New Techniques and Equipment in Large Offshore Aquaculture Platform

The expansion of far-reaching marine aquaculture represents a critical frontier for the sustainable growth of global aquaculture [1,2,3]. This sector is becoming increasingly important in the face of the space constraints, environmental degradation, and regulatory restrictions that limit nearshore aquaculture. The development of advanced technologies and innovative equipment has transformed the aquaculture landscape, enabling operations to be conducted in more challenging offshore environments [4,5]. This Special Issue aims to showcase the latest advancements in far-reaching marine aquaculture technologies and equipment, focusing on key areas such as aquaculture species, breeding technologies, environmental control systems, large-scale platform construction, and cutting-edge aquacultural innovations. The collective results of these studies highlight the potential for future research and expansion of these techniques to other regions and species, driving the aquaculture industry towards more sustainable and productive practices.

A central theme in this Special Issue is the development of new species suitable for far-reaching marine aquaculture and the associated farming techniques required to optimize their growth and health in offshore environments. As aquaculture expands into deeper waters, selecting and developing species that thrive under these conditions is essential. This process requires targeted breeding programs, enhanced disease management protocols, and optimized feeding strategies that account for the specific needs of species in dynamic marine environments. The research presented here highlights the progress made in cultivating these species, including improvements in breeding methodologies and stress management, which are aimed at maximizing productivity while minimizing the ecological impact. The selection of species that exhibit resilience to the unique challenges of offshore aquaculture, such as fluctuating water temperatures, strong currents, and variable salinity, is of particular importance.

Environmental control technologies form another cornerstone of far-reaching marine aquaculture [6]. In offshore settings, maintaining optimal environmental conditions is challenging due to the unpredictable nature of the marine environment. Parameters such as water temperature, salinity, dissolved oxygen levels, and nutrient availability must be carefully monitored and controlled to ensure the health and growth of farmed species. Innovations in sensor technology, automated feeding systems, and real-time environmental monitoring have significantly enhanced the stability of conditions in far-reaching aquaculture environments. These technologies allow precise adjustments to be made in response to environmental fluctuations, ensuring that aquaculture systems remain efficient and productive. This section of the Special Issue delves into the integration of these advanced systems, exploring their role in improving overall aquaculture management and efficiency.

The structural design and construction of offshore aquaculture platforms have undergone significant advancements to ensure the safety and sustainability of operations in open-sea environments. These platforms must be designed to withstand harsh marine conditions, including strong currents, waves, and storms. Recent research has focused on the dynamic motion characteristics of these platforms, particularly the interaction between breeding tanks and wave forces. Optimizing platform stability, durability, and structural integrity is crucial to the long-term success of offshore aquaculture. Innovative designs, such as rotatable net cages and self-cleaning systems, have been developed to enhance water quality and reduce the accumulation of biofouling, which can negatively affect both fish health and operational efficiency. This section explores the latest developments in platform design and their impact on aquaculture productivity and sustainability.

Feeding technologies and fish health management are also crucial to the success of far-reaching marine aquaculture [7]. Precision feeding systems, which utilize real-time data from environmental sensors, have been developed to facilitate more accurate feed distribution, ensuring that fish receive the optimal amount of nutrients while minimizing feed wastage and environmental impact. Additionally, significant progress has been made in understanding the nutritional requirements of species farmed in offshore environments, leading to the development of specialized feed formulations that enhance growth rates and improve fish health. This Special Issue also covers studies on the physiology of fish and their responses to environmental stressors, providing valuable insights into the development of more resilient aquaculture systems capable of withstanding the challenges of offshore farming.

The integration of emerging technologies, such as artificial intelligence (AI), machine learning, and robotics, has revolutionized aquaculture management. AI-driven systems are being used to monitor fish behavior, track health metrics, and optimize feeding regimens in real time, improving both efficiency and sustainability. For instance, image sonar and deep-learning models have been employed to estimate fish populations within cages, allowing for more precise feed allocation and harvest planning. Bio-inspired robotic systems are also being developed to interact with farmed fish, enabling more accurate assessments of their welfare and behavior. These technological innovations enhance operational efficiency and contribute to the sustainable management of offshore aquaculture ecosystems.

The advancements in far-reaching marine aquaculture technologies and equipment presented in this Special Issue represent a major step forward in the development of sustainable, large-scale offshore aquaculture. The research featured here spans a wide range of topics, from species selection and environmental control to platform design and the integration of cutting-edge technologies. Together, these studies provide a comprehensive overview of the current state of far-reaching marine aquaculture and offer valuable insights for future research and application. As the global demand for seafood continues to rise, these innovations will play an increasingly important role in ensuring that aquaculture can meet this demand in an environmentally responsible and economically viable manner. The findings and technologies presented in this Special Issue are poised to shape the future of aquaculture, promoting its expansion into new marine environments and species and driving the industry towards a more sustainable and productive future.

In the first contribution to this Special Issue, Hong et al. present an innovative approach to improving fish pump technology, which plays a crucial role in aquaculture, particularly for deep-sea vessels and cage culture systems. Their research focuses on enhancing the hydraulic performance of a newly designed vacuum fish pump while minimizing damage to the fish during operation. Key aspects of this study include an in-depth analysis of flow dynamics, fluid simulations of the pump body, and the flow channel structure. The authors investigate the effects of variables such as inlet flow rate, pipeline negative pressure, and the impact forces on the tank’s inner walls. Utilizing 167 calculation models based on the Latin hypercube sampling method, they conduct multi-objective optimization using the NSGA-II algorithm to identify optimal structural parameters for the pump. The results indicate that, under the best conditions, the direction of incident water flow is positioned near the upper end of the tank, which reduces the speed of the water–fish mixture as it enters the tank, significantly reducing fish collision damage. The optimal flow velocity at the inlet was found to be approximately 2.5 m/s, with a consistent negative pressure gradient between the tank and inlet pipeline. This design ensures effective fish suction and lifting while also maintaining high survival rates and minimizing the physical harm sustained by the fish. Hong et al.’s work significantly contributes to aquaculture equipment design, providing insights into how hydraulic performance can be optimized for safer and more efficient fish handling.

In their paper, Shen et al. address the persistent challenge of biofouling in aquaculture net cages, which can negatively impact both structural integrity and fish growth. To mitigate this, they propose a novel fixed aquaculture platform equipped with a rotatable horizontal cylindrical cage to facilitate easier cleaning and maintenance. Using ANSYS software, the team develop a numerical model to simulate the platform’s structural response under various conditions, such as waves and currents at three typical attack angles. They calculate the strain, acceleration, and displacement of the structure to evaluate its hydrodynamic performance. The study reveals that as the wave height increases, so do the strain, acceleration, and displacement of the cage, while the wave period has minimal impact. The most unfavorable loading occurs when forces are applied perpendicular to the long axis of the cage. Interestingly, while acceleration increases with water depth, the strain response decreases. Furthermore, when the rotational constraint of the cylindrical cage is released, the cage experiences higher acceleration compared to when it is fixed, though the effect on structural strain and load is minimal. Shen et al.’s research offers valuable insights into aquaculture platform design, highlighting how cage rotation and water depth influence hydrodynamic responses and ultimately aiding in the development of safer, more efficient aquaculture systems.

In their work, Liu et al. address the challenge of fish re-identification (re-ID) under varying environmental and camera conditions, focusing on large yellow croaker. Traditional re-ID methods often struggle with domain distribution differences between fish images captured in different culture settings, limiting the effectiveness of existing training data. The authors propose a novel approach that combines CycleGAN (Cycle Generative Adversarial Network) with transfer learning to overcome these limitations. Their method involves constructing two datasets: one from controllable environments and another from actual farming conditions. The CycleGAN framework is employed to transform images from the source domain to the target domain, enabling data amplification. They further improve identity loss judgment using IDF (Identity Foreground Loss) and narrow the distribution gap between domains with MMD (Maximum Mean Discrepancy). Transfer learning is then applied to the expanded dataset to accurately identify large yellow croaker across different conditions. The experimental results are highly promising, demonstrating recognition accuracies of 96.9% in controlled environments and 94% in real farming conditions. This approach enhances the reliability of fish identification across various settings and lays the groundwork for future advancements in fish behavior tracking and phenotype measurement, providing essential technical support for the development of intelligent aquaculture systems.

In their manuscript, Tao et al. examine the critical impact of sloshing responses on the design and operational efficiency of aquaculture vessels. Sloshing, the movement of liquid inside a partially filled tank, significantly affects both the safety of culture equipment and the overall efficiency of aquaculture operations. To analyze these dynamics, the authors conducted experiments using a 1/50 scale model of a novel aquaculture vessel in a controlled wave basin. They explored sloshing behavior under two wave directions—beam and head waves—and two fill levels of 81.5% and 47.4%. The study investigated both time-domain and frequency-domain characteristics of sloshing under regular and extreme sea conditions. Their findings revealed that the sloshing response is primarily driven by the wave frequency, with more pronounced effects under beam wave conditions than head waves. The response was also stronger for a half load than a full load. The complexity of the sloshing mechanism stems from the interaction between external waves, vessel motion, and internal liquid movement. The results of irregular wave tests supported the conclusions of regular wave tests, but they also highlighted the presence of stronger nonlinearity and more prominent higher natural modes, with greater amplitude. Tao et al.’s research offers crucial insights into optimizing aquaculture vessel design by understanding sloshing behavior, providing valuable data for enhancing operational safety and efficiency in dynamic marine environments.

In their contribution, Wang et al. investigate the influence of different photoperiods on the growth performance and physiological responses of juvenile scalloped spiny lobsters (Panulirus homarus), a species that is of high economic value in aquaculture. Over 56 days, the researchers exposed 90 lobsters to varying light–dark cycles (0L:24D, 6L:18D, 12L:12D, 18L:6D, 24L:0D) and carefully measured growth rates, digestive and immune enzyme activities, as well as antioxidant enzyme responses. The study found no significant differences in survival rate, molting frequency, or meat yield among the different photoperiod treatments. However, the 12L:12D photoperiod resulted in the highest weight gain rate (WGR) and specific growth rate (SGR), indicating that this balanced light–dark cycle is optimal for lobster growth. Under continuous darkness (0L:24D), pepsin activity remained elevated in gastric tissues, while trypsin and chymotrypsin activities were highest in the hepatopancreas. Other key enzymes, such as α-amylase, lipase, and acid phosphatase, showed peak activities under different light conditions, with optimal lipase activity recorded at 12L:12D and the highest α-amylase activity at 18L:6D. In terms of antioxidant capacity, the study showed that the total antioxidant capacity (T-AOC), catalase (CAT), and superoxide dismutase (SOD) activities were highest under the 12L:12D photoperiod. Additionally, the highest levels of glutathione peroxidase (GSH-Px) were observed under 18L:6D. Malondialdehyde (MDA), an indicator of oxidative stress, peaked at 12L:12D. These results suggest that the 12L:12D light–dark cycle is essential for achieving optimal growth and maintaining physiological balance in juvenile scalloped spiny lobsters. Wang et al.’s findings offer valuable guidance for optimizing lighting conditions in aquaculture settings to enhance the growth and health of this species.

In their work, Pino et al. delve into the use of zebrafish (Danio rerio) as a model organism for neurobehavioral research, particularly in the context of stress, fear, and anxiety responses. Their research explores the effects of bio-inspired mini robotic fish, designed with various components, on zebrafish behavior. The primary goal of the study is to optimize robotic biomimicry to minimize stress and improve fish welfare, which could have broader applications in aquaculture. While previous studies predominantly focused on externally controlled fish models, Pino et al. introduce novel prototypes of freely actuated swimming robots. These robots allow for more natural interactions between the bio-inspired robots and the zebrafish. By analyzing the zebrafish’s behavioral responses, the researchers identify specific robotic components that may induce anxiety in fish. These findings not only enhance our understanding of zebrafish stress responses but also offer valuable insights for designing future bio-inspired robotic systems in aquaculture, aiming to minimize stress and ensure the welfare of aquatic species.

In their study, Wang et al. investigate the effects of acute seawater acidification on the antioxidant defenses, metabolic performance, and liver histology of juvenile yellowfin tuna (Thunnus albacares). The experiment exposes the tuna to a pH gradient ranging from 8.1 to 6.6 over 48 h, simulating acidification stress. The results reveal that a pH of 7.1 significantly disrupts the antioxidant and metabolic systems of the fish compared to the control group. Specifically, at this pH level, notable increases are observed in glutathione reductase (GR), total antioxidant capacity (T-AOC), lactate dehydrogenase (LDH), hexokinase (HK), pyruvate kinase (PK), sodium–potassium ATPase (Na⁺K⁺-ATP), and calcium-magnesium ATPase (Ca²⁺Mg²⁺-ATP). Despite these changes, levels of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TGs) remained relatively stable across all treatment groups. However, the study also detected elevated transaminase levels at pH 7.1, indicating potential liver damage corroborated by signs of liver tissue degeneration and hepatocyte vacuolation. These findings suggest that acute acidification leads to a reduction in antioxidant capacity and a suppression of metabolic activity in juvenile yellowfin tuna, ultimately causing oxidative damage. Wang et al.’s research provides critical insights into the physiological responses of yellowfin tuna to seawater acidification, offering a foundational understanding of the mechanisms behind acidification stress. The study also underscores the broader implications for sustainable tuna farming in the face of changing ocean conditions.

Sun et al.’s work examines the impact of acute ammonia nitrogen (NH3-N) exposure on the kidney’s antioxidant capacity, phosphatase activity, and related gene expression in juvenile yellowfin tuna (Thunnus albacares). A total of 180 juvenile tuna are exposed to varying NH₃-N concentrations (5 and 10 mg/L) for 6, 24, and 36 h, with natural seawater (0 mg/L) serving as the control. The study measures the levels of malondialdehyde (MDA), a marker of lipid peroxidation, and antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), alkaline phosphatase (AKP), and acid phosphatase (ACP) to evaluate changes in antioxidant activity and immune-related phosphatase function in the trunk kidney. At 36 h, MDA, SOD, CAT, and GSH-PX levels significantly increase in the 5 mg/L group compared to the control, with even higher elevations in the 10 mg/L group after 24 and 36 h. Phosphatases, which play a key role in immune responses, also show marked activity increases—AKP surges at 6 h, and ACP rises significantly at 36 h in the 5 mg/L group. Using real-time fluorescence quantitative PCR, the authors observe significant upregulation of antioxidant genes SOD2 and GPX1b in the 5 mg/L group at 6 and 36 h, while similar upregulation is seen in the 10 mg/L group at 36 h. Additionally, immune cytokine gene expression shows an increase in Interleukin 10 (IL-10) in the 5 mg/L group at 6 h, whereas Interleukin 6 receptor (IL-6r) expression decreases. Both IL-10 and IL-6r levels were suppressed in the 10 mg/L group. The findings suggest that low concentrations of NH3-N (around 5 mg/L) enhance antioxidant defenses, phosphatase activity, and gene expression, while higher concentrations (10 mg/L) may have a suppressive effect. In juvenile yellowfin tuna farming, managing NH3-N levels is critical for health; at concentrations between 5 and 10 mg/L, stress exposure should be limited to 24 h, whereas concentrations below 5 mg/L allow for extended exposure up to 36 h without adverse effects.

In their contribution to the Special Issue, Yang et al. investigate the effects of licorice (Glycyrrhiza uralensis) as a feed additive on the growth performance and gene expression of Asian seabass (Lates calcarifer), a species that holds significant economic importance in China’s aquaculture industry. While licorice has been known for its immunological benefits in aquaculture, its impact on growth has been less explored. This study aims to fill that gap by evaluating the influence of various concentrations of licorice (0%, 1%, 3%, and 5%) in artificial feed on the expression of growth-related genes over 56 days. The key growth-related genes analyzed include growth hormone–releasing hormone (GHRH), growth hormone (GH), growth hormone receptor (GHR), insulin-like growth factor 1 (IGF1), IGF2, IGF2 receptor (IGF2R), and myostatins (MSTN1 and MSTN2). The results demonstrate that diets supplemented with 3% and 5% licorice significantly improve survival rates and weight gain in comparison to the control group. Notably, licorice supplementation enhances the expression of GHR and IGF1 in the liver, while a 5% licorice diet downregulates IGF2 expression. As the licorice concentration increases, IGF2R and MSTN1 expression initially decreases and then increases, while MSTN2 expression is inhibited. Moreover, licorice supplementation significantly downregulates the expression of GH and GHRH. Yang et al.’s findings suggest that the inclusion of licorice in the diet of Asian seabass, particularly at optimal levels, can boost growth-related gene expression, thereby enhancing both the weight gain rate and specific growth rate of the fish. This research offers valuable insights into the potential of licorice as a feed additive to improve the survival and growth of Asian seabass in aquaculture settings.

In their work, Zhu et al. propose an innovative method for accurately estimating fish quantities in aquaculture cages using image sonar technology. To meet the challenges of real-time fish counting in dynamic environments, the authors utilize forward-looking image sonar combined with the YOLO target detection model, enhanced by an attention mechanism and a backpropagation (BP) neural network. This integrated approach enables continuous, automated estimation of fish numbers within cages. The research involves conducting a quantitative experiment in the South China Sea to create a comprehensive dataset for training both the YOLO model and the neural network. The improved YOLOv8 model achieves an average detection accuracy (mAP50) that is 3.81% higher than that of the original algorithm. Additionally, the neural network’s accuracy in estimating fish quantities reaches 84.63%, outperforming cubic polynomial fitting by 0.72%. Zhu et al.’s work significantly advances aquaculture management, providing a precise method for assessing fish quantities. This allows for more informed decision-making with regard to feeding strategies and harvest planning, contributing to the overall efficiency and sustainability of aquaculture operations.

In response to increasing limitations in coastal aquaculture environments and the need for larger-scale operations, Zhang et al. explore the potential of deep-sea aquaculture using large-scale aquaculture vessels. These vessels offer new opportunities for expanding aquaculture into deeper waters, but their success requires the optimization of tank design to ensure ideal fish growth conditions and effective removal of particulate matter. This balance is essential for maximizing productivity and profitability in aquaculture vessels. Zhang et al.’s study specifically investigates how the structural ratio of aquaculture tanks impacts flow field characteristics and particulate removal efficiency. Using FLOW-3D software (solver version: 11.2.0.16), they conduct numerical simulations on the flow field of an 8000-ton aquaculture vessel at anchor. Their simulations evaluate the impact of the corner ratio on key parameters such as flow velocity, turbulence intensity, tank utilization, and particulate removal efficiency. The results indicate that tanks with corner structures exhibit better overall flow dynamics, including higher flow velocities, stronger turbulence, and improved particulate discharge efficiency. However, the study also finds that further increases do not significantly improve these flow characteristics once the corner length exceeds one-third of the tank length. The findings provide a valuable reference for the structural design and optimization of aquaculture tanks, contributing to the efficiency and effectiveness of large-scale deep-sea aquaculture vessels.

In their paper, Hu et al. introduce a novel approach for accurately estimating the distribution of Trachinotus ovatus in marine cages, leveraging omnidirectional scanning sonar and deep-learning techniques. Their method provides precise fish location data by segmenting the water into layers and applying clustering algorithms to analyze the data from each layer. The process begins with omnidirectional scanning sonar, which performs a spiral detection within the cages to capture fish image data. These images are then labeled to construct a training dataset for an enhanced CS-YOLOv8s model. Once trained, the CS-YOLOv8s model is employed to identify and locate fish in the images. Next, the cage environment is divided into water layers, with depth intervals of 40 cm. The DBSCAN clustering method is applied to the identification coordinates for each layer, generating precise location data for fish at various depths. Finally, the data from all layers are combined to form a comprehensive map of fish distribution within the cage. The method is tested through extensive experimentation and accurately estimates the distribution of Trachinotus ovatus, with results closely matching manual observations. Hu et al.’s approach represents a significant advancement in using sonar and deep-learning technology for aquaculture, providing a more efficient and automated method for managing fish populations in marine cages.

In their work, Liu et al. address the challenges of deep-sea aquaculture, which offers significant potential to alleviate the spatial and environmental pressures associated with near-shore operations while producing higher-quality aquatic products. Despite China’s relatively flat coastline, where aquaculture typically occurs in waters 30–50 m deep, the frequent typhoons and adverse sea conditions make designing effective mooring systems for deep-sea cages challenging. Liu et al.’s study investigates multiple fish cage configurations, focusing on a 1 × 4 layout and a 2 × 2 layout, and proposes three distinct mooring system design schemes. The researchers compare mooring line tension under different self-storage conditions, examining factors such as line accumulation and contact with the steel structure on the leeward side. Furthermore, flexible net models are compared to rigid net models to assess how net deformation influences cage movement and mooring line tension. Liu et al. also analyze the dynamic response of the optimal mooring design under irregular wave conditions, offering valuable insights into the safety and economical design of mooring systems for multiple fish cages. Their findings provide essential guidance for improving the reliability and resilience of deep-sea aquaculture systems, particularly in regions prone to challenging sea conditions.

In the final contribution, Martzikos et al. explore the integration of renewable energy sources with aquaculture on floating multi-use platforms, aiming to create sustainable offshore infrastructure. From March 2021 to January 2022, a 1:15 scale prototype was tested in Reggio Calabria, Italy, providing insights into the structures’ behavior under various wave conditions. The study utilizes Artificial Neural Networks (ANNs) to predict changes in mooring loads at critical points, analyzing metocean data to evaluate different ANN models and optimization techniques. The best predictive model achieves a Normalized Root Mean Square Error (NRMSE) of 1.7–4.7%, demonstrating the effectiveness of ANNs in forecasting offshore platform dynamics. This research underscores the potential of machine learning for sustainable ocean system management, paving the way for advancements in data-driven marine resource management.