Biofloc Technology (BFT), an environmentally sustainable aquaculture approach, harnesses in situ microbial processes to purify water, supply supplemental nutrition, and suppress pathogens, thereby serving as a cornerstone for advancing sustainable aquaculture. This review systematically addresses core technical challenges inherent in BFT applications, with particular emphasis on constraints stemming from species-specific physiological requirements, the diversity and economic feasibility of carbon sources, dynamic fluctuations in critical water quality parameters, and overall system stability. Our analysis underscores that precise control of the carbon-to-nitrogen (C/N) ratio, judicious selection of carbon sources, efficient dissolved oxygen (DO) management, continuous alkalinity replenishment, and stable regulation of suspended solids are fundamental to maintaining system functionality. To overcome these challenges, we integrate key strategies—including optimized carbon supplementation protocols, refined microbial community management, innovative aeration system design, and intelligent real-time monitoring technologies. Finally, we delineate future development pathways for BFT, focusing on standardization, intelligent automation, multi-trophic integration, and enhanced energy efficiency, thereby offering theoretical foundations to accelerate its adoption at industrial scale.

Antarctic krill (Euphausia superba) is an important strategic marine resource globally, and improving its fishing technology is essential for increasing catches for each national fishing industry. Currently, the Antarctic krill fishery is entering a new phase of resource competition driven by continuous technological developments in fishing. Although China has successively deployed several professional continuous fishing vessels, it still faces challenges such as reliance on imported core equipment and low fishing efficiency. This paper systematically reviews the development and application of Antarctic krill fishing technologies, with a focus on continuous trawling methods and the existing challenges in areas such as precise krill swarm detection, fishing path planning, and dynamic fishing depth adjustment. We propose the establishment of an intelligent continuous fishing technology system, which is centered on precise krill swarm detection, intelligent decision-making for fishing paths, and coordinated control of operational fishing gear layers. The overarching objective is to promote the high-quality development of China's Antarctic krill fishery towards intelligent precision and enhance the competitiveness of catch shares.

To optimize acoustic conditioning parameters for enhancing the aggregation effect and stock enhancement efficiency of Sebastes schlegelii, this study applied continuous pulsed sounds at 200 Hz, 300 Hz, and 500 Hz over a 20-day acoustic conditoning period. The effects on shoaling behavior (response time, aggregation time, aggregation rate) and physiological indicators (plasma cortisol, total protein, alanine aminotransferase) were evaluated. Results showed that the 200 Hz group exhibited the fastest behavioral response during the initial stage (days 1~4), while the 300 Hz group achieved the highest aggregation rate in the mid-stage (days 2~7). In the later experimental stage (days 8~20), all acoustic conditioning groups demonstrated significantly better shoaling behavior than the control group (P < 0.05). The final aggregation rate was highest in the 300 Hz group (73.74%), followed by the 200 Hz group (69.1%) and the 500 Hz group (63.51%). Physiologically, levels of alanine aminotransferase (ALT) and cortisol (COR) increased transiently before recovery. The 300 Hz group showed the smallest ALT peak (30.79 ± 1.10 pg/mL), and its COR levels returned to baseline faster than those in the 200 Hz and 500 Hz groups. Total protein (TP) levels showed only minor overall fluctuations, indicating the mildest stress fluctuation in the 300 Hz group. In conclusion, the 300 Hz acoustic frequency effectively promotes shoaling behavior in Sebastes schlegelii while inducing less physiological stress compared to 200 Hz and 500 Hz, making it the preferred parameter for acoustic technology optimization. This finding holds practical significance for improving resource management efficiency in marine ranching.

In order to investigate the effects of different stocking densities on the growth performance, antioxidant capacity and immune function of Siniperca chuatsi in a factory farming production system, and to preliminarily determine its suitable stocking density. Three stocking density groups of low (M1, 150 fish/m³), medium (M2, 200 fish/m³) and high (M3, 250 fish/m³) were set up to carry out the 180d culture experiment. The growth indexes of Siniperca chuatsi were measured and the expression levels of antioxidant enzyme activities and related immune factors in the head, kidney and spleen were analysed. The results showed that at the end of the culture period (180 d), the M2 group was significantly better than the M1 and M3 groups in terminal body mass, body length and weight gain rate (P < 0.05). The antioxidant capacity tended to decrease with increasing density, with a significant decrease in superoxide dismutase (SOD) activity and total antioxidant capacity (T-AOC) content, and a significant increase in malondialdehyde (MDA) content; the activities of non-specific immunoenzymes (AKP, ACP, LYS) and the activities of pro-inflammatory factors (TNF-α, IL-8), interferon pathway-associated molecules (IRF11, IFP35) and T-cell receptor (TCRα) content were significantly upregulated with increasing density. It was shown that excessive high density induces oxidative stress and chronic inflammation, although it can stimulate the immune response. The present study suggests that the density of Siniperca chuatsi in factory culture should be around 28.61 kg/m³ in order to achieve a balance between culture efficiency and fish health.

 In view of the characteristics of high salinity of suspended particles in the tail water discharged from high-density intensive aquaculture, and the low efficiency and high cost of traditional tail water treatment equipment, this study designed a centrifugal desalting and slag collection machine integrating centrifugal dehydration, high-pressure spraying and negative-pressure collection, completed the structural design and control system of the equipment, and made a prototype to carry out performance tests. The raw water mixed with feed and seawater is used to simulate the actual tail water, and the collection rate, desalination rate and water content of treated solid particles of the equipment are taken as indicators. By using the single factor experimental design method, the performance test is carried out under the working conditions of the same equipment operating parameters and different liquid-solid concentration ratios, and the treated solid particles are dried to calculate the index value of the equipment. The results show that the equipment has a good effect of solid-liquid separation and salt reduction. The collection rate of solid particles in aquaculture tail water can reach over 65%, the desalination rate is over 80%, and the water content of treated solid particles is about 65%. The research shows that the equipment can significantly reduce the pollution risk of water and soil caused by direct discharge of tail water, and realize the resource utilization of tail water tailings, which has a good prospect of popularization and application.

In response to the actual needs of Sanya Bay Marine Ranch, this paper designs a porous box-shaped artificial reef with an internal shelter tube and the function of juvenile fish care. Based on the structural and flow field characteristics, this porous box-shaped artificial reef was compared and analyzed with three traditional reef structures. In addition, the flow field characteristics of the porous box-shaped artificial reef under different inflow velocities, flux-facing angles, transverse and longitudinal layout spacings were explored by combining numerical simulation. The research results show that the hydrodynamic characteristics of the four reef structures are significantly different. Among them, the volume of the upwelling flow and the back nest flow of the porous box-type artificial reef is the largest, followed by the square A-type artificial reef and the hollowed-out frame-type artificial reef, and the square B-type artificial reef is the smallest. Moreover, the stability of the four reef structures all meets the requirements, and the porous box-shaped artificial reef has prominent advantages in terms of surface area and flow field effect. The flow field parameters of the porous box-type artificial fish reefs do not change significantly with the increase of the incoming flow velocity. The flow field parameters of the artificial fish reefs show a trend of first decreasing and then increasing with the increase of the flow angle. When the flow angle is 45°, the upflow volume, the length of the back-burrow flow, and the volume are the largest. It is recommended to use this angle for deployment. The lateral spacing is negatively correlated with the flow field parameters of the artificial fish reef group. It is recommended to use a spacing of 0.5 times the reef length for layout, which can effectively suppress cross-flow and enhance cooperative blocking. The longitudinal spacing is positively correlated with the flow field parameters of the artificial fish reef group. It is recommended to use a spacing of 2.0 times the reef length for layout, in order to promote the superposition and coupling of the flow fields of adjacent reefs and expand the slow-flow area.

This study addresses the challenge of efficiently removing bottom solid waste in intensive aquaculture tanks by focusing on rectangular aquaculture tanks. A two-dimensional transient model, coupling the standard k–ε turbulence model with the VOF free surface model, was developed to optimize a mechanical scraper discharge system. Using an L25(5³) orthogonal design, the effects of scraper height (6–14 cm), tilt angle (−20° to +20°), and speed (0.05–0.09 m/s) on particle distribution and discharge efficiency were analyzed. The results showed that the tilt angle had the most significant impact, with the optimal parameters being 6 cm height, +10° tilt, and 0.05 m/s speed, achieving the highest efficiency and minimal residue. To validate the numerical model, 45 single-factor tests were conducted on a physical platform using particle recovery to quantify removal efficiency. Results deviated by only 5%–10% from simulations, confirming model accuracy. The study supports the engineering optimization of mechanical scraper systems.

Aiming at the problems existing in current fish barrier electric fences on the market, such as non‑continuously adjustable output pulse voltage, easy corrosion of unipolar pulse electrodes, and generally low system scalability and networking level, a fish barrier electric fence device is designed based on power electronics, automation, and Internet of Things (IoT) technologies.An Omron network‑type PLC is used as the central control core, combined with IoT gateway communication, to achieve easy system expansion, networked control, and remote operation. A PWM pulse generator outputs high‑frequency (50 kHz) pulses to control the on‑off states of the MOSFET in a synchronous BUCK circuit, thereby realizing continuous voltage regulation. The same PWM pulse generator outputs low‑frequency (≤30 Hz) pulses to control the on-off states of the IGBT in the pulse generating circuit, achieving power supply pulses with adjustable frequency and duty cycle. Specialized driver chips and protection circuits are selected and designed to ensure safe and reliable on‑off control of the MOSFET and IGBT.The results show that the continuously adjustable pulse voltage output by the fish barrier electric fence provides better adaptability, enabling the fish barrier effect to match the environment. The effective voltage of the bipolar pulse fish barrier electric fence is 10~15 V lower than that of the unipolar pulse type, and the effect is more significant. This study provides partial experimental basis and data for research on electric fence fish barriers and also offers a technical design reference for the development of fish barrier electric fence system equipment.

Squid is a marine mollusk, stands out as one of the most commercially valuable seafood resources globally, with profound economic significance for China’s marine fisheries sector. As a key species in China’s aquatic product supply chain, squid contributes significantly to the national marine catch volume: data from 2024 shows that China’s total squid catch reached 317,325 tons, accounting for 32.97% of the country’s overall marine catch. This substantial output underscores the urgent need for efficient and precise processing technologies to maximize the economic value of squid products, particularly in the segment of squid tentacle slicing, an essential step in producing value-added products such as frozen squid slices, canned squid, and ready-to-eat seafood snacks. Against this backdrop, this project proposes a novel quantitative cutting solution for squid tentacles, integrating line laser scanning, 3D point cloud reconstruction, improved deep learning, and optimized algorithmic decision-making. The implementation process consists of three core stages: First, a line laser scanning platform was constructed to capture the 3D morphological information of squid tentacles. Given that a single-angle laser scan can only obtain partial point cloud data, the platform performs multiple laser scans of the same squid tentacle from different angles. The acquired multi-angle incomplete point cloud datasets are then processed through point cloud matching and surface reconstruction. This process ultimately synthesizes a complete, high-resolution 3D point cloud model that accurately represents the entire morphological structure of the squid tentacle, including details such as suction cup distribution and local diameter variations. Second, an improved Generative Adversarial Network deep learning model was established to address the potential inefficiency of multi-angle scanning in industrial scenarios. The key improvement lies in integrating an attention mechanism into both the autoencoder and decoder modules of the original GAN architecture. This attention mechanism enables the model to dynamically weight and emphasize valuable feature information during the learning process, while downplaying irrelevant or noisy data. The trained model can efficiently reconstruct the complete 3D structure of a squid tentacle from a single incomplete point cloud, significantly reducing scanning time while maintaining morphological accuracy. Comparative experiments show that the improved GAN model outperforms the baseline GAN model by 6.2% in the Intersection over Union (IoU) index and by 42.4% in the Cross-Entropy (CE) index, demonstrating its superior performance in 3D structure reconstruction. Finally, the quantitative cutting of squid tentacles was transformed into a multi-objective optimization problem, with the core objectives being: minimizing the weight error of each sliced piece and maximizing the overall utilization rate of the squid tentacle. To solve this problem, the Simulated Annealing  algorithm was improved by incorporating domain-specific constraints from squid processing. Cutting tests were then conducted on the 3D point cloud models of squid tentacles using the improved SA algorithm. Experimental results confirm that under the constraint of a single-slice weight error≤8%, the average utilization rate of squid tentacles reaches 87.3%, a significant improvement of 27.3–37.3 percentage points compared to the 50–60% utilization rate of manual slicing. In summary, this project develops a comprehensive quantitative cutting technology for squid tentacles that integrates 3D sensing, intelligent reconstruction, and optimized decision-making. It effectively addresses the inefficiencies, low precision, and high waste of traditional manual and mechanical cutting methods, providing a feasible technical solution for the industrial upgrading of the squid processing industry and laying a foundation for the intelligent transformation of aquatic product processing.

To address the problems of incomplete cleaning of oyster shells and low efficiency in traditional oyster cleaning machines, this paper studies the ultrasonic cooperative cleaning technology and develops an ultrasonic cooperative cleaning device for oysters. Based on the COMSOL Multiphysics finite element simulation technology, the distribution of the ultrasonic field was simulated, and the influence laws and pressure distribution of the ultrasonic cleaning frequency, cleaning cross-section height, and the number of transducers on the sound pressure and sound pressure level in the ultrasonic cleaning domain were clarified. The research shows that the optimal energy distribution of the ultrasonic field is achieved when the ultrasonic cleaning frequency is in the range of 25-45 kHz, the cleaning cross-section height is -125 mm, and the number of transducers is 10. The sound pressure value range is 2.5-4.8×104 Pa. A prototype was manufactured and the cleaning performance was verified. By exploring the effects of feeding rate, cleaning time, and ultrasonic cleaning frequency on the overall cleaning performance of the machine, the results show that the order of influence of each factor on the oyster impurity removal rate is feeding rate > ultrasonic cleaning frequency > cleaning time. Under the operating conditions of an ultrasonic cleaning frequency of 28 kHz, a cleaning time of 5 minutes, and an oyster feeding rate of 1150 g, the impurity removal rate of the device is 5.63%. This study can provide a reference for the development of ultrasonic cleaning devices for oysters.

To address the issue of feed breakage during hydraulic conveying in aquaculture that affects feeding efficiency and water environment. This study employs a CFD-DEM coupled method to develop a solid-liquid two-phase flow model for particle breakage. The research thoroughly investigates the breakage behavior of cylindrical feed particles within curved pipes during hydraulic conveying, with a particular focus on breakage types, fragment size distribution, and mechanisms of energy transformation and dissipation. The results indicate that feed particle breakage primarily manifests as surface peeling, occurring progressively under shear stress rather than via complete fracture. The size distribution of breakage products exhibits a bimodal pattern: large fragments retain the size of the parent particles, whereas small fragments are numerous but contribute relatively little to total mass. Energy dissipation is especially pronounced during collision-induced breakage, with up to 45.2% of energy lost during the initial breakage event, mainly due to the conversion of translational kinetic energy into internal and rotational kinetic energy. This study systematically reveals the breakage behavior of feed particles during hydraulic conveying from three perspectives—microscopic mechanisms, characteristics of breakage products, and energy transformation—providing a theoretical basis for optimizing hydraulic conveying processes to reduce particle breakage.

In order to address the challenges of insufficient ambient lighting, small target size, and target clustering and occlusion leading to decreased detection accuracy in underwater target detection, this study proposes a multi-scale underwater target detection algorithm, FDM-YOLO, based on receptive field features. First, to address the issues of insufficient underwater ambient lighting and the fact that underwater organisms are often small targets with colors similar to their surroundings, the RFCADown module is used to generate large receptive field spatial features, enhancing the extraction of key information about underwater targets. Second, a Dysample upsampling module is introduced to suppress blurring and distortion in traditional upsampling processes. Third, a multi-scale, multi-dimensional information collaboration module, C3K2-IMCA, is designed to improve the representation performance of densely occluded targets. Finally, WIoU is used instead of CIoU loss function to mitigate the negative impact of extreme-shaped bounding boxes on model training for small targets. Experimental results show that FDM-YOLO achieves a 2.1% and 2.0% improvement in mAP50 and mAP@50-95 respectively compared to the benchmark model on the DUO dataset, while the model parameters and computational cost are only 2.35M and 6.0 GFLOPs. The above results verify the efficiency of the improved model in enhancing the detection performance of small underwater targets.

To address the challenges of low detection accuracy and high false positive rates caused by the complex morphology, significant scale variations, and blurred boundaries of lesion areas in Carassius auratus diseases, this paper proposes a novel recognition model named CAI-YOLO based on the YOLOv11 framework. First, the backbone network incorporates the ConvNeXt V2 module. This module utilizes a self-supervised pre-training strategy based on Masked Auto Encoders and introduces a Global Response Normalization layer, effectively mitigating feature collapse and enhancing feature diversity. Second, the neck network integrates AKConv, which leverages an adaptive sampling mechanism to improve the model's multi-scale modeling capability for irregular disease spots. Finally, the loss function employs IF-IOU, which combines the internal constraints of Inner-IOU with the re-weighting mechanism of Focaler-IOU, thereby accelerating model convergence and improving localization accuracy. Experiments conducted on a self-built Carassius auratus disease dataset show that the CAI-YOLO model achieves Precision, Recall, mAP@0.5, and mAP@0.5:0.95 of 85.6%, 87.8%, 86.7%, and 58.6%, respectively. Compared to the baseline YOLOv11n, the mAP@0.5 and mAP@0.5:0.95 are increased by 0.9 and 1.1 percentage points, respectively. Furthermore, the number of parameters, computational complexity, and model size are reduced by 10.89%, 8.19%, and 7.84%, respectively. The research demonstrates that the CAI-YOLO model effectively enhances overall detection performance while simultaneously reducing computational resource requirements, providing a valuable reference for the lightweight design and practical application of Carassius auratus disease detection systems.

At present, the processing of shells for laver seedling cultivation mainly relies on manual edge milling and drilling, which is inefficient and poses safety risks. Therefore, this study designed an automatic shell milling and drilling device for laver seedling cultivation integrated with a PLC control system. The working principle of the device is explained, and structural design and strength verification of the core components of the device are carried out based on theoretical calculation and finite element analysis methods.By building a prototype, the shell breakage rate was used as the test index, and a Box-Behnken experimental design method was adopted to conduct significance tests on the drilling speed, drill feed rate, milling cutter speed, and shell self-rotation speed. The test results were analyzed and optimized to determine the value range of each factor. The test results show that the device operates stably as a whole. Under the optimized experimental conditions of a drilling speed of 3300 r/min, a feed rate of 0.65 mm/s, a milling cutter speed of 4800 r/min, and a self-rotation speed of 11 r/min, the shell breakage rate is only 1.75%, meeting the requirements for productization of shell drilling and milling processing.Research shows that this automatic drilling and milling device has good machining performance, can significantly reduce the breakage rate in the processing of shells used for purple laver seedling cultivation, and has a good application prospect.