantly higher than that of the full spectrum 4000 mW/m2 group(P<0.05). For enzyme activity, amylase (AMS) activity was the highest in the red light 4000 mW/m2 group and lipase (LPS) activity in the red light 2500 mW/m2 group. The activities of acid phosphatase (ACP) and alkaline phosphatase (AKP) in the red light 4000 mW/m2 group were significantly higher than those in the red light 1000 mW/m2 group (P<0.05). The catalase (CAT) activity was the highest in the full spectrum 2500 mW/m2 group. The activity of superoxide dismutase (SOD) was the highest in the red light 4000 mW/m2 group, which was significantly higher than that in the full spectrum 1000 mW/m2 group(P<0.05). In summary, it is recommended to use red light to cultivate juvenile ginseng in an indoor culture environment and control the irradiance at 1000-4000 mW/m2. In this study, the effects of three irradiance degrees on the juvenile ginseng were studied, and the results showed that the growth performance of the juvenile ginseng with red light of 1000-4000 mW/m2 was better. In order to accurately and optimally determine the most appropriate irradiance, a fine irradiance gradient was recommended to further evaluate the effect of irradiance on the young radiance.

To explore the effects of different wall conditions on fish swimming ability, crucian carp, a typical fish with carangiform swimming mode, was selected for 1:1 biomimetic modeling. Computational fluid dynamics (CFD) combined with dynamic meshing technology was employed for 2D unsteady simulations of autonomous propulsion under various wall conditions. The study analyzed the impact of kinematic parameters like frequency (f) and amplitude (A) on swimming performance across different wall scenarios. Results showed that at low frequency (f=1.7 Hz) and small amplitude (A=0.04 L), a single - sided wall increased the fish's acceleration during the start - up phase and its cruising speed. When frequency rose from 1.7 Hz to 2.5 Hz at constant amplitude, acceleration under single - and double - sided walls rose by 52.7% and 75.9%, respectively. Similarly, when amplitude increased from 0.06 L to 0.07 L at constant frequency, acceleration under single - and double - sided walls rose by 32.4% and 33.3%, respectively. In low - frequency and small - amplitude conditions, a single - sided wall significantly enhanced propulsion. Within the low - frequency and high - amplitude range, increasing frequency and amplitude can significantly improve swimming speed. This study offers a useful reference for fish behavior research.

The height of the mooring point significantly affects the platform's hydrodynamic characteristics and structural stress, thereby impacting its stability. This study uses ANSYS to investigate the hydrodynamic and structural stress features of a semi - submersible aquaculture platform under different mooring point heights. The results indicate that higher mooring points lead to greater platform motion responses, especially in terms of increased tilt angles, which negatively affect platform operation and stability under extreme sea conditions. The lowest mooring point (P1) experiences higher mooring forces and stress but remains within acceptable limits, with the smallest motion response, making it favorable for platform operation and recommended as the ideal mooring point. Further analysis was conducted on the impact of different wave periods and load directions on platform motion and stress. When only subjected to wave action, the mooring force and stress show low sensitivity to the wave period, while horizontal displacement and heave increase with the wave period. Under combined wave - current action, the trends are opposite to those observed under pure wave action. The mooring force is maximized and platform displacement minimized when the load direction is 0°, while at load directions of 15° and 30°, two mooring chains share the load, resulting in reduced mooring forces, heave, and stress, while horizontal displacement increases. The findings provide valuable insights for the design and optimization of mooring heights for semi - submersible aquaculture platforms.

Portunus trituberculatus has high nutritional and economic value, and its appearance integrity directly affects its market value. At present, the sorting of Portunus trituberculatus faces challenges due to low levels of automation in traditional methods. Traditional sorting of Portunus trituberculatus is generally done manually, which has the problems of low efficiency and high labor costs, and human observation is easily affected by subjective factors. To solve the sorting problem of Portunus trituberculatus, this paper proposes a defect recognition model for crabs based on an improved ConvNext model , which can accurately identify the feet of Portunus trituberculatus and carry out intelligent recognition and grading. By accurately identifying the feet of Portunus trituberculatus, intelligent recognition and grading are carried out. Using re-parameterized refocusing convolution to replace depthwise separable convolution in the ConvNext model block, the network is able to capture richer and more detailed features. Coordinate attention mechanisms are added before the Block module and after the Downsample module of the ConvNext model to enhance the model's attention to key features and discard irrelevant features. The results show that the improved model has the highest accuracy on the validation set, at 98.90%, which is 3.32% higher than the original ConvNext baseline model network. The proposed algorithm ensures effectiveness. This study contributes to achieving the goal of intelligent and precise grading in the Portunus trituberculatus industry, and is anticipated to replace traditional methods to improve the sorting efficiency of Portunus trituberculatus. This can provide technical support for the further development of an automatic recognition and classification system for defects in Portunus trituberculatus.

To address issues like seedling blockage and damage during the falling and clamping processes in the development of mechanized kelp seedling clamping equipment, this study measured the biomechanical parameters of suitable - period kelp seedlings (Saccharina japonica) to obtain the mechanical parameters and deformation patterns of their stems and leaves under external forces. The structural composition of kelp seedlings was introduced, and their biological characteristics were measured. A texture analyzer and a friction coefficient analyzer were used to measure the mechanical properties of kelp seedlings, and discrete element simulations using EDEM verified the compression characteristics of kelp seedlings. Results showed that the tensile strength of kelp seedling stems ranged from 0.67 to 0.79 MPa, their shear strength from 1.95 to 2.23 MPa, and their compression recovery from 0.43 to 0.46. For kelp seedling leaves, the tensile strength was between 0.52 and 0.71 MPa, the shear strength between 1.12 and 1.74 MPa, and the compression recovery between 0.03 and 0.06. The tensile and shear strengths of kelp stems and leaves decreased with increasing loading speed, while the compressive recovery increased. Among stainless steel, rubber, and silicone, the friction coefficient between kelp seedlings and silicone was the highest when the normal force and loading speed were constant. The error between the simulated and measured radial compression values of kelp seedling leaves using EDEM was 8.2%. These findings offer data and theoretical support for optimizing the design of kelp seedling clamping equipment.

This study aimed to evaluate the feasibility of Biofloc technology (BFT) in Carassius auratusvar. Pengze aquaculture and to investigate the effects of total suspended solids (TSS) concentration on the growth of Pengze crucian carp, its intestinal tract, and the microbial community structure in the aquaculture water. The experiment included four TSS concentration groups: BF300, BF500, BF700, and BF900, as well as a water-exchanged control group (CW), and the Pengze crucian carp were cultured for 120 days. The results showed that the total ammonia nitrogen and nitrite nitrogen in the water of the Biofloc treatment groups could be maintained at low levels. The highest weight gain rate, body condition, specific growth rate, and condition factor were observed in the BF500 group, which also had the lowest feed coefficient of 1.42. In addition, there was no significant difference in the content of T-SOD and LSZ among the groups (P > 0.05). Microbiome analysis showed that the richness index of the intestinal microbial community in the Biofloc group decreased with the increase of TSS concentration in Pengze crucian carp; the dominant bacterial phylum in the intestine was Proteobacteria, Bacteroidota, Fusobacteriota, and Actinobacteriota, with Proteobacteria being the main bacterial group. The dominant bacterial phylum in the aquaculture water of the Biofloc group was Proteobacteria, Bacteroidota, Chloroflexi, and Actinobacteriota. In summary, the optimal TSS concentration for Pengze crucian carp was 500 mg/L, and BFT can serve as a new model for the green aquaculture of Pengze crucian carp.

To address the environmental pollution caused by the untreated discharge of laver processing wastewater and the inadequacy of traditional solid-liquid separation devices due to the unique adhesiveness of residual algae and impurities, a solid-liquid separation device for laver processing wastewater was developed. The working principle of this device was briefly described, and the structural dimensions of its core components were designed and calculated. A prototype was assembled for performance testing. With the separation rate and adhesion rate of laver processing wastewater as evaluation indices, and considering roller brush speed, filter mesh aperture, and backwashing movement speed as factors, a three-factor, three-level Box-Behnken experimental design method was used to conduct a quadratic orthogonal combination experiment. The results indicated that the optimal operating parameters were a roller brush speed of 476.28 r/min, a filter mesh aperture of 0.32 mm, and a backwashing movement speed of 0.007 m/s. Under these conditions, prototype testing achieved a separation rate of 84.12% and an adhesion rate of 4.71%, with no significant precipitates or suspended solids observed in the treated wastewater, meeting the requirements for solid-liquid separation. The study demonstrates that this solid-liquid separation device exhibits good separation performance, significantly reducing the risk of water and soil pollution from direct wastewater discharge and mitigating eutrophication issues, indicating promising prospects for widespread application.

 The high humidity environment in aquaculture workshops reduces the service life of workshop engineering and facilities. The high - humidity environment in aquaculture workshops present a significant challenge to equipment durability, frequently resulting in metal corrosion and mold growth. In particular, most industrial aquaculture workshops are steel - structured. Condensation on the steel frames leads to corrosion of the steel structures, which not only affects the aesthetics and service life of the workshops but also causes pollution to the aquaculture water quality. However, there is a lack of research on the temperature and humidity distribution and condensation under winter operating conditions in actual aquaculture workshops. This study provides a combined temperature - humidity control strategy for aquaculture workshops in winter, reducing the humidity in the workshop and the operating energy consumption of the ventilation system effectively. The accuracy of the numerical model was verified in this study through actual measured data of thermal environment in the experimental platform of aquaculture workshop. Thermal and humid environment and condensation in an aquaculture workshop in the condition of natural ventilation, mechanical ventilation and mechanical ventilation combined with heating are being investigated, and environmental control measures is proposed. The appropriate relative humidity range for aquaculture workshops is 60% to 80%. The study shows that the humidity of workshop and condensation on the inner wall can be reduced in the condition of mechanical ventilation. In the condition of mechanical ventilation combined with heating, indoor temperature can be increased uniformly, humidity can be reduced effectively in the workshop in winter, and heat consumption and operating costs can be reduced. The temperature and humidity monitoring points in the workshop are located at a height of 3 - 4 meters, providing a basis for the temperature and humidity monitoring positions in industrialized aquaculture. Intermittent ventilation for 23 minutes can achieve the effect of low - energy - consumption dehumidification. By adopting total heat recovery of thermal-humid air, through calculating the total heat recovery of mechanical ventilation in the actual workshop in winter, the heat recovery efficiency reaches 71.7%. The conclusions of this study have laid a research foundation for the dehumidification and energy - saving design of the air - conditioning system in industrialized aquaculture workshops, as well as the intelligent control of temperature and humidity.

To investigate the water quality variations and microbial community structure in the aquaculture zone of a freshwater pond with an embedded container recirculation aquaculture system, this study measured water quality indicators in the zone containing a three - stage biofilter (sedimentation tank, oxidation tank, purification tank, and filter dam) and biofill (filter cotton and brush). High - throughput sequencing was also employed to analyze the microbial community structure in the water column of each biofilter and on the biofill. Results indicate that the water purification system in the aquaculture zone operates stably and effectively, with the treated water quality meeting aquaculture requirements. The removal rates of ammonia nitrogen (NH4+-N), nitrite nitrogen (NO2--N), and total nitrogen (TN) were 52.97%, 63.23%, and 53.51%, respectively. The bacterial community in the aquaculture zone consisted mainly of 33 phyla, including Proteobacteria, Actinobacteria, and Bacteroidota. In the biofilter, the bacterial community structure of the biofilm differed from that of the water column, with a significantly higher relative abundance of Actinobacteria on the biofilm (P < 0.05). The water column samples had higher bacterial community diversity and richness than the biofilm samples. Correlation analysis revealed that NH4+-N, NO2--N, and TN significantly influenced the microbial community structure in the water column group (P < 0.05), while TP, AP, and DO had a more significant impact on the bacterial community structure in the biofilm group. In conclusion, the three - stage biofilter can effectively increase the microbial flora that promotes nitrogen and phosphorus metabolism, contributing to stable water quality. These findings provide theoretical support for the construction and water quality regulation of freshwater pond embedded container recirculation aquaculture systems.

In order to calibrate the discrete element simulation parameters of fish pellet feed and analyze the influencing factors of repose angle of fish pellet feed, this paper measured the repose angle of fish pellet feed based on stacking experiment. Taking Tongwei 150 model pellet feed as the research object, the funnel method, cylinder lifting method and suction plate method were used to realize the formation of the repose angle, and MATLAB software was used to process the accumulation image to determine the boundary contour of pellet feed. Plackett-Burman test was used to screen out three significant influencing factors: the static friction coefficient between feed and feed, the restitution coefficient between feed and feed, and the rolling friction coefficient between feed and feed. Finally, Box-Behnken test was used to construct the regression model of repose angle and significant influencing parameters. The optimal simulation parameters were determined by Design Expert optimization as the recovery coefficient between feed and feed is 0.28, the static friction coefficient between feed and feed is 0.31, and the rolling friction coefficient between feed and feed is 0.14, among which the static friction coefficient between feed and feed and its quadratic term have the greatest influence on the repose angle of granular feed. The experimental results provide a reference for the discrete element parameter calibration of fish pellet feed and the design of feed delivery and throwing equipment.

The continuous accumulation of nitrogen and phosphorus during zero water exchange biofloc culture is difficult to deal with, while floating duckweed (Lemna minor) is regarded as a plant with good water treatment ability, and in view of its aquaculture benefits as a feed supplement, so in order to better explore the duckweed-biofarming system for P. vannamei, the present study was set up to investigate the floating duckweed group (DG) and control group (CG) for a 45-day experiment with P. vannamei . At the beginning of the experiment, 40 g (wet weight) of duckweed was placed in the net box of GD. Fresh duckweed was fed every day in addition to the normal feed, and the amount of feed was adjusted according to the body weight of P. vannamei measured every week. Results indicated that DG achieved significantly lower levels of nitrate nitrogen (NO3--N), total nitrogen (TN), phosphates (PO43--P), and total phosphorus (TP) by 13.7%, 11.6%, 12.5%, and 11.8%. The growth metrics in DG were all significantly higher than those in CG (P < 0.05). The crude ash, crude fat, and crude protein of the shrimp in DG were (2.37±1.13)%, (2.48±0.35)%, and (19.63±0.64)%, showing significant differences compared to CG (P < 0.05). The levels of ASP, Gly, Met, Leu, Lys, and Arg in DG were also significantly different from those in CG (P < 0.05). The muscle hardness, chewiness, and water-holding capacity of the P. vannamei in DG were significantly higher than those in CG (P < 0.05). The enzyme activity tests indicated that the shrimp in the DG exhibited a significant enhancement in antioxidant and digestive capacities (P < 0.05). Based on these findings, incorporating duckweed in biofloc shrimp systems can purify water and enhance the growth performance, muscle quality, antioxidant capacity, and digestive enzyme activities of P. vannamei.

The phenomenon of oxygen deficiency is common in intensive aquaculture and live fish transportation, and has become an increasingly important issue in the aquaculture industry. The effects of hypoxic stress on water quality, biochemical parameters, and tissue structure during the transport of Siberian hybrid sturgeon (♀Acipenser baerii × ♂Acipenser schrenckii) larvae were investigated. The hybrid sturgeon larvae were placed in environments with dissolved oxygen concentrations of 2.5 ± 0.5 mg/L and 7.5 ± 0.5 mg/L for simulated transportation. Sampling was conducted before transport (0 h) and at 3, 6, 9, and 12 hours post-transport. The results showed that after 12 hours of transport, the survival rate of larvae in the hypoxic group was 54%. The serum cortisol (COR) concentration, liver alkaline phosphatase (AKP) and acid phosphatase (ACP) activities were significantly higher than those before transport (P<0.05). Serum glucose (GLU) levels peaked at 6 hours post-transport. Liver malondialdehyde (MDA), glutathione (GSH) content, and superoxide dismutase (SOD) activity were significantly higher than those in the normoxic control group (P<0.05). The liver antioxidant capacity (T-AOC) and lysozyme (LZM) activity in the hypoxic group exhibited a trend of initial decrease followed by an increase. After 12 hours of transport, the muscle glycogen content in the hypoxic group was significantly lower than that in the normoxic control group (P<0.05), while lactic acid levels peaked at 3 hours. More severe tissue damage was observed in the liver of hypoxic group larvae after 12 hours of transport. The study indicates that hypoxic stress during transportation affects juvenile fish survival rates, water quality, and other parameters, leading to oxidative stress responses and exacerbating liver tissue damage. 

To address the issues of data tampering, low credibility, and high on-chain storage pressure in aquaculture, this study constructs a blockchain-based data storage and traceability model for aquaculture. The model adopts a hierarchical storage strategy, where unstructured data such as videos and images generated in aquaculture are stored in IPFS, with only their hash addresses recorded on the blockchain. Additionally, encryption techniques are integrated to enhance data security. For structured data collected by sensors, a batched on-chain mechanism is designed, and data compression algorithms are introduced to reduce on-chain storage costs. Meanwhile, smart contracts are employed to enable automatic data verification. Using pufferfish aquaculture data as an example, the model is implemented and tested on a Hyperledger Fabric consortium blockchain. The results demonstrate that the proposed blockchain-based data storage and traceability model effectively ensures reliable traceability of aquaculture data. The value density of on-chain data is improved by approximately 91.6%, the transaction throughput reaches up to 300 TPS, and the average transaction latency is 0.5 seconds. These results indicate that the model significantly alleviates on-chain storage pressure and meets the traceability and storage requirements of aquaculture data.

Offshore aquaculture has developed rapidly in recent decades. As the most common aquaculture equipment, fish cages are widely used in the world. In order to further adapt to the harsh environment and improve the efficiency of aquaculture, a variety of large scale aquaculture cages combined with traditional marine engineering structures have also emerged. Vessel-shaped fish cage is a new type of large aquaculture structure, composed of steel floating body, net, steel frames and mooring lines, etc. Different from the conventional platform and fish cage, vessel-shaped fish cage has a large number of nets, which will affect fish cage motion and mooring response, furthermore increase economic and ecological risks. In this study, a time-domain coupling analysis method is developed to calculate the dynamic response of large floating cages in waves. Firstly, the three-dimensional potential flow theory is employed to determine the hydrodynamic coefficients of floating body, including added mass, potential damping coefficients and first order wave excitation force RAO. Subsequently the state space method is used to simulate the radiation load of floating body, the Morison equation is used to solve the hydrodynamic loads on slender structures (including steel frame, mooring line and net). Then, the coupled whole cage motion equation is established in time domain. By numerical method, influence of 3 different net models (no net, rigid net, flexible net) and net solidity ratios on motion and mooring responses were studied respectively. The results show that net increases the surge motion with 26%, but the heave and pitch motion are weakened due to the net damping effect. Additional, damping effect of flexible net is more obvious than that of rigid net. An increase of mooring line tension due to the net influence is also observed. This study can provide engineering reference and design basis for large fish cage in the concept and basic design stage.

Semi-submersible platforms face risks of mooring failure and motion instability caused by the combined action of waves and currents in exposed sea conditions. To verify the hydrodynamic performance of a retractable aquaculture platform, physical model tests were conducted to evaluate its behavior under three typical operational conditions: maintenance, floating, and seabed-resting. A 1:75 scale model was used to measure the platform’s six-degree-of-freedom motion responses and the dynamic characteristics of mooring line tensions. The results show that under maintenance and floating conditions, the combined action of waves and currents leads to the maximum mooring forces, while different load combinations have little impact on the platform’s motion. The wave period significantly affects mooring forces and pitch motion but has a minor influence on linear displacements. Under the combined action of waves and currents, mooring forces and linear displacements increase with wave period, whereas the opposite trend is observed under pure wave conditions. In the seabed-resting condition, the platform’s surplus weight provides strong resistance to sliding and overturning, with negligible motion and mooring forces. A comparison of the platform’s dynamic responses under maintenance and floating conditions reveals that under pure current or combined wave-current conditions, increasing the draft heightens mooring forces and exacerbates pitch motion while limiting linear displacements. In contrast, under pure wave conditions, increasing the draft reduces motion responses and mooring forces. The study confirms that the stability of the six-point mooring system and the strength of the mooring chains meet the design requirements, providing a basis for platform construction.

This study aimed to construct an integrated aquaponics system combining Litopenaeus vannamei and Beta vulgaris var. cicla L, and evaluate its potential for nitrogen/phosphorus removal and resource utilization in aquaculture wastewater treatment. The system's effectiveness was investigated through monitoring water quality parameters (turbidity, NH₄⁺-N, NO₃⁻-N, NO₂⁻-N, TN, TP), assessing plant and shrimp growth patterns, and analyzing microbial community dynamics. Results demonstrated that the system achieved a maximum turbidity removal efficiency of 66.9 %. Peak removal efficiencies reached 68.6 % for NH₄⁺-N and 86.0% for NO₃⁻-N during mid-operation, while NO₂⁻-N concentrations remained stable at 0.10-1 mg/L. Both Beta vulgaris var. cicla L and Litopenaeus vannamei maintained normal growth, with the plants assimilating 20.6% of total nitrogen input and 15.4 % of phosphorus input. Microbial analysis revealed that Beta vulgaris var. cicla L promoted enrichment of functional microorganisms responsible for nitrogen and phosphorus removal. The system exhibited excellent nutrient removal performance mediated by synergistic plant-microbial interactions, providing a novel approach for resource utilization of aquaculture wastewater. These findings highlight the practical significance of shrimp-vegetable symbiosis systems in sustainable aquaculture wastewater management.

In order to study the effects of different water spinach (Ipomoea aquatica) floating bed coverage ratios in aquaponic systems on the feeding rate and growth performance of Nile tilapia (Oreochromis niloticus), four experimental groups were designed: a control group with 0% coverage (C0), and three aquaponic groups with 20% (C2), 30% (C3), and 40% (C4) coverage ratios. Each group contained three replicates. Feeding rates were calculated every 7 days. After 35 days of rearing, growth indices and serum antioxidant parameters were measured. Results showed no significant differences in feeding rates among groups during the 7th days and 14th days (P>0.05). On the 21st days, aquaponic groups exhibited significantly higher feeding rates than the control (P<0.05). On the 28th and 35th days, feeding rates followed the order C4 > C3 > C2 > C0 (P<0.05). At the end of the experiment, all performance indicators in the aquaponic groups surpassed those of the control group,and with the increase of the floating bed coverage rate, the weight gain rate and specific weight gain rate of tilapia in each group increased, the activities of serum antioxidant enzymes (CAT, GSH-PX) enhanced, the total antioxidant capacity (T-AOC) increased, and the content of malondialdehyde (MDA) decreased. Considering the feeding rate and growth performance indicators of tilapia in each group, it can be concluded that the aquaponic group with a 40% floating bed coverage rate had the best rearing effect within the experimental range.

The land-based elevated round pond culture model has garnered significant attention in intensive aquaculture in recent years due to its advantages of land and water conservation and controllable farming environments. To evaluate its impact on the comprehensive quality of fish, this study focused on juvenile hybrid snakehead "Male Snakehead No.1", conducting a 365 day comparative farming experiment between an intensive land based elevated round pond group and a traditional pond culture group. post experiment analyses included growth indicators, muscle conventional nutrients, mineral elements, amino acid composition, and fatty acid content. Results revealed that in terms of growth,the intensive group exhibited higher weight gain rate, specific growth rate, and lower feed conversion ratio compared to the pond group, though differences were not statistically significant (P> 0.05). The intensive group showed a significantly higher crude fat content (P<0.01) and no difference in protein content (P>0.05). The intensive group had significantly higher calcium levels (P<0.05) but significantly lower zinc, selenium, iron, and sodium levels (P<0.05). Amino acid analysis identified 18 amino acids in both groups: the intensive group showed significantly lower total amino acids (TAA), essential amino acids (EAA), non-essential amino acids (NEAA), and umami-associated amino acids (DAA) (P<0.05). However, both groups had EAA/TAA ratios exceeding 40%, indicating high-quality protein. The intensive group detected 16 fatty acids, with significantly higher saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids (P<0.05) than the pond group, including unique components like EPA. The study concludes that land-based elevated round pond culture enhances muscle fat and functional fatty acid content but requires feed fortification to optimize mineral and amino acid balance. These findings provide insights for refining aquaculture strategies and improving aquatic product nutritional value.

Sea treasure target detection is a key technology for the intelligent development of sea treasure resources. This paper proposes an improved algorithm YOLOv9-PAEG based on YOLOv9-S to address the problem of low accuracy in detecting sea treasures in complex underwater environments, difficult feature extraction, diverse target sizes, and a large number of small targets. Firstly, the SPPELAN module was improved by introducing the PfAAM attention mechanism and distributed shift convolution DSConv2D, and the PFAD_SPPELAN module was designed to enhance the detection accuracy and speed of the model. Secondly, by introducing a variable kernel convolution AKConv in the backbone network layer of the model, the model can more flexibly adapt to features of different sizes and shapes, thereby improving its feature extraction ability for multi-scale targets, especially small targets. Then, the ECA attention mechanism was integrated into the neck layer of the model, enhancing its ability to represent important features and improving detection accuracy. Finally, by using the GIoU loss function, the convergence of the model was accelerated and the positioning accuracy was optimized. Experiments have shown that the YOLOv9-PAEG model performs well on datasets DUO and UDD mAP@0.5 They reached 89.7% and 77.6% respectively, and FPS reached 71 and 69, respectively. Compared with the original model and other mainstream object detection models, they have improved detection accuracy and speed. This fully proves the effectiveness and progressiveness of the YOLOv9-PAEG model, which can provide a better detection effect for marine treasures.

To investigate the potential of edge computing technology in intelligent fisheries equipment, this study addresses limitations of traditional cloud computing regarding real-time responsiveness and efficiency by proposing an optimized solution through relocating computational resources closer to the network edge. The research systematically reviews the development history of edge computing technology and emphasizes the critical technologies in intelligent fisheries equipment, such as computational offloading and data storage and management. By analyzing typical fishery application scenarios, the role of edge computing in improving real-time data processing and system responsiveness is highlighted. Results indicate that edge computing significantly alleviates network bandwidth constraints and transmission latency issues by decentralizing computational resources, thereby enhancing the real-time performance of intelligent fisheries equipment. Nevertheless, challenges such as limited computing capabilities of edge devices and insufficient coordination among heterogeneous equipment continue to hinder broader adoption. With deeper integration of edge computing with artificial intelligence, big data, and the Internet of Things (IoT), edge computing promises further improvements in remote data transmission, IoT integration, intelligent decision-making, and sustainable development in intelligent fisheries. This advancement is expected to drive the fisheries industry toward greater intelligence, efficiency, and ecological sustainability.

A real-time structural safety assessment method based on digital twin technology is proposed to ensure the safe and stable operation of the environmental monitoring platform of the sea ranch during its service period. A three-level digital twin architecture is adopted to achieve rapid prediction and real-time visualization of the overall stress distribution state of the monitoring platform. The maximum error is less than 10%, which verifies the reliability of the simulation model; the structural stress field response database covering the monitoring platform under the common sea conditions during the service period is established by batch front simulation calculation of multiple working conditions; the structural stress field response database covering the monitoring platform under the common sea conditions during the service period is established by batch front simulation calculation of multiple working conditions;   the structural stress field response database covering the monitoring platform under the common sea conditions during the service period is established by batch front simulation calculation of multiple working conditions; under the simultaneous change of environmental parameters, the structural stress distribution of the monitoring platform can be predicted and visualized in real time.   In the case of simultaneous changes of environmental parameters, a fast prediction based on the structural response database is carried out by the improved inverse distance weight interpolation (IIDW) method, and the results show that the average absolute errors between the interpolated data and the simulation data for axial forces, moments, and spatial displacements at the monitoring points are 7.62%, 11.93%, and 5.77%, respectively. The average absolute errors between interpolation data and simulation data for all 2462 structural rods were 6.24%, 7.88% and 5.39%, respectively. The rapid structural safety assessment method of the ocean ranch environmental monitoring platform proposed in this study provides a feasible solution for the real-time monitoring of the overall stress and safety early warning during the platform's service period.

Accurately and efficiently monitoring the stress behavior of fish fry not only helps to regulate stressors during the breeding process to reduce yield losses, but also provides an effective means for evaluating the vitality of fish fry during the breeding stage. In view of the characteristics of fish fry, such as small size, high stocking density, and high - speed non - linear movement, this study proposes a method for monitoring the stress behavior of fish fry by improving YOLOv8n - pose and combining it with BoTSORT.The improved YOLOv8n - pose is used as a detector. The BMS module is combined with the C2f module to enable the model to fully learn features at different scales. The SPPCSPC module is used to replace the original feature fusion module of the model to optimize the detection accuracy in the case of fish fry occlusion. Finally, N - EMASlideLoss is used to replace the original loss function of the model, enhancing the model's stability and attention to small targets.In the tracker part, based on the targets detected by the detector, a method more suitable for monitoring the non - linear movement of fish fry under stress is achieved by combining the BoTSORT multi - target tracking algorithm.Finally, three features of fish fry, namely acceleration, tail - wagging angle, and aggregation degree, are extracted and weighted for fusion. Based on the fused feature values, it is determined whether the fish fry are under stress. The experimental results show that the mAP of the improved YOLOv8n - pose algorithm in target detection and key - point detection is 3.6% and 4.5% higher than that of the original model respectively. The MOTA of the BoTSORT algorithm is 77.628%, the MOTP is 80.307%, the IDF1 is 79.573%, and the IDSW is 51, which are superior to those of the DeepSORT, ByteTrack, and StrongSORT algorithms. The accuracy of the stress behavior monitoring of this study's algorithm based on feature values is 95.24%, providing new ideas and methods for stress behavior monitoring in fish fry breeding. 

This study proposes a target detection and tracking method based on the improved YOLOv11 model—YOLOv11n-DFM. It aims to evaluate losses during the fishing process by detecting the number of crab traps being lifted or lowered and to assess the normalcy of the trap mechanism by detecting the number of traps in key areas. The method integrates DyHead, FocalModulation, and CCFM modules into the YOLOv11n model to enhance multi-scale feature fusion, improve detection accuracy for traps of different scales, and reduce computational and memory costs. Additionally, the ByteTrack algorithm is employed to ensure precise tracking of the traps. Experimental results demonstrate that the YOLOv11n-DFM model improves detection accuracy by 1%, increases mAP@50-95 by 0.8%, while mAP@50 and recall remain unchanged. Compared to the YOLOv11n model, the detection performance is enhanced while maintaining the same detection efficiency. The study indicates that the YOLOv11n-DFM model excels in detecting and tracking the crabs' traps, consumes fewer computational resources, and is suitable for deployment in environments with limited computing power. It provides valuable references for fishery monitoring, resource management, and the future automation of crab trap deployment and collection.

 High-density polyethylene (HDPE) is a novel thermoplastic material for fishing vessel construction, whose welding quality is one of the primary factors ensuring the safety of HDPE fishing vessels. To address the challenges in HDPE fishing vessel welds defect detection, including high similarity between defects and background as well as weak small-target features, this study proposes an improved ACA-YOLOv8(Adown-CCFM-AC-mix-YOLOv8) object detection algorithm.The proposed method employs an Adaptive Downsampling(ADown) strategy to effectively preserve defect features, enhances multi-scale feature representation through a Cross-scale Consistent Feature Fusion Network(CCFM), and incorporates a Self-attention and Convolution Mixed(AC-mix) mechanism during feature fusion to improve small target detection capability.Experimental results demonstrate that the improved model maintains lightweight characteristics while achieving an average detection accuracy of 98.9%, representing 3.2%  improvement over the baseline model. Additionally, it reduces parameters by 43.5% and computational load by 2.0G. This algorithm better meets the computational requirements for HDPE fishing vessel welds defect detection in industrial production environments.

The gravimetric (weight-based) method is widely used for detecting suspended particulate matter (SPM) in aquaculture water. However, it is labor-intensive and time-consuming. To enable rapid and efficient detection, this study focused on the SPM in the aquaculture environment of Scophthalmus maximus. By capturing video footage of suspended particulates in a tank, we developed an automatic detection method based on the Gaussian Mixture Model (GMM) for identifying SPM in water. The results demonstrated that dynamic grayscale processing combined with GMM-based background modeling enabled the extraction of recognizable images of SPM. An intelligent image screening and particle-counting approach was then established. The recognition algorithm was implemented and automated using Python, incorporating relevant image processing libraries. The GMM-based method achieved a detection limit as low as 0.6 mg/L in an industrial recirculating aquaculture system (RAS) for Scophthalmus maximus. Moreover, particle counts obtained through intelligent recognition showed strong correlation with gravimetric measurements (R² = 0.981). To further validate the method, 24-hour continuous monitoring of SPM was conducted, and the relative error between the intelligent detection and the traditional weight method remained below 5%. These results indicate that the GMM-based intelligent recognition approach can reliably and automatically quantify SPM concentration. This method offers advantages such as real-time monitoring, continuity, intuitive visualization, and operational simplicity, showing strong potential for practical application in aquaculture water monitoring.

In the photovoltaic river crab breeding pond environment, solar panel obstruction significantly reduces the accuracy of the unmanned operation ship's satellite positioning system. To address this, a laser - inertia - based unmanned operation ship positioning method is proposed, considering the pond's unique conditions. This method improves the Hector - Slam positioning process. First, LiDAR point cloud data undergoes preprocessing to filter disturbances and reduce data size, enhancing accuracy. Then, the map continuity method in Hector - Slam is enhanced by using nonlinear fitting to identify obstacle centers, followed by Gaussian blurring to ensure map continuity, creating a smoother reference map for matching. Next, the map - matching process in Hector - Slam is improved by replacing the Gaussian Newton method with gradient descent, yielding more precise results. Finally, a Kalman filter integrates radar and IMU poses, combining position and heading angle information for improved positioning accuracy. Experimental results show the laser inertial fusion positioning method reduces average positioning deviation by 46% compared to the Hector algorithm. Unlike satellite positioning, which fails to meet the accuracy requirements in photovoltaic ponds, our laser - based method ensures precise positioning. It also outperforms visual schemes in accuracy under disturbances and low - light conditions. Moreover, compared to high - cost 3D laser solutions that are impractical for agricultural production, our cost - effective laser method offers significant advantages. Thus, this laser inertial fusion positioning method can replace satellite positioning, effectively meeting practical production needs.

n response to the variability of fishing boat trajectories, this study aims to improve the accuracy of the prediction model by optimizing the characteristic parameters of fishing boats during the data preprocessing stage, in order to enhance the accuracy of predicting fishing boat berthing trajectories. Propose a fishing vessel berthing trajectory prediction model based on Beidou ship position data and combined with Long Short Term Memory (LSTM) network. Collect Beidou fishing vessel position data through a Vessel Monitoring Systems (VMS) onboard terminal, extract spatiotemporal position information and other feature parameters, preprocess the collected Beidou fishing vessel position data, select input feature parameters for the prediction model using correlation analysis, classify the feature parameters according to fishing vessel size and type, and train the model. Finally, compare the predicted trajectory with the actual berthing trajectory. Exploring the practicality of Beidou ship position data in ship trajectory prediction and the impact of fishing vessel types on berthing trajectory prediction. The final experimental results showed that the accuracy of the model prediction reached 92.3%, proving the superiority of Beidou ship position data in ship trajectory prediction research. At the same time, it proved the conclusion that the type of fishing captain is positively correlated with the longitude of trajectory prediction, providing a new method for port and fishery management.

Underwater biological target detection still predominantly relies on manual identification methods, facing challenges related to low levels of intelligence. Existing target detection algorithms, such as the YOLO series, suffer from issues such as large parameter counts, high computational requirements, and poor detection accuracy. This paper proposes an improved algorithm based on the RT-DETR model. The DynaShareNet backbone network is introduced, which shares stem information architecture to enhance feature fusion efficiency and reduce computational burden; the Dilated Transformer Attention Block (DTAB) is introduced to combine global and local feature interactions to enhance robustness in complex underwater environments; the MaSA-RetBlock module is adopted to address target blurring and low-contrast recognition issues; and the EMASlideVarifocalLoss is introduced to enhance the ability to handle difficult-to-classify targets. Experimental results on the URPC2020 dataset demonstrate that the improved algorithm significantly enhances detection accuracy, with mAP50 and mAP50:95 improving by 3.3% and 3.5%, respectively, while significantly reducing model complexity, with parameter counts and computational costs decreasing by 41.7% and 47.7%, respectively. The detection accuracy and parameter count/computational complexity outperform YOLO series algorithms, and the algorithm demonstrates excellent generalization performance on the RUOD dataset. The study indicates that the improved algorithm effectively enhances the performance and efficiency of underwater target detection, offering promising application prospects.

Oysters hold the top position in terms of production among shellfish farming species, demonstrating significant economic value. However, current farming facilities face challenges such as low levels of standardization and mechanization, as well as fragility to wind and waves. These issues severely limit the sustainable development of the oyster farming industry. In this research, an elevating oyster farming platform was meticulously designed. Subsequently, the physical model test method was employed to comprehensively investigate the hydrodynamic characteristics of the platform under various wave parameters, drafts, and mooring configurations. The research indicates that the motion responses and mooring line forces of the farming platform are positively correlated with wave height and period. In contrast, the growth rates of the motion responses and mooring line forces are negatively correlated with the period. Under identical working conditions, the amplitude of heave and pitch motion changes more dramatically. Under extreme sea conditions, when the farming platform transitions from the floating state to the submerged state, the surge, heave, pitch, and mooring line forces are reduced by 27.32%, 45.89%, 42.32%, and 18.47%, respectively. This transition significantly enhances the platform's capacity of withstanding wind and waves. Notably, the attenuation effects on the heave and pitch motions are the most pronounced. The motion responses and mooring line forces of the slack mooring farming platform are relatively lower than those under the tension mooring condition. Moreover, their increase exhibits an approximately linear relationship. This research not only provides a theoretical support for the development of oyster farming platforms but also offers a critical reference value for the design and research of other shellfish farming platforms.

To accurately predict the air gap performance of offshore frame-type aquaculture platform, a frame-type aquaculture platform was selected as the research object. Based on linear wave diffraction/radiation theory, Morrison equation theory, and rigid body kinematics principles, frequency-domain method was employed to analyze air gap performance. The effects of viscous loads on structural slender members and nettings, disturbed wave surface elevation, position mooring system stiffness on air gap performance were analyzed. Key findings from comparative analysis include: viscous loads on structural slender members and nettings substantially improve platform motions and optimize air gap performance, with a decrease range of about 0.3-1.0 m; Disturbed wave surface elevation significantly affects the air gap performance of frame-type platforms, with an increase range of about 0.2-0.7 m and a decrease range of about 0.3-1.6 m; Position mooring system stiffness constrains platform motion and affects the air gap results, with a decrease range of about 0.1-0.4 m. The results emphasize that the effects of viscous loads on structural slender members and nettings, disturbed wave surface elevation, position mooring system stiffness should be considered reasonably in frame-type aquaculture platform air gap analysis.