Aquacultural Engineering最新文献

{"title":"Development and multi-objective optimization of a solar-powered hybrid aerator for aquaculture","authors":"Zhi Qu ,&nbsp;Changfeng Tian ,&nbsp;Xuan Che ,&nbsp;Mengxia Han ,&nbsp;Yin Zhou","doi":"10.1016/j.aquaeng.2025.102608","DOIUrl":"10.1016/j.aquaeng.2025.102608","url":null,"abstract":"<div><div>Aerator is a crucial equipment in aquaculture production that accounts for over 60 % of equipment energy consumption. So far, two major challenges - high energy consumption and low oxygen mass transfer efficiency, still have not been resolved. To address these issues, this study designed a hybrid energy-saving aerator integrating solar power and conventional power supply. A multi-objective optimization algorithm was employed to analyze the influence of parameters such as aerator rotational speed and impeller submergence depth on dissolved oxygen (DO), diffusion efficiency and energy consumption. In this manner, the optimal combination of rotational speed and impeller submergence depth can be determined. Experimental results showed that under the optimal operating conditions (rotational speed of 90 rpm, impeller submergence of 0.10 m), the standard oxygen transfer rate (SOTR) reached 1.17 kg/h, with the standard aeration efficiency (SAE) of 1.74 kg/(kWh), representing a 32 % improvement compared to the YC-0.75 two-blade waterwheel aerator. Spatial DO distribution analysis indicated that the average DO concentration in the core area (0–10 m) was 8.96 mg/L, and it remained at 6.81 mg/L at 20 m, both meeting the aquaculture safety threshold of 5 mg/L. The hybrid power supply system prioritized solar energy utilization, achieving a daily power saving of 2.87 kWh, annual savings of 1047.55 kWh, and an energy-saving rate of 35.6 %. These findings provide theoretical support for the intelligent and low-carbon development of aquaculture equipment.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102608"},"PeriodicalIF":4.3,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810652","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":"Osedax-GAN: A novel metaheuristic approach for missing pixel imputation imagery for enhanced detection accuracy of freshwater fish diseases in aquaculture","authors":"Mostafa Elbaz ,&nbsp;Sadeq K. Alhag ,&nbsp;Laila A. Al-Shuraym ,&nbsp;Farahat S. Moghanm ,&nbsp;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 &gt; 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 &lt; 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":"2025-08-05","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":"LightHybridNet-Transformer-FFIA: A hybrid Transformer based deep learning model for enhanced fish feeding intensity classification","authors":"Usama Iqbal ,&nbsp;Daoliang Li ,&nbsp;Muhammad Farrukh Qureshi ,&nbsp;Zohaib Mushtaq ,&nbsp;Hafiz Abbad ur Rehman","doi":"10.1016/j.aquaeng.2025.102604","DOIUrl":"10.1016/j.aquaeng.2025.102604","url":null,"abstract":"<div><div>Accurate assessment of fish feeding intensity is important for efficient and sustainable aquaculture. This paper introduces LightHybridNet-Transformer-FFIA, a novel and parameter-efficient hybrid neural network for automated fish feeding intensity classification in aquaculture. Addressing the critical need for optimized feed management, our model utilizes the fusion of sonar imagery and Mel spectrograms to accurately assess feeding intensity levels. LightHybridNet-Transformer-FFIA integrates a Convolutional Neural Network branch for spatial feature extraction from sonar images with a Transformer branch for capturing temporal dynamics in Mel spectrograms, fused by a Feature Fusion and Interaction Aggregation (FFIA) module. Evaluated on the MRS-FFIA dataset, our model achieves a high validation accuracy of 95.42% and a macro-averaged F1-score of 95.40%, demonstrating competitive performance against state-of-the-art multi-modal models while utilizing a significantly smaller parameter footprint (0.102 million parameters). The architectural novelty and parameter efficiency of LightHybridNet-Transformer-FFIA present a promising solution for real-time aquaculture monitoring, enabling optimized feed delivery, reduced waste, and improved sustainability. This work highlights the effectiveness of hybrid CNN-Transformer architectures for multi-modal underwater sensing and contributes a practically deployable model for intelligent aquaculture management.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102604"},"PeriodicalIF":4.3,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829632","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 budgeting and economic analysis of shrimp (Penaeus vannamei) production under different culture techniques in Tamil Nadu, India","authors":"S. Ayesha Jasmin ,&nbsp;Mohammad Tanveer ,&nbsp;Pradeep Ramesh","doi":"10.1016/j.aquaeng.2025.102605","DOIUrl":"10.1016/j.aquaeng.2025.102605","url":null,"abstract":"<div><div>This study evaluates energy usage and economic performance in shrimp farms using conventional, biofloc, and semi-biofloc culture techniques across Tamil Nadu, India. Data were collected from 37 farms and classified into nine culture systems based on culture techniques and stocking density. Energy input ranged from 918,734.30 MJ/ha to 6,961,172.45 MJ/ha, while output energy varied from 19,463.50 MJ/ha to 340,456.48 MJ/ha, with the highest values in biofloc super-intensive systems. Results reveal that energy consumption increases with stocking intensity, particularly in biofloc systems, due to continuous aeration and higher feed input. Electricity was identified as the major input energy source, followed by chemicals, fertilizers, and fuel. Semi-biofloc culture systems showed higher energy efficiency compared to conventional methods, while super-intensive biofloc culture systems exhibited higher productivity with lower relative energy inputs performing well in terms of both energy and economic aspects. Semi-intensive systems in semi-biofloc culture were identified as the most energy-efficient and sustainable, balancing economic returns with lower environmental impacts. Therefore, conducting energy budgeting to identify high energy consumption areas and adopting energy-efficient practices, in conjunction with harnessing renewable energy sources, can substantially enhance sustainable productivity in shrimp production systems.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102605"},"PeriodicalIF":4.3,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766522","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":"2025-07-22","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":"Optimizing rapid biofloc establishment: Effects of inoculum biofloc concentration and feed addition on maturation time, water quality, and nutritional composition","authors":"Xin Hu ,&nbsp;Xingxue Ren ,&nbsp;Baojie Fan ,&nbsp;Gaopeng Wu ,&nbsp;Hongxin Tan ,&nbsp;Wenchang Liu ,&nbsp;Guozhi Luo","doi":"10.1016/j.aquaeng.2025.102602","DOIUrl":"10.1016/j.aquaeng.2025.102602","url":null,"abstract":"<div><div>Despite growing interest in biofloc technology, methods for rapid biofloc system establishment remain unclear. While mature biofloc inoculation can accelerate system maturation, the critical parameters of inoculation biofloc total suspended solids (TSS) and feed addition amount remain underexplored. This study addressed this gap through two trials. Trial Ⅰ tested initial biofloc TSS levels (100, 200, and 300 mg/L). While the 300 mg/L treatment accelerated biofloc maturation, statistical analysis revealed no significant differences (<em>p</em> &gt; 0.05) in TSS production, total ammonia nitrogen (TAN) removal efficiency, or nutritional profiles (crude protein/fatty acid content) between the 200 and 300 mg/L treatments. Consequently, 200 mg/L TSS was identified as the optimal inoculum concentration. Trial II evaluated feed addition amount (0.5–5.0 g/L) using the 200 mg/L biofloc inoculum. Results showed that higher feed addition amount significantly prolonged maturation time (<em>p</em> &lt; 0.05). While the 0.5 and 2.0 g/L groups had comparable nutritional quality, the 2.0 g/L group exhibited superior TAN removal rate and significantly lower peak nitrite concentration (<em>p</em> &lt; 0.05). These results demonstrate that 2.0 g/L feed supplementation balances nutritional value with enhanced water treatment capacity. Our results indicate that an inoculated biofloc TSS of 200 mg/L combined with a feed addition of 2.0 g/L is an appropriate biofloc expansion strategy. This study optimizes the accelerated cultivation process of biofloc, offering valuable insights to facilitate its large-scale implementation.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102602"},"PeriodicalIF":3.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694408","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":"Big multi-step motion and mooring load forecasting of fish cage using a novel hybrid model based on Bi-SLSTM neural network","authors":"Can Yang ,&nbsp;An Hu ,&nbsp;Daqing Wu ,&nbsp;Xiaodong Bai ,&nbsp;Lars Johanning","doi":"10.1016/j.aquaeng.2025.102601","DOIUrl":"10.1016/j.aquaeng.2025.102601","url":null,"abstract":"<div><div>Accurate forecasting of motion and mooring loads in fish cages is vital for efficient field monitoring and numerical simulations. This research introduces an innovative hybrid model that leverages Bidirectional Stateful Long Short-Term Memory (Bi-SLSTM) neural networks to predict the dynamic behavior of fish cages. By incorporating bidirectional data flow and state-preserving mechanisms, the model enhances the accuracy of multi-step predictions. Performance is assessed through the Root Mean Square Error (RMSE) and the Trapezoidal-based Integral Similarity Index (<em>R</em>_{<em>trapz</em>}). Results show that Bi-SLSTM outperforms Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional Long Short-Term Memory (BiLSTM) models, achieving <em>R</em>_{<em>trapz</em>} values above 0.85 in large multi-step predictions. Further analysis reveals that combining wave and motion data as inputs improves prediction accuracy, with surge and heave predictions reaching 91 % and 98 %, respectively. The hybrid strategy combining motion response and load data provides the best performance for mooring load prediction, with <em>R</em>_{<em>trapz</em>} values exceeding 0.85 across different output steps. The Bi-SLSTM model demonstrates strong prediction capability and robustness in forecasting cage dynamics.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102601"},"PeriodicalIF":3.6,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655947","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":"Estimation of total suspended solids by settleable solids and turbidity, using coagulants and flocculants as settlers","authors":"Magna Santos ,&nbsp;Julio Cesar Zemor ,&nbsp;Ivanilson Santos ,&nbsp;Wilson Wasielesky","doi":"10.1016/j.aquaeng.2025.102600","DOIUrl":"10.1016/j.aquaeng.2025.102600","url":null,"abstract":"<div><div>Accurate measurement of solids in different biofloc systems is essential for production optimization. Thus, this study aimed to optimize methodologies for measuring settleable solids in the culture media of <em>Penaeus vannamei</em> with photoautotrophic, heterotrophic, and chemoautotrophic predominance by applying different doses of chemical products to force the sedimentation of solids in the Imhoff cone to perform correlation and regression analyses with total suspended solids and turbidity. This study also evaluated water quality parameters, microbial community composition, proximal composition, and shrimp growth performance. The evaluated products were aluminum polychloride (100 %), copper sulfate (19.5 %), and aluminum sulfate (100 %), commonly used in water and effluent treatment. The 70-day experiment was conducted with <em>P. vannamei</em> at a density of 500 shrimp. m⁻³. Aluminum sulfate and aluminum polychloride were the most effective in optimizing the compaction and sedimentation of solids, particularly in the predominantly photoautotrophic and heterotrophic media. Equations were proposed to estimate total suspended solids by settleable solids and turbidity values. Considering the strength of correlation and the lower standard error of estimation, producers are advised to estimate total suspended solids concentrations not only by settleable solids values but also by turbidity, because this is a quick and practical unit of measurement to analyze throughout the shrimp production cycle. The findings provide a fast-reading and predictive method to support decision-making in biofloc systems management.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102600"},"PeriodicalIF":3.6,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605595","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":"2025-07-08","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":"Aquaponics performance optimization: The impact of hydraulic loading rate on striped murrel (Channa striata) and lettuce (Lactuca sativa L.) production in a vermicompost-supplemented system","authors":"Venisza Cathy John ,&nbsp;Ajit Kumar Verma ,&nbsp;Murtaza Hasan ,&nbsp;Hare Krishna ,&nbsp;Prativa Sahu ,&nbsp;Kishore Kumar Krishnani ,&nbsp;Sukham Munilkumar ,&nbsp;Prem Kumar ,&nbsp;Tincy Varghese ,&nbsp;Chandrakant Mallikarjun Hittinahalli","doi":"10.1016/j.aquaeng.2025.102598","DOIUrl":"10.1016/j.aquaeng.2025.102598","url":null,"abstract":"<div><div>The rising global food crisis calls for adopting circular economy concepts like aquaponics for effective nutrient and resource reuse for sustainable development. The study for 90 days aimed at optimizing the performance of striped murrel (<em>Channa striata</em>)-lettuce aquaponics for different hydraulic loading rates (HLR) of 2, 4, 6, 8 and 10 m/day with vermicompost extract supplementation at 27.5 mg/L in all treatments. The increase in HLR exhibited a positive linear relation between water quality and fish growth. A parallel growth of fish and plant was recorded at 4 m/day (66.81 ± 1.59 g and 1481.56 ± 46.30 g) and 6 m/day (65.80 ± 1.80 g and 1455.91 ± 30.94 g), respectively, while at higher HLR a linear decline was observed. The study revealed that the interaction between the physico-chemical characteristics of culture water was influenced by HLR, with significant reduction in total ammonia nitrogen (TAN) and nitrite at increased HLR, while nitrate, phosphate and iron exhibited a reverse trend which increased with higher HLR. The serum glucose, cortisol, alanine transaminase (ALT), aspartate transaminase (AST) and superoxide dismutase (SOD) in liver of fish were significantly higher at 2 m/day. The results displayed that all tested HLRs were effective, while HLR of 4 and 6 m/day improved water quality, mineral content of lettuce and production of striped murrel- lettuce aquaponics. The separate quadratic regression model fitted for different HLR with fish and plant production was 5.4 and 5.9 m/day, respectively. Hence, a HLR of 5.6 m/day with vermicompost supplement was recommended as the best compromise for optimal performance of striped murrel-lettuce aquaponics.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"111 ","pages":"Article 102598"},"PeriodicalIF":3.6,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596036","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}