Aquacultural Engineering最新文献

{"title":"Osedax-GAN: A novel metaheuristic approach for missing pixel imputation imagery for enhanced detection accuracy of freshwater fish diseases in aquaculture","authors":"Mostafa Elbaz , Sadeq K. Alhag , Laila A. Al-Shuraym , Farahat S. Moghanm , Hanaa Salem Marie","doi":"10.1016/j.aquaeng.2025.102606","DOIUrl":"10.1016/j.aquaeng.2025.102606","url":null,"abstract":"<div><div>This paper introduces Osedax-GAN, a novel framework that combines the newly introduced Osedax metaheuristic algorithm as a loss function with Generative Adversarial Networks (GANs) to address the critical challenge of missing pixel imputation in underwater imagery for freshwater fish disease detection. The research addresses a fundamental problem in sustainable aquaculture: while laboratory-based computer vision systems achieve > 95 % accuracy on high-quality images, performance degrades to 65–75 % when applied to corrupted underwater imagery characteristic of commercial environments, precisely when automated monitoring becomes most valuable. Our investigation introduces four key innovations: (1) First application of deep-sea Osedax worm foraging behavior as a biologically-inspired metaheuristic for GAN optimization, providing superior global search capabilities specifically adapted for underwater imaging challenges; (2) Novel identity block architecture that preserves critical pathological markers during restoration, ensuring disease-specific features remain detectable even with substantial image corruption; (3) Adaptive 8-connected neighborhood strategy that dynamically adjusts to variable underwater conditions including turbidity, lighting variations, and refraction effects; (4) Pathological feature loss function specifically engineered for aquaculture disease detection that enables unprecedented preservation of diagnostic markers. Comprehensive experiments demonstrate that Osedax-GAN significantly outperforms nine state-of-the-art GAN approaches across all evaluation metrics, achieving superior restoration quality (29.86 dB PSNR, 0.918 SSIM), enhanced classification performance (92.7 % accuracy, 91.7 % F1-score), and most critically, remarkable early disease detection capability (83.9 % accuracy) that enables pathogen identification 1.6 days earlier than existing methods—expanding the critical intervention window when treatment success rates exceed 85 %. The framework demonstrates exceptional computational efficiency (34.5 ms inference time, 19.7 h training) with 10.9 % faster processing and 9.9 % lower power consumption compared to the strongest baseline, making it the first practical solution for real-time disease monitoring in commercial aquaculture facilities. Statistical validation confirms significance across all metrics (p < 0.05) with large effect sizes (Cohen's d ranging from 0.74 to 2.13), while cross-validation demonstrates robust generalization across diverse underwater conditions and disease categories. The significance of this research extends beyond immediate aquaculture applications: by enabling earlier disease detection and intervention, this work directly contributes to global food security through reduced mortality rates (potentially preventing billions in annual losses), decreased antibiotic usage supporting sustainable farming practices, and democratization of advanced monitoring technology for resource-co","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102606"},"PeriodicalIF":4.3,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid H2S production in layers of freshwater and marine fish organic waste from recirculating aquaculture systems","authors":"Alexandre M. Nguyen-tiêt,&nbsp;Carlos O. Letelier-Gordo,&nbsp;Sanni L. Aalto","doi":"10.1016/j.aquaeng.2025.102578","DOIUrl":"10.1016/j.aquaeng.2025.102578","url":null,"abstract":"<div><div>Hydrogen sulfide (H₂S) is an extremely toxic gas that has been associated with fish mass mortality events in recirculating aquaculture systems (RAS), resulting in substantial economic losses for the aquaculture industry. Previous studies have identified favorable conditions and potential hotspots for H₂S production in RAS under mixed reactors conditions, but knowledge on temporal and spatial dynamics of H₂S production within layers of accumulated organic matter within these systems remains limited. In this study, we investigated H₂S production dynamics at fine spatial (millimeter) and temporal (hourly) scales in accumulated marine and freshwater organic waste collected from RAS, using a high-resolution microsensor setup. In addition to measuring the natural H₂S production potential, we examined the response to the addition of readily available carbon sources and sulfur-rich amino acid cysteine, as well as the microbial communities present in organic waste. In both freshwater and marine organic waste, H₂S appeared only within one centimeter of the accumulated fish organic waste after oxygen was consumed. When this organic waste was disturbed, the accumulated H₂S was rapidly released into the water column and reached concentrations above the toxicity threshold for fish. Through a combination of carbon and cysteine supplementation and 16S rRNA gene analysis, we identified cysteine degradation and sulfate reduction as key microbial pathways for H₂S production in the accumulated organic waste. Overall, this study demonstrates that hydrogen sulfide can form within very thin layers of accumulated fish organic waste in both freshwater and saltwater environments and once released, can reach toxic levels for fish. Therefore, it is crucial to focus on minimizing organic matter accumulation in RAS and implementing contingency measures when the bottom of tanks is disturbed.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102578"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy optimization in large-scale recirculating aquaculture systems: Implementation and performance analysis of a hybrid deep learning approach","authors":"Ashwaq M. Alnemari ,&nbsp;Wael M. Elmessery ,&nbsp;Farahat S. Moghanm ,&nbsp;Víctor Espinosa ,&nbsp;Mahmoud Y. Shams ,&nbsp;Abdallah Elshawadfy Elwakeel ,&nbsp;Omar Saeed ,&nbsp;Mohamed Hamdy Eid ,&nbsp;Sadeq K. Alhag ,&nbsp;Laila A. Al-Shuraym ,&nbsp;Lamya Ahmed Alkeridis ,&nbsp;A.E. El-Namas","doi":"10.1016/j.aquaeng.2025.102561","DOIUrl":"10.1016/j.aquaeng.2025.102561","url":null,"abstract":"<div><div>Recirculating Aquaculture Systems (RAS) represent an increasingly important solution for sustainable fish production, yet their high energy consumption remains a significant operational challenge. This study extends our previous work on using Deep Deterministic Policy Gradient (DDPG) for optimizing feeding rates in Recirculating Aquaculture Systems (RAS) by developing a hybrid Long Short-Term Memory (LSTM)-DDPG approach for energy optimization in a large-scale commercial RAS facility. The system, comprising 108 tanks with a total water volume of 3132 m³ , was monitored over a complete annual cycle, collecting 8760 hourly observations of environmental, biological, and operational parameters. The hybrid model achieved high predictive accuracy for energy consumption patterns, with R² values exceeding 0.91 for key components. Implementation resulted in a 15–20 % reduction in daily energy consumption while maintaining optimal water quality. Economic analysis revealed a 17 % decrease in energy costs per kilogram of fish production. The system's performance was validated under varying fish biomass densities (80–120 kg/m³) and seasonal temperature profiles. These findings demonstrate the effectiveness of integrating deep learning techniques for energy optimization in RAS, offering a scalable solution for enhancing the economic and environmental sustainability of intensive aquaculture operations.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102561"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microalgae plant site selection analysis: A multi-criteria decision model based on hierarchical analysis, geographic information systems and Monte Carlo simulations","authors":"Shuai Guo ,&nbsp;Feng Pan ,&nbsp;Jun Wang ,&nbsp;Feng Li ,&nbsp;Hongwei Ke ,&nbsp;Chunhui Wang ,&nbsp;Minggang Cai","doi":"10.1016/j.aquaeng.2025.102599","DOIUrl":"10.1016/j.aquaeng.2025.102599","url":null,"abstract":"<div><div>This study develops an integrated Analytic Hierarchy Process-Geographic Information System-Monte Carlo simulation (AHP-GIS-MCS) framework to address the critical yet underexplored challenge of province-level strategic siting for microalgae cultivation plants in China. The methodology synergizes: (1) AHP to establish criteria priorities (Sunshine weighting 0.458), (2) GIS for geographic constraint mapping, and (3) MCS (10,000 trials, ±20 %-40 % perturbations) for uncertainty quantification. Kunming, Yunnan Province, emerged as the optimal location (100 % stability under perturbations) due to exceptional annual effective sunlight duration (2 345.0 h), favorable temperature, and competitive industrial costs, with Urumqi and Hohhot as socioeconomic-contingent alternatives. This work establishes a scalable decision-support paradigm for bioenergy planning while bridging theoretical gaps in algal plant siting methodologies. Future extensions should prioritize fuzzy-AHP implementation, dynamic policy module integration, and municipal-level downscaling to enhance operational utility.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102599"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precise feeding technology for outdoor pond aquaculture based on detection and counting method","authors":"Zhongpei Wang ,&nbsp;Rong Qian ,&nbsp;Haoran Deng ,&nbsp;Lele Zhou ,&nbsp;Jun Ling","doi":"10.1016/j.aquaeng.2025.102588","DOIUrl":"10.1016/j.aquaeng.2025.102588","url":null,"abstract":"<div><div>In aquaculture, both overfeeding and underfeeding pose significant challenges. Underfeeding impedes fish growth, while overfeeding leads to feed waste, increased costs, and water pollution, ultimately compromising fish health. Precise feeding strategies are thus critical for sustainable aquaculture. Existing feeding technologies are primarily limited to indoor environments and specific fish species. Our study aims to extend the research scope to outdoor natural environments, applicable across diverse fish species. We start from the basic biological characteristics of fish, that is, fish will feed when they are hungry, to evaluate fish feeding behavior. We use object detection and counting technology to measure fish appetite by dynamic changes in feeding fish populations. The feeding strategy proposed is more refined and can continuously reflect the changes in the feeding intensity of the fish school. Considering the real-time needs of the application scenario, we select the YOLOv8 object detection algorithm as the basic algorithm. In view of the complexity of natural scenes—where targets are often small and feature-poor—we enhance the YOLOv8 algorithm with a Star operation, CAA module, and DyHead mechanism. The resulting YOLOv8-FishDetect model achieves significant performance gains, improving precision by 3.30 %, [email protected] by 2.51 %, and [email protected]–0.95 by 4.28 % over baseline YOLOv8. This work can provide a scalable solution for outdoor precision feeding, advancing sustainable aquaculture practices.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102588"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating submerged and surface feeding strategies in farmed Atlantic Cod: Energetic and production perspectives","authors":"Peygham Ghaffari ,&nbsp;Thor Magne Jonassen ,&nbsp;Johannes Kvam ,&nbsp;Fredrik Staven ,&nbsp;Trond M. Kortner ,&nbsp;Guro Løkka ,&nbsp;Julianne Jacobsen","doi":"10.1016/j.aquaeng.2025.102613","DOIUrl":"10.1016/j.aquaeng.2025.102613","url":null,"abstract":"<div><div>This study investigated the influence of submerged versus surface feeding strategies on behavior and growth performance in farmed Atlantic Cod (<em>Gadus morhua</em>) in a full-scale, surface-based open cage system in northern Norway. Cod receiving submerged feed consistently occupied deeper and more stable vertical positions than surface-fed fish, particularly under elevated surface temperatures (<span><math><mrow><mo>&gt;</mo><mn>15</mn><mspace></mspace><mo>°</mo><mtext>C</mtext></mrow></math></span>). While both groups exhibited diurnal vertical migrations, submerged-fed Cod displayed tighter vertical cohesion and reduced surface avoidance. The SGR was slightly higher in the submerged-fed group (<span><math><mrow><mn>0</mn><mo>.</mo><mn>39</mn><mtext>%</mtext><mspace></mspace><msup><mrow><mtext>day</mtext></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> vs. <span><math><mrow><mn>0</mn><mo>.</mo><mn>35</mn><mtext>%</mtext><mspace></mspace><msup><mrow><mtext>day</mtext></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span>), likely reflecting reduced thermal stress and better alignment with the species’ natural foraging depth. However, FCR was marginally poorer (1.23 vs. 1.20), possibly due to increased feeding competition caused by localized feed delivery. In contrast, surface feeding provided more uniform feed dispersion, resulting in lower competition and more efficient feed utilization. Mortality rates were comparable between treatments (24.2% submerged vs. 23.4% surface), with peaks observed during a warm-water starvation phase. Principal component analysis identified feed availability as the primary driver of behavioral dynamics, followed by temperature and biomass. Submerged feeding also promoted greater behavioral synchrony and depth targeting under thermally stratified conditions. These findings highlight a trade-off between growth potential and feed efficiency, shaped by the spatial and competitive dynamics of feeding depth. They underline the importance of species- and site-specific feeding strategies, particularly in environments subject to thermal stress. The results can inform the optimization of feeding depth, scheduling, net pen configuration, and feeder design and placement. Furthermore, they support the development of behavior-informed, adaptive management tools aimed at improving production efficiency and fish welfare in Cod aquaculture.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102613"},"PeriodicalIF":4.3,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PUFFER-DETR: Tiger puffer similar abnormal behavior recognition based on transformer","authors":"Yixi Zhang ,&nbsp;Zeyuan Hu ,&nbsp;Jihang Liu ,&nbsp;Yinjia Li ,&nbsp;Jianjian Lin ,&nbsp;Yue Wang ,&nbsp;Hong Yu","doi":"10.1016/j.aquaeng.2025.102552","DOIUrl":"10.1016/j.aquaeng.2025.102552","url":null,"abstract":"<div><div>Fish behavior monitoring is crucial for fish farmers to obtain growth information, improve aquatic product quality, and adjust aquaculture strategies. However, the small size, severe occlusion, and similar behavior of fish pose challenges for identifying abnormal behavior. Therefore, this study proposes an abnormal behavior detection method based on PUFFER-DETR. Using the TripletAttention backbone network, the ability of the model to extract features of fish swarm behavior and individual fish behavior in turbid water has been improved. Furthermore, weight calculation is performed on the similar behavioral characteristics between individual fish and the behavioral characteristics of the fish groups to obtain a relationship feature map of similar behavior. Cross-scale feature fusion is performed using SHS-FPN, and the similarity behavior features of individual fish are adjusted to avoid the loss of similarity behavior features during the feature fusion process. Experimental results indicate that PUFFER-DETR achieved the best fusion accuracy at a speed of 127.9 frames per second, with an average accuracy of 92.8 %. This method can accurately detect abnormal behavior of fish and assist aquaculture personnel in judging the growth status of fish. Source code is available at <span><span>https://github.com/DLOU-FishBehavior/PUFFER-DETR</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102552"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Typical farming behaviors recognition in aquaculture using an improved VMamba approach","authors":"Chenglin Sun ,&nbsp;Xinting Yang ,&nbsp;Chenjian Liu ,&nbsp;Yuming Ye ,&nbsp;Shantan Li ,&nbsp;Xudong Xu ,&nbsp;Chao Zhou","doi":"10.1016/j.aquaeng.2025.102603","DOIUrl":"10.1016/j.aquaeng.2025.102603","url":null,"abstract":"<div><div>Accurate and real-time recognition of typical aquaculture farming behaviors, such as “Inspection”, “ApplyMedication”, and “Dead fish retrieval”, is essential for the development of intelligent aquatic product traceability systems. Existing manual recording methods are inefficient and lack reliability. To address this issue, a farming behavior recognition model FBR-Mamba (Farming Behavior Recognition Mamba) is proposed based on an improved VMamba, which can automatic identification of 3 representative behaviors from surveillance video. A motion feature extraction module, ME-Former, is introduced by integrating the STMEM and CGFormer to generate motion feature maps. Additionally, the IDConv module is incorporated into the original VMamba, allowing large-kernel convolution while preserving computational efficiency and parameter economy. An EMA module is further employed to enhance the extraction of informative motion features, improving recognition accuracy. Experimental results demonstrate that the proposed FBR-Mamba achieves a Top-1 accuracy of 97.28 %, representing a 2.53 % improvement over the baseline VMamba model. The proposed approach provides an effective solution for automatic behavior monitoring in aquaculture, contributing to intelligent traceability and farming management.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102603"},"PeriodicalIF":4.3,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioral response of farmed Cod to environmental drivers and interaction with feeding practice","authors":"Peygham Ghaffari ,&nbsp;Thor Magne Jonassen ,&nbsp;Johannes Kvam ,&nbsp;Fredrik Staven","doi":"10.1016/j.aquaeng.2025.102560","DOIUrl":"10.1016/j.aquaeng.2025.102560","url":null,"abstract":"<div><div>This study investigated how environmental drivers and feeding practices influence the vertical behavior of farmed Atlantic Cod (<em>Gadus morhua</em>) in a commercial sea cage environment. A 70-day continuous observation was conducted at a farm in northern Norway, utilizing a dual-echosounder setup combined with temperature loggers and model-derived environmental data, including current velocity, salinity, and oxygen profiles. Cod behavior was compared between submerged (5 m) and surface feeding regimes across four sea cages. Fish consistently avoided surface layers above 15^∘C, aggregating at cooler depths, and shifted upward as thermal stratification weakened into autumn. Submerged feeding supported tighter aggregation, stronger rhythmicity, and vertical cohesion, while surface feeding induced anticipatory surfacing, behavioral fragmentation, and increased thermal exposure. These patterns were amplified by Cod’s physoclistic physiology and anatomical predispositions to strain from repeated vertical movement. Signal processing of depth-use patterns revealed stronger behavioral synchronization under submerged feeding, particularly aligned with the 48-hour feeding cycle. Aggregation dynamics were more closely aligned with residual current patterns and deeper water mass structure than with tidal forcing, and air temperature emerged as a reliable and practical proxy for estimating the vertical center of biomass. This study provides critical insight into farmed Cod’s depth preferences and environmental rhythms, which may be essential for enhancing fish welfare, reducing mortality, and improving the sustainability of Cod aquaculture.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102560"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated multi-trophic culture of Penaeus vannamei with Crassostrea sp. and Gracilaria sp. in a nursery system","authors":"Priscilla Celes Maciel de Lima ,&nbsp;Elizabeth Pereira dos Santos ,&nbsp;Danielli Matias de Macedo Dantas ,&nbsp;Luis Otavio Brito ,&nbsp;Alfredo Olivera Gálvez","doi":"10.1016/j.aquaeng.2025.102595","DOIUrl":"10.1016/j.aquaeng.2025.102595","url":null,"abstract":"<div><div>Currently, aquaculture seeks to implement production techniques with better use of nutrients that increase biosecurity and productivity. Therefore, the use of Brazilian native oyster <em>Crassostrea</em> sp. and red seaweed <em>Gracilaria</em> sp. in integrated multi-trophic culture (IMTA) with Pacific white shrimp <em>Penaeus vannamei</em> was evaluated for 40 days in synbiotic nursery system. Four treatments were evaluated: a shrimp monoculture (control without oysters and seaweed in static intensive system), Multi-SOS (culture of shrimp, oyster juveniles and seaweed), Multi-SO (shrimp and oyster culture), and Multi-SS (shrimp and seaweed culture). For water quality, Multi-SOS and Multi-SS treatments presented the lowest values of nitrogenous compounds (TAN, nitrite-N and nitrate-N), while Multi-SO and Multi-SOS presented lower results regarding settleable solids (respectively, 2.84 mL L⁻¹ and 2.02 mL L⁻¹) than other treatments. At the end, the shrimp performance was significantly higher in the Multi-SOS (0.80 g of final weight and 2.02 kg m⁻³ of yield) and Multi-SS (0.85 g of final weight and 2.09 kg m⁻³ of yield) treatments compared to the control. The proximate composition showed flocs with lower crude protein and lipid content and a greater amount of ash in Multi-SOS and Multi-SO compared to the other treatments (control and Multi-SS). Therefore, integrated multi-trophic culture with oysters and seaweed is recommended, as oysters could control settleable solids, and seaweed, in addition to providing a supplementary source of food for shrimp, also reduced toxic nitrogenous compounds.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102595"},"PeriodicalIF":3.6,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}