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Aspect-based sentiment analysis has achieved many results in recent years, but most of the research focuses on goods, services, and topics. The research in the medical field is very limited. Considering the problem that the fish disease descriptions contain large numbers of emotional tendencies but the existing data are insufficient in this field, a dataset named Diseases of Fish Animals (DFA) is constructed. In this paper, we propose a feature interaction model based on an adversarial strategy to learn the relationship between aspects and texts by improving the attention mechanism. Aiming at the problem that the fusion effect is reduced due to the difference in feature distribution space during the interaction process, an adversarial strategy is designed to align text and aspect features. Experiments are carried out on the DFA dataset, which involves 7 aspects and 3 sentiment polarity and contains more than 4700 samples. The experimental results show that the accuracy and F1 of the model are 87.07% and 87.19% respectively. Although the model proposed in this paper achieves the best results on DFA, there is still a certain gap for precision medicine diagnosis and further efforts are needed. [ABSTRACT FROM AUTHOR]

In response to the challenges of accurately identifying event triggers and elements in long texts related to aquaculture, existing models struggle to differentiate between elements and triggers, as well as effectively recognize complete entity texts. To tackle this issue, this study proposes an algorithm for extracting fish disease events based on pseudo triggers and augmented event element data. The method starts by constructing pseudo samples using the original dataset. Two types of noise datasets are then generated: a trigger noise dataset constructed based on fish disease triggers and an entity noise dataset with varying levels of entity noise constructed based on fish disease entities. Next, three parallel neural networks are deployed to extract sample features from these datasets. The fish disease event extraction for the source dataset employs multi-label classification. For the trigger noise dataset, the sample features are activated using the sigmoid function, and the MRSE loss is utilized for optimization of this branch. For the entity noise dataset, the sample features are activated using the Relu function, and the XOR loss is used for optimization. Finally, the losses from the three branches are combined with weighted summation to obtain the fusion loss. The experimental results on the fish disease dataset used in this paper show that the proposed algorithm achieves an average accuracy of 78.71%, 78.95%, and 79.43% on F1, recall, and precision, respectively, which is a maximum improvement of 11.201%, 11.849%, and 12.421% in accuracy with respect to the baseline model on F1, recall, and precision, respectively. [ABSTRACT FROM AUTHOR]

Image semantic segmentation is widely used in aquatic product measurement, aquatic biological cell segmentation, and aquatic biological classifications. However, underwater image segmentation has low accuracy and poor robustness because of turbid underwater environments and insufficient light. Therefore, this paper proposes an Underwater Image Semantic Segmentation Network (UISS-Net) for underwater scenes. Firstly, the backbone network uses an auxiliary feature extraction network to improve the extraction of semantic features for the backbone network. Secondly, the channel attention mechanism enhances the vital attention information during feature fusion. Then, multi-stage feature input up-sampling is used to recover better semantic features in the network during up-sampling. Finally, the cross-entropy loss function and dice loss function are used to focus on the boundary semantic information of the target. The experimental results show that the network effectively improves the boundary of the target object after segmentation, avoids aliasing with other classes of pixels, improves the segmentation accuracy of the target boundary, and retains more feature information. The mean intersection over union (mIoU) and mPA of UISS-Net in the semantic Segmentation of Underwater IMagery (SUIM) dataset achieve 72.09% and 80.37%, respectively, 9.68% and 7.63% higher than the baseline model. In the Deep Fish dataset, UISS-Net achieved 95.05% mIoU, 12.3% higher than the traditional model. [ABSTRACT FROM AUTHOR]

In aquaculture, real-time and rapid detection of dead fish is important for early risk warning and improving aquaculture efficiency. However, the complex actual environment and uncontrollable fish movement have brought great challenges to the detection of dead fish. Therefore, this paper proposes a high-precision and lightweight dead fish-detection transformer (DF-DETR) based on machine vision and original RT-DETR (real-time detection transformer). The specific implementation is as follows: Firstly, the backbone of the original RT-DETR was replaced by the RepNCSPELAN module which extracts multi-scale features. This not only improves the model’s ability to detect targets of different sizes but also reduces the amount of model parameters. Secondly, the AIFI in the RT-DETR was improved to CascadedGroupAttention (CGA). By changing the original feature fusion method, different levels of features are grouped and attention mechanism is added, so as to capture more target features. Finally, the CCFM_CSP module was constructed to fuse important features using parallel dilated convolution with different expansion rates, which improves the detection accuracy. The experimental results show that the mAP@.5 of the proposed dead fish detection model DF-DETR can reach 96.6%, and the parameter amount is reduced by 27% compared with the original RT-DETR. In summary, the proposed DF-DETR model realizes real-time and high-precision dead fish detection, which can provide effective technical support for the development of intelligent inspection robots. [ABSTRACT FROM AUTHOR]

In recent years, shrimp aquaculture has become one of the most promising and fastest-growing aquaculture industries in providing aquatic food globally. In comparison with other aquatic products, shrimp plays an important role because of its high export value and self-employment opportunities provided for farmers and stakeholders along its value chain in developing countries. This study attempts to provide some insights into the export-agricultural growth nexus by considering the aquaculture shrimp industry. The objective of this paper is to analyze the effects of shrimp exports on aquaculture shrimp production over the period 1998–2022 for the major South Asia and Southeast Asian shrimp-producing countries. By using the cointegration approach and panel autoregressive (PVAR) model, empirical findings indicated that there is no causal relationship between the volume of shrimp aquaculture production, its exports, imports, and the domestic prices in the long run and the short run. In addition, the results of the PVAR approach did not show enough evidence to support the assumption that growth in shrimp exports can enhance growth in the production of aquaculture shrimp perhaps because of the small sample size or other plausible reasons. However, our findings evidence that exports rather than imports explain much of the variation in aquaculture shrimp production across time. Despite the limitations of evidence, hence suggesting the need of more data, these findings have some policy implications in providing insights to the governments in countries where aquaculture (shrimp industry) have considerable importance. Exploring all possible ways to increase or promote aquaculture shrimp production can help shrimp producers in South Asia and Southeast Asia countries and, by extension, all shrimp production countries globally. Evaluating the shrimp exports-production growth nexus or similar work to this current study could be carried out by incorporating more countries and variables over a much longer period. [ABSTRACT FROM AUTHOR]

In recirculating aquaculture system, precise estimation of perch size from images is essential for developing intelligent management system. However, variations in fish postures and visual field lead to different fish sizes in RGB images, posing challenges for accurate fish detection and localization. To address the above issues, this paper proposes a nondestructive target detection and size measurement method for perch, based on depth information and RGB-D images. The details are as follows: firstly, the capture ability of perch key point features is augmented by a bi-level routing attention (BRA) mechanism. Secondly, the enhanced CSPDarknet53 to 2-Stage FPN(C2f) module and new detection layer are introduced into the model’s backbone and neck, further improving the learning ability of perch features and the recognition accuracy of small-size targets. Finally, based on the detected key point coordinates, the perch size is calculated by combining the three-dimensional transformation from depth camera and measurement model. The experimental results show that the mAP@.5:.95 for key point detection reaches 86.4%, which is 3.6% higher than the baseline model, and the average relative error of perch size measurement is ± 5%. The proposed model provides an important basis for developing scientific feeding strategies and harvest plans. [ABSTRACT FROM AUTHOR]

The burgeoning field of the aquaculture industry has experienced a paradigm shift over the last three decades with the introduction of triploid animals. This review paper aims to dissect the comparative investigations on the performance of triploid and diploid animals within aquacultural practices, focusing on salmonids and oysters. The core of this article lies in the application of omics platforms, encompassing genomics, transcriptomics, proteomics, and metabolomics, to a comprehensive understanding of the intricacies of triploid biology in contrast to their diploid counterparts. Omics technologies have developed as crucial tools in studying triploid fish and bivalves, offering unprecedented visions into their genomic, transcriptomic, proteomic, and metabolic makeups. These visions are vital for enhancing our understanding of triploid performance, often marked by increased growth rates and partial or complete reproductive sterility, making them highly valuable for aquaculture. The paper highlights the importance of omics in identifying the molecular determinants of these desirable traits, thereby providing a molecular lens through which the efficacy of triploid aquaculture species is assessable. The review synthesizes the main findings from various omics platforms, revealing that triploids display distinct molecular profiles that confer them with superior aquacultural qualities. These comprise alterations in gene expression patterns related to growth and stress response, gonadal development, nutritional requirements, and unique metabolic adaptations. Providing a comprehensive omics-based comparison illuminates the path forward for optimizing triploid production, ensuring food security, and advancing the aquaculture industry toward a more sustainable future. [ABSTRACT FROM AUTHOR]

Monitoring and evaluating fish growth and health relies on accurate aquaculture body size and weight data. Pearl's gentian grouper has tender flesh and rapid growth, and the scale of aquaculture is increasing yearly. Moreover, it is inefficient to measure body size and weight data manually regularly, so in this paper, taking pearl gentian grouper as the research object, we propose a body size and weight estimation method based on machine vision and improve DeepLabV3 + algorithm, with the MIoU reaching 97.37% on the self-constructed dataset, to extract the closed contour of the fish body curve, then apply the algorithm for measuring body scale traits. This paper determines the critical points of body scale calculation. It uses the calibration coefficients to calculate the body scale parameters and then estimate fish body weight. In the established body weight estimation model, the coefficient of determination of the CatBoost regression model based on the total length, body height, body thickness, and area of the fish was R2 of 0.987 which realized the high-precision estimation of the body weight of the pearl gentian grouper and provided the basis for intelligent grading. [ABSTRACT FROM AUTHOR]

The detection technology of soft-shell crab breaks the traditional soft-shell crab breeding method. Conventional farming practices rely heavily on human labor for the identification of soft-shell crab birth, and manual inspections are prone to issues such as delayed and inaccurate results. In this paper, we propose an improved high-precision detection algorithm called YOLOF based on YOLOv5. This algorithm achieves precise detection of soft-shell crab. To address the absence of soft-shell crab detection datasets on the internet, this paper establishes the Crab Molting Detection Dataset (CMP) for the purpose of training neural networks. The detection algorithm has undergone several improvements in the following aspects: the introduction of the FassterNetT1 feature extraction network to replace the original CSPDarknet53 backbone network significantly reduces model complexity and computational overhead; The incorporation of an additional auxiliary prediction feature layer of size 5 × 5 enhances the model's adaptability for detecting various molting states of crabs; the activation function GeLU was introduced, to enable the model to extract features more smoothly and reduce information loss during feature extraction; additionally, the definition of Mixed Convolution (MConv) was proposed to replace Partial Convolution (PConv) in the FasterNet Block. MConv exhibits comparable speed to PConv while possessing high-performance convolution capabilities, allowing the backbone network to extract more abundant semantic information; The introduction of the Content-Aware ReAssembly of FEatures (CARAFE) operator, a universal upsampling algorithm, enhances the extraction of crab shell contour information, thereby improving the model's accuracy in detecting soft-shell crab; addition of an Explicit Visual Center (EVC) in the network neck to strengthen the model's grasp of long-range dependencies and critical information in the image, enhancing the model's robustness. The experimental results demonstrate that YOLOF achieves a 5.4% improvement in mean average precision compared to the original YOLOv5s algorithm. The average precision for the classes "shedding_crab" and "end_unshell" increased by 1.7% and 16.3% respectively. The model running speed is 28FPS, indicating that the proposed YOLOF algorithm can accurately and efficiently identify the molting states of crabs. This study provides the theoretical foundation and technical support for the realization of an automated system for soft-shell crab cultivation. [ABSTRACT FROM AUTHOR]

Nanoparticles offer unique physiochemical properties and diverse applications, providing significant advantages for fish culture. Their antimicrobial properties effectively combat bacterial, viral, and fungal infections, addressing crucial challenges in aquaculture. Moreover, nanoparticles are efficient carriers for delivering therapeutic agents, vaccines, and immune stimulants directly to fish, optimizing treatment and minimizing environmental impacts. Therefore, researchers are focusing more on developing optimal dosage and delivery mechanisms and their interaction between nanoparticles and the fish immune system. In this paper, we will discuss the recent applications of nanotechnology in aquaculture, including feed ingredients, fish medicine, wastewater treatment, and fish packaging fisheries accessories. It will also emphasize nanoparticle utilization's potential benefits and challenges in fish culture. Nanoparticles could be applied through fish feed to enhance growth, reproduction, and other aspects, added to water for treatment, or administered via injection. By incorporating nanomaterials into feed, fish improve their appearance and become stronger and healthier, effectively preventing diseases. This paper explores various applications of nanotechnology in fish culture, including enhancing fish medicine, facilitating sex reversal, achieving optimal nutrition, and improving water treatment practices. [ABSTRACT FROM AUTHOR]

The establishment of the China-ASEAN Free Trade Area has prompted closer cooperation in aquatic products trade between China and Vietnam. Studying the aquatic trade situation and export trade growth dynamics of China and Vietnam can help clarify the aquatic trade relationship between China and Vietnam and promote the sustainable development of bilateral aquatic trade cooperation. This paper analyzes the trade growth dynamics of aquatic products exported from China and Vietnam from 2002 to 2020 using the ternary marginal method. The trade growth pattern of aquatic products exported from China to Vietnam is "both quantity and price growth," and the trade growth pattern of aquatic products exported from Vietnam to China is "quantity growth mainly, extensive growth supplemented." The two countries have apparent differences in the growth dynamics of aquatic products export trade. Moreover, there is a higher complementarity when exporting Vietnam's aquatic products to China than China's aquatic products to Vietnam. Based on these, analyze the factors affecting the growth dynamics of Vietnam's aquatic products export to China: Vietnam's economic development level negatively affects the price index and quantity index of Vietnam's aquatic products exported to China, and Vietnam's aquatic product output affects the price index. China's trade freedom positively affects the price index and negatively affects the quantity index. Finally, this paper put forward suggestions to promote the sustainable development of bilateral aquatic products trade between China and Vietnam to facilitate the formulation of relevant policies between the two countries. [ABSTRACT FROM AUTHOR]

The classification of underwater fish species holds significant importance for fisheries management. Nevertheless, existing deep fish classification models require high computational resources, which hamper their deployment on underwater devices. Additionally, the complex underwater environment, the camouflaged appearance of fish, and the similarity among fish species pose challenges to the accuracy of lightweight fish classification models. To address the above issues, this paper proposes a novel two-tier knowledge distillation (T-KD) method to improve the accuracy and reduce the parameters of the underwater fish species classification models. Specifically, the T-KD involves the following key steps. Firstly, a new fish species dataset, Fish37, is constructed to augment the diversity of fish species present in existing datasets. Subsequently, we introduce a novel interlayer mapping similarity-preserving (IMSP), to facilitate the learning of richer discriminative features by capturing the mapping relationships between teacher and student network layers. Moreover, a new layer tail response (LTR) is proposed to mimic the predictions of the teacher network, efficiently improving classification performance and generalization capability. The proposed T-KD approach demonstrates remarkable performance in fish species classification, surpassing that of well-known lightweight models. The effectiveness of T-KD is extensively validated across various network depths, including ResNet and EfficientNet, and compared to other knowledge distillation methods like KD, PKT, RKD, and SP. Notably, T-KD outperforms MobileNetv3-large and obtains an impressive Top-1 accuracy of 97.20% on the Fish37 dataset only using about 1/15 model size of Vision Transformer. Furthermore, detailed generalization experiments are conducted to assess T-KD's performance on popular benchmark datasets, such as A_Large_Scale_Fish_Dataset, Fish4knowledge, WildFish and WildFish++. In conclusion, the results indicate the potential of the T-KD to facilitate underwater fish species classification with limited computational resources on underwater devices. This research also opens up promising avenues for the practical implementation of lightweight fish classification models. [ABSTRACT FROM AUTHOR]

Aiming at the problem that inserting a needle into the abdomen of spindle-shaped fish can easily damage the internal organs during vaccine injection, this paper takes grass carp as the experimental object and designs a fry adsorption injection device. Through theoretical analysis, the key factors affecting the adsorption force are determined. The internal cavity of the adsorption block is simulated and optimized under the given boundary conditions. The single-factor test shows that the H-shaped suction head has the best adsorption effect. Further orthogonal experiments found that the height of the adsorption port, the adsorption port's length, and the diameter of the adsorption port are important factors that affect the test results, and they are arranged in descending order of their importance. The optimal parameter combination is the adsorption port height of 3 mm, adsorption port length of 15 mm, and adsorption pore diameter of 3 mm. Under these parameters, the success rate of needle insertion is 98%, and the survival rate of fry is 100%, which can meet the production requirements. In summary, the adsorption and injection device is simple in design, easy to operate, and can significantly reduce the damage to the fish body. It provides an effective solution and design reference for fish vaccination. [ABSTRACT FROM AUTHOR]

Algal oligosaccharides (AOS) have been shown to effectively promote plant growth. While there have been many studies on the use of AOS in promoting crop growth, few have investigated their potential in improving ecological floating bed wastewater treatment. Therefore, this paper aims to explore the effects and mechanisms of AOS in enhancing ecological floating bed wastewater treatment. Water spinach was cultivated in aquaculture wastewater treated with varying concentrations of AOS (0.025, 0.05, 0.1, and 0.2 mg/L), with an ecological floating bed without AOS serving as the control group. Results shows the addition of AOS can significantly enhancing ecological floating bed plant and microbial accumulation, resulting in profound improvement in ecological floating bed wastewater treatment efficiency. This is evident in the increased plant height, stem diameter, main root length, number of roots, leaf area, above water-surface fresh weight, below water-surface fresh weight, above water-surface dry weight, below water-surface dry weight, chlorophyll a, chlorophyll b, and chlorophyll content. The combination of 0.05 mg/L AOS with the ecological floating bed exhibits the most favorable results, with percentage increases in various indicators were 44.0%, 52.9%, 29.9%, 62.0%, 28.0%, 141.6%, 84.0%, 97.7%, 220.0%, 24.6%, 34.2%, 26.9% compared to the control group. The addition of AOS to the water spinach ecological floating bed system significantly enhances the removal efficiency of water turbidity, chemical oxygen demand (COD), ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), total nitrogen (TN), and total phosphorus (TP) water quality indicators. This experiment also investigated the differences in microbial community structure between the control group and the group with the optimal concentration of AOS to study the mechanism of action of AOS. The combination of 0.05 mg/L AOS with the ecological floating bed demonstrates the optimal removal efficiency. This study offers crucial technical insights for further optimizing ecological floating bed technology and improving water purification efficiency. [ABSTRACT FROM AUTHOR]

In light of Vietnam's significant role as a top ten seafood exporter, particularly in shrimp and catfish, the COVID-19 pandemic has disrupted the nation's crucial seafood production and exports since early 2020. Our investigation, which is based on farmer surveys and enterprise interviews, has revealed a significant increase in production costs, especially in intensive shrimp farming, which has had a greater impact on compared to semi-intensive farming. Approximately 51.6% of farmers reported a strong effect on feed expenses, with 39.6% categorizing it as a very strong effect. This represents a significant impact on input costs, primarily due to challenges in sourcing materials, particularly feed, which constitutes the highest proportion of production costs. Challenges in goods exchange along the supply chain were strongly reported by 75% of enterprises, with 25% describing them as very strong, thus affecting production costs and inventory. Labor costs have also increased due to COVID-19, with 25% reporting a strong influence and 75% indicating a stable impact. The pandemic has affected commercial pangasius prices, with 29.7% of respondents noting a decrease and 41.8% confirming increased raw material costs, especially for fish feed. Feed costs account for 85.6%, while seed costs comprise 5.1% of total expenditure. Supply chain disruptions have led to enterprises having to suspend operations or reduce operating capacity to 30–40% due to a shortage of workers. The paper suggested practical management and technical solutions, emphasizing the need for supportive policies and a government-led mechanism to assist workers. This study offers valuable insights into the industry's resilience and adaptive mechanisms to face post-pandemic challenges. [ABSTRACT FROM AUTHOR]

Aquaculture is an important economic and food source in many countries. Due to environmental restrictions and the effects of aquatic diseases, aquaculture requires a lot of labor and expensive materials, and it relies on the expertise of aquaculture experts. The quality of water is essential for aquaculture development. Therefore, in this paper, a novel aquaculture water quality monitoring using autonomous sensors (AquaSense) has been proposed which uses autonomous sensors for efficient monitoring of water in the aquaculture environment. In the AquaSense framework, temperature, pH, dissolved oxygen, and salinity measurements are recorded and collected using a variety of autonomous sensors. Based on the information gathered, users can assess the condition of their farm through the Internet. The MATLAB R2012b platform is employed to verify the effectiveness of the suggested water quality (WQ) monitoring technique and analyze the data. Several criteria including accuracy, precision, recall, specificity, and f1-score have been used to assess the effectiveness of the suggested strategy. AquaSense achieves the high accuracy ranges of 96.98%, and existing techniques ISAS, AquaStat, and IoT-WQI FIS achieve 91.24%, 93.39%, and 88.92%, respectively. [ABSTRACT FROM AUTHOR]

The fisheries and aquaculture sectors are growing rapidly, reflecting their importance in meeting the ever-increasing human population's demands for animal protein. Production progress in this sector, however, is challenging as a result of increased deaths from epidemics caused by bacterial infectious diseases in aquaculturally important species. In order to minimize the impact of such diseases, quick and reliable diagnosis of pathogens, timely intervention, and control of the disease are essential to ensure the health of aquaculture and fisheries stocks. Thus, high-throughput proteomics-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used as a rapid, accurate, and species-specific tool for the identification of bacterial fish pathogens and antibiotic resistance. The aim of this article is to review and evaluate the results of nearly three hundred papers published from 2010 to 2023 on the application of MALDI-TOF MS in aquaculture, showing that this method has been increasingly used over the years for the species-level identification and antibiotic resistance of fifty different gram-positive and negative bacterial aquatic pathogens encountered in wild or cultured fish, shellfish, invertebrates, and crustaceans. In addition, the history and general principles of the MALDI-TOF MS method are also mentioned in the article so that fish disease researchers interested in the use of this technology can see all aspects of the topic. [ABSTRACT FROM AUTHOR]

The pikeperch (Sander lucioperca, Linnaeus, 1758), with its unique characteristics, has gained increasing attention in the aquaculture sector. These include its highly valued and delicious meat, soft white tissue with few intermuscular bones, commendable growth performance, and favorable market acceptance. It is farmed in North, Central, Western, and East Europe through recirculation aquaculture systems (RAS), net pens, and pond aquaculture. Nevertheless, the sensitivity of pikeperch to environmental changes and other aquaculture activities has made the need to provide optimal rearing conditions for the growth and survival of this valuable species a priority in its propagation and rearing industry, whereas the aquaculture stressors (e.g., handling, transporting, stocking density) and environmental conditions (e.g., photoperiod, temperature, oxygen status, water quality, oxidative stress) are inevitable factors in pikeperch aquaculture industries that affect the entire life cycle. Meanwhile, examining the adaptive or maladaptive responses of pikeperch to these stressors, in addition to being able to determine the tolerance limit of the fish, sheds light on the type of tissue, involved organs, and adaptive or maladaptive drivers of the fish. Certainly, identifying this tolerance limit and the organs involved is crucial to optimize the breeding conditions and provide the welfare of these valuable species. Hence, the effects of environmental stressors on pikeperch physiological changes deserve further investigation. Therefore, to help ameliorate management methods in pikeperch culture, this review discussed the pikeperch adaptive or maladaptive reactions to various environmental stressors. Accordingly, this paper identified the leading and complementary indicators (effective causes) inducing stress in pikeperch during aquaculture operations and identified management errors to conserve its safety, welfare, and survival. It will prevent destructive stress consequences that lead to disease, retardation, or lack of growth and reproduction in this species. [ABSTRACT FROM AUTHOR]

Object detection adopting deep-learning has strongly promoted the development of intensive aquaculture. However, shrimp larvae, as an important aquatic organism, are more difficult to be detected than others. On the one hand, they have indeed small sizes, which will cause them to be easily ignored due to the background noise pollution. On the other hand, affected by environmental factors and the fact that shrimp larvae like to move fast as jumping, the images of shrimp larvae often appear blurry. In order to obtain better shrimp larvae detection performance, we propose an improved anchor-free method called CAGNet in this paper. Compared with YOLOX_s, three structures including backbone, neck, and head have been improved in the proposed method. Firstly, we ameliorate the backbone by adding a coordinate attention module to extract more location information and semantic information of shrimp larvae at different levels. Secondly, an adaptively spatial feature fusion module is introduced to the neck. It can adaptively integrate effective shrimp larvae features from different levels and suppress the interference of conflicting information arising from the background. Moreover, in the head, we use GIoU module instead of conventional IoU for more accurate bounding box regression. We conducted experiments by collecting shrimp larvae data from a real aquaculture farm. Compared with the general object detection methods and previous related research, CAGNet has achieved better performance in Precision, Recall, F1 Score, and AP@0.5:0.95. Hence, the proposed method can be effectively applied to shrimp larvae detection in intensive aquaculture. [ABSTRACT FROM AUTHOR]

Biotoxins and harmful algal blooms (HABs) are damaging to aquaculture operations. Occurrences lead to disrupted operations, fish kills, and significant risks to human health. The conditions leading to blooms are driven by known, but complex processes. Heuristics exist about the drivers but the nonlinearity and opaqueness of relationships make it difficult to resolve using traditional rule-based mathematical models. An alternative approach leverages machine learning to uncover the conditions that lead to the closure of farms. This paper presents a comprehensive framework that combines semi-automated machine learning with ensemble classification approaches to predict site closures. Performance is evaluated on 7 years of site closure data from a shellfish farm in Southwest Portugal, together with publicly available environmental data. The model reports an accuracy of 83% across a challenging forecasting task. The proposed framework provides a pragmatic, scalable, site-specific decision tool to help aquaculture stakeholders mitigate the impacts of HABs. [ABSTRACT FROM AUTHOR]

Among the challenges of the aquaculture sector, the present study tries to focus on the necessary modernisation and innovation of the Hungarian sector education by strategically outlining the possibility of a niche secondary-level fisheries PILOT (experimental) training. It is obvious that the "launching" of such a shortage training level is a very complex and long-term task, but in our opinion not unfeasible. To this end, we are considering the development of a multi-stage action plan, the first milestone of which will be a thorough situation survey of the aquaculture education community. The study applies a deductive approach to specific areas of education and training within the general trends in aquaculture, covering the main traces of PILOT training in fisheries as a niche discipline. Our first paper, targeted at educators, focuses on the results of a questionnaire survey of 94 educators. Our main objective was to assess the presence of aquaculture-related knowledge content and associated methodologies in the classroom and the general digital literacy of educators. Our objectives also focus on the general digital readiness of vocational trainers and on the patterns of "professional marketing" opportunities that aquaculture professionals can express. [ABSTRACT FROM AUTHOR]

Development programs have intensified support for the aquaculture sector to improve production and productivity, as well as food security and diet quality for smallholder farmers. This paper examines the impact of farmers’ participation in Common Interest Groups (CIGs) and the effects of aquaculture development support programs on the net returns and productivity of tilapia fish in Kenya. The study used household-level data of 506 members of the CIG who were randomly selected for the treatment group and benefited from Aquaculture Business Development Program (ABDP) interventions. The analysis employed an endogenous switching regression model to account for selection bias. The results reveal that membership in CIGs and receiving fish production interventions have resulted in a 32.3% increase in tilapia fish sales returns and a 6.6% increase in tilapia fish yields. Specifically, ABDP interventions are aimed at providing fish producers with ponds and cages had a significant and beneficial effect on fish yields and income returns. This finding suggests that policies with targeted interventions that support aquaculture infrastructure can play a significant role in increasing the incomes of smallholder farmers and reducing rural poverty in Kenya. [ABSTRACT FROM AUTHOR]

Underwater segmentation technology achieves effective monitoring of fish biological information through accurate identification of fish species and precise estimation of their quantities. It serves as an effective approach to enhance the informatization level of aquaculture and promote intelligent management in fisheries. However, the complex and diverse underwater environment, coupled with poor visibility, results in blurry and lower-quality underwater fish images. The current image segmentation methods, when applied to fish segmentation, exhibit low accuracy and inadequate generalization capabilities. This paper proposes an image segmentation model based on Atrous Spatial Pyramid Pooling (ASPP) to address these challenges. The model aims to improve fish feature extraction and enhance the segmentation precision of fish images in complex underwater environments, thereby enhancing the accuracy and generalization capabilities of existing fish segmentation models. First, a multiscale feature extraction module (triangular atrous spatial pyramid multifeature fusion) based on dilated convolutional spatial pyramid pooling, which enhances the extraction of high-level semantic features of images through the triangular combination of multilayer dilated convolutional pyramid pooling and the adaptive channel attention module, is proposed. Second, a spatial attention module based on strip pooling (atrous strip pooling) is proposed, which further expands the receptive field of the attention mechanism by combining different expansion rates, enhances the correlations between pixels, and effectively captures spatial information. Finally, a decoder module based on multilayer semantic feature fusion is proposed. Through the processing and fusion of medium-, low-, and high-level semantic features, the model understands image content and performs accurate pixel-level segmentation. The proposed model is evaluated using a VOC-compliant dataset created from underwater fish images and validated against public and specific underwater fish datasets. The results demonstrate the successful application of the feature extraction and feature fusion modules in underwater fish image segmentation, achieving an average Intersection over Union (MIoU) of 85.49% in segmentation tasks. Compared to conventional segmentation models, the proposed model shows significant improvements, with an average increase of 3.8% in MIoU and 2.5% in balanced F-score (F1-score). The accurate segmentation of underwater fish images and extraction of vital biological information by this model provide a solid foundation for intelligent monitoring, including fish length measurement, weight estimation, and analysis of growth and health status. Moreover, the model offers a scientific framework for decision-making in aquaculture, driving advancements in precision and intelligent management practices in the field. [ABSTRACT FROM AUTHOR]

Seaweed is seen as a promising future source of biomass, and significant efforts are taken to upscale seaweed aquaculture production in Europe. Despite regulatory frameworks for food safety, environmental safety, and occupational health and safety applicable to seaweed production, a major barrier to upscaling production is the lack of commonly accepted, uniform frameworks for safety assessment. As a consequence, efforts to deal with food safety, environmental safety, and occupational health and safety are fragmented. Based on a literature review and consultations with stakeholders, this paper introduces a generic protocol on how to approach safety of the production of seaweed. A prototype version of the generic protocol was evaluated in a practical setting in Norway. Results show that a consistent, structured approach to safety makes it possible to identify hazards and prioritize and collect data on key hazards. The protocol facilitated a sector discussion on safety, providing a shared discourse to talk about safety. It must be acknowledged that the farming and processing practices and the location of cultivation strongly influence which hazards are most relevant. The protocol succeeded in bringing focus to data collection, putting effort into the analysis of hazards considered most relevant in a practical setting. [ABSTRACT FROM AUTHOR]

In the field of fisheries, detecting the distribution of fish underwater is an important task for achieving accurate bait feeding. However, the current deep neural networks for fish detection are significantly more computationally intensive than previous methods due to their increased network depths. Additionally, drawbacks such as the difficulty of balancing accuracy and real-time performance limit the deployment of these algorithms in fishery end devices. To address this problem, this paper proposes an improved You Only Look Once version 5 (YOLOv5)-based underwater fish detection method called RC_YOLOv5. First, the Res2Net residual structure is introduced to represent multiscale features at a finer granularity and increase the perceptual field of the network while reducing the computational power of the model. Second, a coordinate attention mechanism is introduced to suppress the interference of the background and help the network locate its target more accurately. Finally, coordinate attention is embedded into the tail of Res2Net to form a residual attention structure, and this structure is used to replace the original bottleneck structure in the YOLOv5 model to improve its accuracy. Experiments show that the proposed model has good performance on a self-built fish dataset, reaching 95.7% and 95.4% precision and mean average precision (mAP), respectively. Compared with those of the original model, the precision of the proposed approach improves by 1.6%, the mAP improves by 0.6%, the number of computations is reduced by 22.2%, the model size is reduced by 23.5%, the detection rate reaches 263 frames per second (FPS) and the performance is better than that of other mainstream detection models. This method enables accurate and rapid fish detection in fisheries. [ABSTRACT FROM AUTHOR]

The constant increase in worldwide per capita consumption of fish indicates the need for reliable and viable sources of fish, and aquaculture fits these criteria. Aquaculture has continued to make a significant contribution to total fisheries production over the last few decades. The significant progress in aquaculture has been largely attributed to the intensification of production and increasing dependency on formulated food. Among the major challenges in aquaculture is aquaculture feed, or in short, aquafeed, which may represent up to 80% of total operational costs. Due to escalating prices and unsustainable resources of aquafeed ingredients, especially fish meal, fish oils, and soybean meal, many substitutes are utilised, mainly animal by-products and animal waste, which is a concern under Islamic jurisprudence. This concern is quite substantial if aquaculture producers are vying for the halal market. Hence, it is important for them to understand this aspect of Islamic law. This paper reviews the current status of aquafeed ingredients and the classical Islamic jurisprudence pertaining to this issue. References to current decrees and standards by major Muslim countries and Islamic authorities are also presented, followed by options and avenues for remediation. [ABSTRACT FROM AUTHOR]

Nowadays, the prevalence of infectious vibriosis soars due to the extensive development of marine fishery, resulting in substantial annual fish mortality. Traditionally, antibiotics have been the preferred treatment for vibriosis worldwide. However, the emergence of antibiotic resistance among Vibrios has prompted the gradual adoption of vaccine therapy. In comparison, vaccines demonstrate superior efficacy, combining efficiency, safety, and cost-effectiveness. Consequently, this paper aims to comprehensively review the current research progress concerning diverse vaccine types, including inactivated and attenuated vaccines, for the prevention and control of vibriosis, as well as offers a prospective outlook on the ongoing research and development endeavors focused on novel vaccine approaches to combat this disease. [ABSTRACT FROM AUTHOR]

Enterocytozoon hepatopenaei (EHP) is a fungal pathogen that causes hepatopancreatic microsporidiosis (HPM) in shrimp, resulting in significant economic losses for the shrimp culture industry. Although the impact of EHP on hormonal regulation in shrimp has been seldom examined, it remains a crucial area of study. In this paper, we analyzed the transcriptomic data of the hepatopancreas of EHP-infected and uninfected shrimp to explore the effect of EHP on hormonal regulation. Our results identified 157 differentially expressed genes (DEGs), of which 32 genes were upregulated and 125 were downregulated. Through gene ontology (GO) and KEGG analyses of hormone regulation-related DEGs, we identified eight genes, six of which were associated with the regulation of molting and growth, one with immunity, and one with osmotic pressure regulation. The up- and downregulated pathways were mostly related to molting and growth regulation, including EGFR tyrosine kinase inhibitor resistance, thyroid hormone signaling pathway, and steroid hormone biosynthesis. Ten genes were selected randomly for qRT-PCR, and results confirmed the findings of transcriptome sequencing. This study provides essential insights into the molecular mechanisms through which EHP affects hormonal regulation in shrimp and serves as a basis for further research to control HPM. [ABSTRACT FROM AUTHOR]

Intensification of aquaculture practices brings about disease outbreaks, resulting in high mortality among farmed species and great economic losses. In order to prevent huge economic losses, various types of antibiotics have been used for the treatment of infections. Nevertheless, frequent use of synthetic antibiotics leads to an increase in antibiotics-resistant pathogenic bacteria and aggravating water pollution. Thereby, herbal medicine appeared to be an alternative for chemotherapy replacement due to its characteristics of being eco-friendly, having a high tolerance in animals, and being less toxic to the environment. Current research on the use of phytogenic compounds to combat some pathogens that cause diseases in aquaculture raises great worldwide interest due to their capability to act as immunostimulants, antibacterials, antioxidants, anti-parasites, and anti-viruses. This review paper aimed to review the past 5 years (2019–2023) on the usage of herbal medicine in disease mitigation, their mechanisms of action, and the effectiveness of various dosages and routes of administration during application in several aquatic species. The potential toxicological effects observed during the application of medicinal plants also were discussed. [ABSTRACT FROM AUTHOR]

Lumpfish (Cyclopterus lumpus) are used as cleaner fish in salmon aquaculture to treat sea lice. However, after 18–24 months and reaching 0.4–0.6 kg, the fish is removed from the salmon cage and usually discarded, which raises social, economic, and environmental challenges, as well as ethical concerns. This paper assesses the viability of marketing lumpfish as food by exploring possible products that can be made from the fish in Vietnamese cuisine, and understanding the stakeholder's perception and acceptance of the fish. We used a customer co-creation method to investigate market potential, sending a sample of 45 kg of frozen and whole lumpfish from Norway to Vietnam. Researchers, industrial stakeholders, restaurant chefs, and household consumers collaborated to discuss, process, cook, and taste the fish, and the evaluations were assessed before and after consumption. More than 10 Vietnamese dishes were identified as possible use for lumpfish, including grilled, fried, sour soup, hotpot, and several value-added products. Household consumers and restaurant buyers evaluated the fish positively in terms of sensory quality (taste, color, flavor, size, and texture), but the rough skin and sharp thorn are negative aspects. Individual consumers accept the fish and were willing to buy it if the price is reasonable. In contrast, industrial stakeholders evaluated the lumpfish less favorably, citing its soft and mushy texture, sticky smell, and very low fillet-recovery-ratio (only 15.9% of skinless fillet and 16.7% of kama can be obtained from whole-defrosted lumpfish). They also found that the taste of the fish was not delicious and bitter in some value-added products. In addition, this study found that the information relating to lumpfish as a cleaner fish is not an issue in the Vietnamese context. [ABSTRACT FROM AUTHOR]

The increasing demand on water resources, reduced land for agriculture, and concerns over food and nutrition security have prompted the evolution of innovative and complex food production systems. In this context, efficient and sustainable food production systems such as aquaponics are viewed as an important and environmentally friendly technology for adaptation under resource-limited environments. Producing food in soilless systems is a promising strategy, as this method utilizes significantly less water than traditional agriculture. However, optimizing growing conditions to enhance crop and fish yields in aquaponics is frequently ambiguous and is often not economically feasible. One of the strategies to improve plant yields and supply of nutrients in aquaponics is the application of probiotics. With this strategy, the crop yields in aquaponics are improved via a variety of mechanisms, including nitrogen fixation, solubilization of mineral nutrients, organic matter mineralization, plant hormone modulation, and biocontrol. As a result, incorporating probiotics in aquaponic systems is a strategy for mitigating environmental effects and advancing sustainable agriculture. This review paper provides the current knowledge of the use of probiotics in aquaponics. Suggestions for further studies on the effects of probiotics in aquaponic systems are proposed. Through literature review, integrating probiotics into aquaponic systems has the potential to improve nutrient supply, modulation of water quality parameters, and microbial communities, which are key processes in enhancing the productivity of aquaponic systems. [ABSTRACT FROM AUTHOR]

Water quality and the management of nitrogenous compounds are of key importance within aquaculture. In this paper, automated and portable analysers for in situ analysis of nitrite and nitrate in water were deployed in freshwater and saline recirculating aquaculture systems (RAS). The analysers were based upon ion chromatography (IC) and employed a NaCl eluent with an anion exchange guard column for low backpressure anion separation, in combination with selective 235 nm ultra-violet light-emitting diode (UV-LED) based absorbance detection. The analysers were monitored and delivered real-time concentration data using a cellular internet of things (IoT) module and cloud-based dashboard. Overall performance and chromatographic repeatability were tested across various temperature profiles and 500 sequential runs within the laboratory. Deployments in freshwater and saline RAS, with concentrations ranging between 0.1–3.6 mg L−1 nitrite and 0.6–392 mg L−1 nitrate, were successful and the analytical performance was comparable to that of accredited lab-based instrumentation. [ABSTRACT FROM AUTHOR]

Aeromonas spp are the most common devastating fish bacterial pathogens associated with a wide range of cultured freshwater fish resulting in mass mortality. The present study plots the Aeromonas research output in fish during 1998–2020 by means of the Web of Science (WoS) database. A total of 1944 publications were used for this investigation to evaluate the scientific productivity in this selected subject area. Global publication share, rank, and its development in terms of research and bibliometric indices such as overall citations, h-index, and average citation per paper were also analysed. China ranked first in terms of total publications among the most productive countries and accounted for 26.18% of the total publications. The network visualisation map revealed that the lead collaborating country was China; however, the collaboration between countries was found to be very less. Lokta's law was noticed not to be valid for Aeromonas research. The study showed that the funding granted to the research investigations and their research productivity in terms of total publications were correlated positively. The results of the current study displayed the trend of "Aeromonas infection in fish" related research investigations published during 1998–2020. This study also highlighted the focused research areas on this topic on which the future areas of research can be determined by fellow researchers in this specific field. This study also suggests enhancing the research efforts on this bacterial pathogen which has the potential to implicate huge economic loss to the fish farming population in the world. [ABSTRACT FROM AUTHOR]

One of the major bottlenecks affecting the expansion of the freshwater aquaculture sector in developing countries is the outbreak of diseases. Fish farmers have traditionally relied on antibiotics and synthetic chemicals to control diseases. However, antibiotics and synthetic chemicals are associated with negative effects on the environment and consumers and their excessive use has resulted in antibiotic-resistant pathogens. In addition, the majority of freshwater fish farmers, especially small-scale farmers, have limited access to antibiotics and synthetic chemicals due to lack of resources. Medicinal plants have been reported to be suitable replacements in aquaculture, but their usage in aquaculture is still limited. The aim of this paper is to undertake a meta-analysis on the effect of medicinal plants on innate immune response and disease resistance in commonly farmed freshwater aquaculture fish species, namely Mozambique tilapia (Oreochromis mossambicus), African catfish (Clarias gariepinus), trout (Oncorhynchus mykiss), and cyprinids (Labeo rohita and Cyprinus carpio). The analysis showed that the mean effect size for respiratory burst (− 1.90 (95% CI − 2.40; − 1.40), I2 = 100%, P = 0); lysozyme activity (0.05 (95% CI − 0.38; 0.48), I2 = 97%, P < 0.01); white blood cells (− 0.69 (95% CI − 1.16; − 0.23), I2 = 89%, P < 0.01); and phagocytic activity (− 1.21 (95% CI − 2.08; − 0.35), I2 = 91%, P < 0.01) was significantly different. Mean effect size for survival rates was not significantly different (2.56 (95% CI 0.10; 5.01), I2 = 0%, P = 1). The funnel plots for all parameters were asymmetrical, which indicates possible publication bias or the presence of systematic differences or inconsistencies among studies. Overall, the meta-analysis showed that medicinal plants could enhance immunity and disease resistance in tilapia, African catfish, carp, and trout. These findings reinforce the observation that plant supplements can be used to prevent disease outbreaks in aquaculture. It is therefore recommended that freshwater fish farmers in African regions such as Southern Africa learn to produce their own diets supplemented with plants at their farms in order to prevent diseases in cultured fish. [ABSTRACT FROM AUTHOR]

Molluscs are among the most valuable resources of the Philippines, an archipelagic country of 7,107 islands bounded by 36,000 km of coastline and 26.6 million ha of coastal waters. In 2020, production from mussels and oysters alone valued at PhP1.552 billion. As primary sources of food and livelihood for marginalized fisherfolk, they are considered important in food security, nutrition, and poverty alleviation. Nevertheless, for almost a century, mollusc culture remained small-scale, with most fish farmers investing in non-fed species, like mussels and oysters. Moreover, mollusc culture in the country is still dependent on wild sources of seed stocks, making production unsustainable and unreliable. This dependence on the wild seed stocks will continue until the issue of the lack of commercial-scale hatcheries or the limited capacity of existing hatcheries to produce seeds, both for top and emerging mollusc aquaculture species, is resolved. Although technologies from broodstock management to post-harvest are available in some species, the lack of capital and the limited government support limit these artisanal fishers from doing large commercial-scale culture. This paper summarizes what has been done and published on the leading mollusc species cultured in the Philippines. Future research activities may be designed based on the research gaps to refine available technologies and develop new ones to improve culture production. The lack of or limited relevant information on the viable economics of the different culture techniques at different culture phases, the limited availability of post-harvest technologies, and the sparse or lack of genetic information for these leading mollusc species are among the gaps that need to be addressed. [ABSTRACT FROM AUTHOR]

Breast cancer is a leading cause of cancer-related deaths among women worldwide. Angiogenesis, the process of the formation of new blood vessels, plays a crucial role in the development and progression of breast cancer. In recent years, marine algal bio-products have garnered attention as a potential alternative to traditional chemotherapeutics for the treatment of breast cancer. Marine algae, which are itself a vast universe to explore in the marine ecology, are rich sources of bioactive compounds with diverse pharmacological activities, including that of the anti-angiogenic properties. In this review, we aim to summarize the current state of knowledge on the use of marine algal bio-products for targeting angiogenic channels in the treatment of breast cancer. In this paper, we reviewed potential use case scenarios for algal metabolites' anti-angiogenic inhibition of human breast cancers, discussed the various types of marine algal bio-products that have been studied for their anti-angiogenic effects, and discussed the mechanisms of action by which they exert these effects. We also examined the potential benefits and drawbacks of marine algal bio-products as anti-angiogenic agents, as well as the future avenues for study in this area. [ABSTRACT FROM AUTHOR]

A comparative quality assessment of fillet (meat) between organically grown and conventionally grown Indian major carps is made in this paper. The assessment was carried out by sensory evaluation, and through the determination of the proximate composition of the whole fish body, texture, taste, off-flavour, appearance and overall acceptability were rated on a Hedonic scale for sensory estimation. The whole fish (2.00 ± 0.58), appearance of skin (1.96 ± 0.54), blood on gill (2.04 ± 0.54), appearance of eyes (2.04 ± 0.54) and gills colour (2.04 ± 0.62) were the parameters used. These parameters were significantly better for catla in the conventional culture system compared to the organic culture system. There were no significant differences in crude protein, moisture and ash content of the whole fish, but a significant difference was found in fat content among the three cultured carps reared using two different culture systems (P < 0.05). During instrumental colour measurement, the highest grades in the entire computed variable were awarded to catla (L*, (48.94 ± 5), a* (1.69 ± 1.1), b* (6.85 ± 2.8)), rohu (L*, (45.22 ± 1.0), a*(1.39 ± 0.9), b* (5.88 ± 1.0)) and mrigal (L*, b (43.33 ± 0.1); a* (1.17 ± 0.7); b* (5.27 ± 0.6)) grown in organic culture system followed by conventional culture system. Therefore, the production of organic Indian major carps is one of the promising areas for the production of organic food. [ABSTRACT FROM AUTHOR]

The objective of this paper was to demonstrate that the promotion of aquaculture clusters as a policy option for developing tilapia aquaculture in Mexico, resulting from glocal externalities as competitive advantages to the global market, is necessary to further develop the sector. The farmed tilapia clusters were described using data from the Veracruz Aquaculture Census, 2010. We then utilise three theories. Firstly, we focus on North (1955) and Krugman (1995) and find that Economic geography and localisation verified that conglomeration is a function of natural resources and population zones. Secondly, we investigate the Porter value system. Cluster competitive advantage was identified in water availability and water access, electric supply coverage, product presentation, and the local market. Thirdly, we apply the Altenburg and Meyer-Stamer (1999) model to identify cluster type, which classifies typology based on natural resource access and the inputs and technologies commercial balance. The Veracruz Tilapia cluster diagnostic showed an incipient development with remarked opportunity areas, where efforts should be directed, supported by a cluster strategy. However, Mexico and the Port city of Veracruz should diversify their economy. We conclude that adopting a cluster strategy for aquaculture is necessary in Mexico to both increase global competitiveness and to supply the local market. [ABSTRACT FROM AUTHOR]

This paper compares the effect of feeding the abalone Haliotis asinina with seaweed (SW), formulated (FD), and mixed (SW+FD) diets. The feeding experiment, in six replicates, was conducted in a tank facility and lasted for 10 months. At the end of the experiment, abalone fed mixed diets had significantly the highest mean shell length and body weight (45.90±0.19 mm, 22.82±0.31 g), followed by those fed seaweeds (43.47±0.17 mm, 18.25±0.26 g), and lastly, by those fed formulated diets (41.78±0.18 mm, 15.76±0.22 g). Mean growth rates were significantly higher in abalone fed mixed diets at 1.48±0.03 mm and 1.69±0.04 g mo−1 than those fed seaweeds (1.26±0.03 mm, 1.27±0.06 g mo−1) or formulated diet (1.06±0.09 mm, 1.00±0.11 g mo−1). Survival was consistent 1 month from the start of culture until harvest—highest in abalone fed mixed diets (78.81±2.48%), followed by those fed seaweeds (70.12±4.07%), and lastly formulated diet (64.53±4.61%). Moreover, feed conversion ratios (FCR) were significantly lower in abalone fed mixed diets (15.48±0.69) and formulated diet (18.07±3.50) compared with those fed seaweeds (41.31±2.36). The body weight to shell length ratios (BW:SL), which were the same in all treatments at the start of the experiment (0.19 g mm−1), increased to 0.51, 0.44, and 0.38 in abalone fed mixed diets, seaweeds, and formulated diet, respectively. Based on the results of this experiment, giving abalone a mix of formulated and natural diets is the best feeding regime. The importance of a balanced and more nutritional diet on the well-being of the abalone was observed in this study. [ABSTRACT FROM AUTHOR]

The collection of farmed fish samples and subsequent diagnosis of microbial pathogens can be difficult and time-consuming procedure under field conditions. Correct diagnosis and identification of bacterial diseases agents (Yersinia ruckeri, Flavobacterium psychrophilum, Lactococcus garvieae, and Vagococcus salmoninarum) are crucial for the effective treatment. In this study, the feasibility of using FTA® card (Flinders Technology Associates filter papers) for sampling infected rainbow trout (Oncorhynchus mykiss) tissues and significantly accelerated the molecular diagnosis of enteric redmouth disease, rainbow trout fry syndrome, bacterial coldwater disease, lactococcosis associated with fatal hemorrhagic septicemia, and vagococcosis were evaluated. We also examined and compared a practical and reliable extraction obtained from immobilized DNA on FTA® card with one commonly used commercial kit to diagnose bacterial pathogens in fish tissues. Results proved that the active working time of extracting DNA from FTA® card is requiring only 30 min and the cost is less than USA $ 0.5 for each eluted sample. A total of hundred extracted DNA from tissues on FTA® card were tested and showed successful PCR amplification of the aroA, murG, pLG, and pSa1 genes. In conclusion, our finding indicates FTA® card as an appropriate tool for the simple collection, easy transfer, and stored at room temperature without contamination and retrieval of high-quality DNA for rapid molecular diagnosis of bacterial fish pathogens without isolation and culture. [ABSTRACT FROM AUTHOR]