Pub Date : 2025-12-03DOI: 10.1016/j.aquaeng.2025.102676
Michael J. Salini , Rehan Mohammed , Kristy DiGiacomo , Jayde Kirkham , David S. Francis , Chethana Minoli Tissera , Aaron Spence
Knowledge of fish proximate composition is vital for farmers and researchers to make proactive management decisions and informed research interpretations. Currently, this is a cumbersome process requiring destructive sampling and specialised laboratory methods. This study strengthens the decision-making process for farmers and researchers by evaluating a rapid method for understanding fish proximate composition. We hypothesise that dual-energy X-ray absorptiometry (DXA) technology, designed and intended for human and livestock subjects, may also prove applicable for aquatic life. If proven, it enables a rapid, non-invasive and harmless method for analysing fish proximate composition and prediction of overall condition. In this study, we compare a DXA protocol with gold-standard “comparative slaughter techniques” (CST) of laboratory analysis for the examination of whole-body composition in Atlantic salmon (Salmo salar). The DXA results demonstrated a high degree of correlation (>0.90) with CST analyses for total mass, fat mass and lean mass analysis. However, there was less agreement between the methods for bone mineral content analysis. Furthermore, regression equations generated from the dataset can predict CST equivalents for fat, lean and total mass with high precision. We conclude that DXA is a feasible substitute over traditional laboratory analysis methods and warrants further study.
{"title":"Evaluating a dual-energy X-ray absorptiometry protocol to determine the body composition of Atlantic Salmon (Salmo salar)","authors":"Michael J. Salini , Rehan Mohammed , Kristy DiGiacomo , Jayde Kirkham , David S. Francis , Chethana Minoli Tissera , Aaron Spence","doi":"10.1016/j.aquaeng.2025.102676","DOIUrl":"10.1016/j.aquaeng.2025.102676","url":null,"abstract":"<div><div>Knowledge of fish proximate composition is vital for farmers and researchers to make proactive management decisions and informed research interpretations. Currently, this is a cumbersome process requiring destructive sampling and specialised laboratory methods. This study strengthens the decision-making process for farmers and researchers by evaluating a rapid method for understanding fish proximate composition. We hypothesise that dual-energy X-ray absorptiometry (DXA) technology, designed and intended for human and livestock subjects, may also prove applicable for aquatic life. If proven, it enables a rapid, non-invasive and harmless method for analysing fish proximate composition and prediction of overall condition. In this study, we compare a DXA protocol with gold-standard “comparative slaughter techniques” (CST) of laboratory analysis for the examination of whole-body composition in Atlantic salmon (<em>Salmo salar</em>). The DXA results demonstrated a high degree of correlation (>0.90) with CST analyses for total mass, fat mass and lean mass analysis. However, there was less agreement between the methods for bone mineral content analysis. Furthermore, regression equations generated from the dataset can predict CST equivalents for fat, lean and total mass with high precision. We conclude that DXA is a feasible substitute over traditional laboratory analysis methods and warrants further study.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"113 ","pages":"Article 102676"},"PeriodicalIF":4.3,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145692425","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}
Floating photobioreactors have recently attracted attention to utilize water surface areas such as estuaries, oceans, lakes, aquaculture ponds for microalgae biomass production. Outdoor cultivations of Tisochrysis lutea with a novel floating oscillation photobioreactor, named CRADLE, were conducted in triplicates under tropical climatic setting in Malaysia. The batch cultivations were performed in September 2022, November 2023, and March 2023. Biomass and fucoxanthin were analyzed using culture aliquot sampled every morning. The maximum dry weights of T. lutea were 0.99 ± 0.11–1.1 ± 0.0 g L−1 under continuous mixing in November 2022 and March 2023. The dry weight and fucoxanthin yield under continuous mixing were significantly higher than that achieved under intermittent mixing (p < 0.05). Additionally, the November 2022 and March 2023 experiments showed higher maximum dry weight than that in September 2022 due to the supplementation of 0.01 M NaHCO3. Considering the energy cost of mixing, the CRADLE demonstrated a 65.9–71.1 % reduction in mixing energy compared with aerated cultivation with bubble column photobioreactor and obtained fucoxanthin productivity per unit of mixing energy within the range of 1.2 ± 0.08–3.6 ± 0.48 mg kWh−1 under continuous oscillation mixing. Overall, these results contribute to the understanding of how oscillation mixing affects microalgae production and fucoxanthin accumulation. The CRADLE, which uses the electric rotary motor for culture mixing, reduced mixing cost and did not require temperature control, thereby demonstrating its potential for energy-saving microalgal cultivation.
浮式光生物反应器利用河口、海洋、湖泊、水产养殖池塘等水面区域生产微藻生物量，近年来受到广泛关注。在马来西亚的热带气候环境下，用一种名为CRADLE的新型浮动振荡光生物反应器进行了三次室外栽培。批量培养分别于2022年9月、2023年11月和2023年3月进行。生物量和岩藻黄素每天早晨取样进行分析。2022年11月和2023年3月连续搅拌条件下，黄茶最大干重为0.99 ± 0.11-1.1 ± 0.0 g L−1。连续混合条件下的干重和岩藻黄素产量显著高于间歇混合条件（p <； 0.05）。此外，由于添加0.01 M NaHCO3, 2022年11月和2023年3月试验的最大干重高于2022年9月。考虑到混合的能量成本，与气泡柱光生物反应器的曝气培养相比，CRADLE的混合能量降低了65.9-71.1 %，在连续振荡混合下，单位混合能量的岩藻黄素产量在1.2 ± 0.08-3.6 ± 0.48 mg kWh−1范围内。总的来说，这些结果有助于理解振荡混合如何影响微藻的生产和岩藻黄素的积累。CRADLE采用电动旋转马达进行培养混合，降低了混合成本，不需要控制温度，从而显示了其节能微藻培养的潜力。
{"title":"Pilot outdoor cultivation of a marine haptophyte Tisochrysis lutea using a novel floating photobioreactor driven by electric rotary motor","authors":"Masashi Fujii , Yoshiki Takayama , Chiaki Tomatsu , Kashu Sano , Hidemi Kishinami , Minamo Hirahara , Abd Wahab Farahin , Razif Harun , Fatimah Md. Yusoff , Fadhil Syukri , Ken Furuya , Tatsuki Toda","doi":"10.1016/j.aquaeng.2025.102666","DOIUrl":"10.1016/j.aquaeng.2025.102666","url":null,"abstract":"<div><div>Floating photobioreactors have recently attracted attention to utilize water surface areas such as estuaries, oceans, lakes, aquaculture ponds for microalgae biomass production. Outdoor cultivations of <em>Tisochrysis lutea</em> with a novel floating oscillation photobioreactor, named CRADLE, were conducted in triplicates under tropical climatic setting in Malaysia. The batch cultivations were performed in September 2022, November 2023, and March 2023. Biomass and fucoxanthin were analyzed using culture aliquot sampled every morning. The maximum dry weights of <em>T. lutea</em> were 0.99 ± 0.11–1.1 ± 0.0 g L<sup>−1</sup> under continuous mixing in November 2022 and March 2023. The dry weight and fucoxanthin yield under continuous mixing were significantly higher than that achieved under intermittent mixing (<em>p</em> < 0.05). Additionally, the November 2022 and March 2023 experiments showed higher maximum dry weight than that in September 2022 due to the supplementation of 0.01 M NaHCO<sub>3</sub>. Considering the energy cost of mixing, the CRADLE demonstrated a 65.9–71.1 % reduction in mixing energy compared with aerated cultivation with bubble column photobioreactor and obtained fucoxanthin productivity per unit of mixing energy within the range of 1.2 ± 0.08–3.6 ± 0.48 mg kWh<sup>−1</sup> under continuous oscillation mixing. Overall, these results contribute to the understanding of how oscillation mixing affects microalgae production and fucoxanthin accumulation. The CRADLE, which uses the electric rotary motor for culture mixing, reduced mixing cost and did not require temperature control, thereby demonstrating its potential for energy-saving microalgal cultivation.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"113 ","pages":"Article 102666"},"PeriodicalIF":4.3,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145692423","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}
Pub Date : 2025-12-01DOI: 10.1016/j.aquaeng.2025.102675
Silvio Peixoto , Vinicius Kenji Takahashi , Fábio Costa Filho , Priscilla Celes Maciel Lima , João Victor dos Santos Melo , Maria Eduarda de Moura Mendonça , Ignacio Sánchez-Gendriz , Roberta Soares
The mandibles of Penaeus vannamei produce click-like sounds during food ingestion, a mechanism increasingly utilized in passive acoustic monitoring (PAM) to assess shrimp feeding behavior and inform automated feeding systems. Despite extensive research on pelleted diets, the acoustic characteristics of clicks associated with fresh food items found in shrimp farming remain largely unexplored. This study compared the acoustic profiles of clicks emitted by P. vannamei when fed polychaete (Nereis sp), shrimp (P. vannamei), fish (Poecilia sphenops), mussel (Mytella strigata), artemia nauplii (Artemia salina), insect (Zophobas morio) and commercial pelleted diet under controlled laboratory conditions. Initial video-synchronized hydrophone recordings in glass aquarium confirmed that clicks were produced during mandible occlusion for all food types. Subsequent anechoic chamber recordings and high-resolution audio analysis revealed significant differences among food items in peak frequency, low and high frequency, maximum power, and click duration. Soft foods, including artemia and mussel, produced clicks with lower acoustic energy and shorter duration, whereas pelleted feed and shrimp meat elicited clicks with higher energy and longer duration. An ensemble-based machine learning model accurately classified feeding activity across most food types, highlighting distinctive acoustic signatures and potential challenges in distinguishing acoustically similar items. These findings advance our understanding of P. vannamei feeding acoustics, supporting improved algorithmic evaluation of shrimp feeding in PAM-based automated systems and offering new opportunities for monitoring feeding behavior in both grow-out ponds and maturation tanks.
{"title":"The noisy eaters: Acoustic characterization of clicks emitted by Penaeus vannamei fed fresh food items and pelletized diet","authors":"Silvio Peixoto , Vinicius Kenji Takahashi , Fábio Costa Filho , Priscilla Celes Maciel Lima , João Victor dos Santos Melo , Maria Eduarda de Moura Mendonça , Ignacio Sánchez-Gendriz , Roberta Soares","doi":"10.1016/j.aquaeng.2025.102675","DOIUrl":"10.1016/j.aquaeng.2025.102675","url":null,"abstract":"<div><div>The mandibles of <em>Penaeus vannamei</em> produce click-like sounds during food ingestion, a mechanism increasingly utilized in passive acoustic monitoring (PAM) to assess shrimp feeding behavior and inform automated feeding systems. Despite extensive research on pelleted diets, the acoustic characteristics of clicks associated with fresh food items found in shrimp farming remain largely unexplored. This study compared the acoustic profiles of clicks emitted by <em>P. vannamei</em> when fed polychaete (<em>Nereis sp</em>), shrimp (<em>P. vannamei</em>), fish (<em>Poecilia sphenops</em>), mussel (<em>Mytella strigata</em>), artemia nauplii (<em>Artemia salina</em>), insect (<em>Zophobas morio</em>) and commercial pelleted diet under controlled laboratory conditions. Initial video-synchronized hydrophone recordings in glass aquarium confirmed that clicks were produced during mandible occlusion for all food types. Subsequent anechoic chamber recordings and high-resolution audio analysis revealed significant differences among food items in peak frequency, low and high frequency, maximum power, and click duration. Soft foods, including artemia and mussel, produced clicks with lower acoustic energy and shorter duration, whereas pelleted feed and shrimp meat elicited clicks with higher energy and longer duration. An ensemble-based machine learning model accurately classified feeding activity across most food types, highlighting distinctive acoustic signatures and potential challenges in distinguishing acoustically similar items. These findings advance our understanding of <em>P. vannamei</em> feeding acoustics, supporting improved algorithmic evaluation of shrimp feeding in PAM-based automated systems and offering new opportunities for monitoring feeding behavior in both grow-out ponds and maturation tanks.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"113 ","pages":"Article 102675"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145692424","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}
Pub Date : 2025-11-21DOI: 10.1016/j.aquaeng.2025.102665
Kai Wang , Yi-Han Wen , Jia-Ming Liu , Cheng Liang , Shuo Huang
To enhance the hydrodynamic design of semi-submersible aquaculture platforms and mitigate potential risks, this study focuses on quantifying the nonlinear effects of structural design and nets on the surrounding flow field by carrying out both scaled model experiments and numerical simulations. The porous media method integrated with the Shear-Stress Transport k-ω turbulence model is employed to characterize fluid behavior, with results validated against experimental measurements. Investigations are conducted under inflow angles of 0° and 90°, at velocities of 0.2–0.4 m/s, and for configurations of net-free and net-equipped platforms. Good agreement is achieved, with a maximum drag coefficient error of 15 % for the net-free platform and a velocity reduction percentage error of 10 % for the net-equipped case. The platform structure induces abrupt velocity variations in the surrounding near-field, with flow significantly altered both in proximity to the structure and within the enclosed internal regions due to structural interference. The influence of nets on flow attenuation intensifies with increasing inflow velocity, with maximum velocity reduction reaching 18.4 % at 0° and 9.7 % at 90°, while dissipating coherent vortices and resulting in homogenized vorticity distribution throughout the internal regions enclosed within the platform structure. Structural details are significant: chamfered cross-sections produce a wake width 0.2 times that of non-chamfered ones. Furthermore, traditional empirical formulas for velocity attenuation overpredict values by approximately 10 % at 0°. At 90°, these formulas fail to capture the flow behavior, as local flow acceleration may occur due to structural interference. These results provide critical insights for safety assessments and design refinements of semi-submersible aquaculture platforms.
{"title":"Numerical and experimental studies on the flow field of a semi-submersible aquaculture platform","authors":"Kai Wang , Yi-Han Wen , Jia-Ming Liu , Cheng Liang , Shuo Huang","doi":"10.1016/j.aquaeng.2025.102665","DOIUrl":"10.1016/j.aquaeng.2025.102665","url":null,"abstract":"<div><div>To enhance the hydrodynamic design of semi-submersible aquaculture platforms and mitigate potential risks, this study focuses on quantifying the nonlinear effects of structural design and nets on the surrounding flow field by carrying out both scaled model experiments and numerical simulations. The porous media method integrated with the Shear-Stress Transport k-ω turbulence model is employed to characterize fluid behavior, with results validated against experimental measurements. Investigations are conducted under inflow angles of 0° and 90°, at velocities of 0.2–0.4 m/s, and for configurations of net-free and net-equipped platforms. Good agreement is achieved, with a maximum drag coefficient error of 15 % for the net-free platform and a velocity reduction percentage error of 10 % for the net-equipped case. The platform structure induces abrupt velocity variations in the surrounding near-field, with flow significantly altered both in proximity to the structure and within the enclosed internal regions due to structural interference. The influence of nets on flow attenuation intensifies with increasing inflow velocity, with maximum velocity reduction reaching 18.4 % at 0° and 9.7 % at 90°, while dissipating coherent vortices and resulting in homogenized vorticity distribution throughout the internal regions enclosed within the platform structure. Structural details are significant: chamfered cross-sections produce a wake width 0.2 times that of non-chamfered ones. Furthermore, traditional empirical formulas for velocity attenuation overpredict values by approximately 10 % at 0°. At 90°, these formulas fail to capture the flow behavior, as local flow acceleration may occur due to structural interference. These results provide critical insights for safety assessments and design refinements of semi-submersible aquaculture platforms.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"113 ","pages":"Article 102665"},"PeriodicalIF":4.3,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610556","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}
Biodiesel, as a renewable energy source synthesized through the transesterification of algal lipids, has received increasing attention in recent years. The quality of biodiesel derived from microalgal lipids depends largely on the composition of fatty acid methyl ester in the fuel. This research employed a fractional factorial design (2 ¹¹⁻⁷) to statistically screen eleven independent factors, including NaHCO3, CO2, MgSO4.7H2O, K2HPO4, NaNO3, NH4Cl, salinity, light spectrum, aeration rate, light intensity, and temperature, for achieving a rich fatty acid profile by Chlorella sp. PG96 (a strain isolated from municipal wastewater), as well as the synthesis of superior-quality biodiesel. The effects of all eleven physicochemical factors and their interactions on the growth characteristics (biomass and lipid production) of Chlorella sp. PG96 were thoroughly investigated in our previous study. According to the experimental results of the present study, the maximum concentrations of palmitic acid (32.23 ± 2.87 %), oleic acid (31.53 ± 3.31 %), saturated fatty acids (38.07 ± 4.03 %), and monounsaturated fatty acids (33.63 ± 3.36 %) in microalgal lipids were obtained when Chlorella sp. PG96 was grown at a low NaHCO3 concentration (0 mg L⁻¹) and white light irradiation. The estimated values of biodiesel properties such as iodine value, unsaturation degree, oxidation stability, cetane number, higher heating value, density, and kinematic viscosity were all in accordance with the quality benchmarks established by ASTM and EN 14214. The findings further demonstrated that temperature and light intensity represented the key determinants influencing fatty acid composition. Aeration rate and salinity had the most significant effects on the cetane number index, whereas the oxidation stability of algal oil was markedly affected by the concentrations of NaNO₃ and NaHCO₃. Moreover, ammonium as a nitrogen source and bicarbonate as a carbon source exhibited greater significance in fatty acid biosynthesis compared with nitrate and CO₂, respectively. The interactions between NaHCO₃ and the light spectrum, as well as between NaHCO₃ and NH₄Cl, were found to be the most significant for all measured responses. It is suggested that Chlorella sp. PG96, when cultivated with elevated NH₄Cl concentration and light intensity but under reduced temperature (320 mg L⁻¹, 22,500 Lux, and 20 °C, respectively), may act as a promising feedstock for biodiesel production.
{"title":"Fractional factorial design-based evaluation of physicochemical parameters affecting biodiesel properties from Chlorella sp. PG96","authors":"Roya Parichehreh , Reza Gheshlaghi , Mahmood Akhavan Mahdavi , Hesam Kamyab","doi":"10.1016/j.aquaeng.2025.102664","DOIUrl":"10.1016/j.aquaeng.2025.102664","url":null,"abstract":"<div><div>Biodiesel, as a renewable energy source synthesized through the transesterification of algal lipids, has received increasing attention in recent years. The quality of biodiesel derived from microalgal lipids depends largely on the composition of fatty acid methyl ester in the fuel. This research employed a fractional factorial design (2 ¹¹⁻⁷) to statistically screen eleven independent factors, including NaHCO<sub>3</sub>, CO<sub>2</sub>, MgSO<sub>4</sub>.7H<sub>2</sub>O, K<sub>2</sub>HPO<sub>4</sub>, NaNO<sub>3</sub>, NH<sub>4</sub>Cl, salinity, light spectrum, aeration rate, light intensity, and temperature, for achieving a rich fatty acid profile by <em>Chlorella</em> sp. PG96 (a strain isolated from municipal wastewater), as well as the synthesis of superior-quality biodiesel. The effects of all eleven physicochemical factors and their interactions on the growth characteristics (biomass and lipid production) of <em>Chlorella</em> sp. PG96 were thoroughly investigated in our previous study. According to the experimental results of the present study, the maximum concentrations of palmitic acid (32.23 ± 2.87 %), oleic acid (31.53 ± 3.31 %), saturated fatty acids (38.07 ± 4.03 %), and monounsaturated fatty acids (33.63 ± 3.36 %) in microalgal lipids were obtained when <em>Chlorella</em> sp. PG96 was grown at a low NaHCO<sub>3</sub> concentration (0 mg L⁻¹) and white light irradiation. The estimated values of biodiesel properties such as iodine value, unsaturation degree, oxidation stability, cetane number, higher heating value, density, and kinematic viscosity were all in accordance with the quality benchmarks established by ASTM and EN 14214. The findings further demonstrated that temperature and light intensity represented the key determinants influencing fatty acid composition. Aeration rate and salinity had the most significant effects on the cetane number index, whereas the oxidation stability of algal oil was markedly affected by the concentrations of NaNO₃ and NaHCO₃. Moreover, ammonium as a nitrogen source and bicarbonate as a carbon source exhibited greater significance in fatty acid biosynthesis compared with nitrate and CO₂, respectively. The interactions between NaHCO₃ and the light spectrum, as well as between NaHCO₃ and NH₄Cl, were found to be the most significant for all measured responses. It is suggested that <em>Chlorella</em> sp. PG96, when cultivated with elevated NH₄Cl concentration and light intensity but under reduced temperature (320 mg L⁻¹, 22,500 Lux, and 20 °C, respectively), may act as a promising feedstock for biodiesel production.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102664"},"PeriodicalIF":4.3,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575887","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}
This study investigated the effects of Spirulina platensis integration in a biofloc technology (BFT) system on water quality, biofloc composition, growth performance, fillet nutritional profiles, antioxidant activities, and gut microbiota in common carp (C. carpio)(100 g) under zero-water exchange conditions over 60 days. Four treatments were evaluated: Control (no biofloc or Spirulina), biofloc (BFT without Spirulina), biofloc+Spirulina (BFT with weekly Spirulina at 0.1 g/L), and Spirulina (Spirulina without BFT). biofloc+Spirulina exhibited superior growth metrics, including weight gain (204.43 g), specific growth rate (2.76 %/day), and feed conversion ratio (1.82), alongside enhanced fillet protein (55.58 %) and polyunsaturated fatty acid content (e.g., DHA 15.62 % in Spirulina) (P < 0.05). Water quality improved markedly in biofloc+Spirulina treatments, with reduced TAN-N (<0.1 mg/L) and nitrite (<0.1 mg/L), while nitrate accumulated moderately (up to 6.95 mg/L) (P < 0.05). biofloc composition was enriched in Spirulina treatments, with protein reaching 64.75 % (P < 0.05). Antioxidant capacities were the highest in biofloc+Spirulina (TAC 22.55 μmol/g; DPPH scavenging 65.05 %). Gut microbiota shifted towards probiotic genera (e.g., Rhodopseudomonas 15 %) in biofloc treatment, modulating cytokines with elevated TNF-α (1.9 in biofloc+Spirulina treatment) and IL-10 (1.5 in Spirulina treatment). Sensory attributes improved, with overall acceptance at 6.85 in biofloc+Spirulina. These findings demonstrate that Spirulina-enhanced BFT optimises sustainability, nutritional quality, and health in carp aquaculture, promoting sustainable and cost-effective production systems.
{"title":"The effect of Spirulina platensis on water quality factors, biofloc composition, growth efficiency, fatty acid and amino acid profile of fillets, carcass composition, antioxidant activities, bacterial population, and gene expersion in common carp (Cyprinus carpio) reared in a system without water exchange","authors":"Roholamin Alishahi , Manizheh Biabani Asrami , Raheb Mahforouzi , Saeid Vahdat , Sakineh Yeganeh","doi":"10.1016/j.aquaeng.2025.102660","DOIUrl":"10.1016/j.aquaeng.2025.102660","url":null,"abstract":"<div><div>This study investigated the effects of <em>Spirulina platensis</em> integration in a biofloc technology (BFT) system on water quality, biofloc composition, growth performance, fillet nutritional profiles, antioxidant activities, and gut microbiota in common carp (<em>C. carpio</em>)(100 g) under zero-water exchange conditions over 60 days. Four treatments were evaluated: Control (no biofloc or <em>Spirulina</em>), biofloc (BFT without <em>Spirulina</em>), biofloc+<em>Spirulina</em> (BFT with weekly <em>Spirulina</em> at 0.1 g/L), and <em>Spirulina</em> (<em>Spirulina</em> without BFT). biofloc+<em>Spirulina</em> exhibited superior growth metrics, including weight gain (204.43 g), specific growth rate (2.76 %/day), and feed conversion ratio (1.82), alongside enhanced fillet protein (55.58 %) and polyunsaturated fatty acid content (e.g., DHA 15.62 % in <em>Spirulina</em>) (P < 0.05). Water quality improved markedly in biofloc+<em>Spirulina</em> treatments, with reduced TAN-N (<0.1 mg/L) and nitrite (<0.1 mg/L), while nitrate accumulated moderately (up to 6.95 mg/L) (P < 0.05). biofloc composition was enriched in <em>Spirulina</em> treatments, with protein reaching 64.75 % (P < 0.05). Antioxidant capacities were the highest in biofloc+<em>Spirulina</em> (TAC 22.55 μmol/g; DPPH scavenging 65.05 %). Gut microbiota shifted towards probiotic genera (e.g., <em>Rhodopseudomonas</em> 15 %) in biofloc treatment, modulating cytokines with elevated TNF-α (1.9 in biofloc+<em>Spirulina</em> treatment) and IL-10 (1.5 in <em>Spirulina</em> treatment). Sensory attributes improved, with overall acceptance at 6.85 in biofloc+<em>Spirulina</em>. These findings demonstrate that <em>Spirulina</em>-enhanced BFT optimises sustainability, nutritional quality, and health in carp aquaculture, promoting sustainable and cost-effective production systems.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102660"},"PeriodicalIF":4.3,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525330","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}
Pub Date : 2025-11-05DOI: 10.1016/j.aquaeng.2025.102662
Alioune Diouf , Leandre Bereziat , David Nodier , Marco Amaral , Sinan Haliyo , Abdelkrim Mannioui
The accurate quantification and continuous monitoring of Brachionus plicatilis. rotifer cultures are essential for aquaculture and aquatic animal research laboratories. Manual counting methods are labor-intensive, error-prone, and inefficient for large-scale operations, necessitating automated solutions. This study presents the Rotiferometer, an automated and cost-effective system that integrates mechanical design, deep learning, and automation for precise rotifer detection, classification and counting. Using a YOLOv8 model, the system achieves a mean average precision ([email protected]) of 94.7 % in distinguishing gravid and non-gravid rotifers. It proceeds by scanning a 1 mL Sedgewick Rafter slide under 3 min, ensuring rapid and accurate enumeration. A strong correlation was observed between manual and Rotiferometer counts, (with R2 values of 0.9729 and 0.9868 for gravid (egg-bearing) and non-gravid (non-egg-bearing) rotifers, respectively), confirming the system’s accuracy. Additionally, the analysis of operator variability using the Rotiferometer delivered consistent results regardless of the user, minimizing the need for specialized expertise. Finally, a 45-day monitoring experiment with the Rotiferometer effectively tracked rotifer population changes, identifying key phases of growth, decline, and recovery. These results highlight the device’s potential to enhance rotifer culture management by providing real-time, reliable, and automated monitoring, thereby optimizing aquaculture productivity and research efficiency.
{"title":"Rotiferometer: An automated system for quantification of rotifer cultures","authors":"Alioune Diouf , Leandre Bereziat , David Nodier , Marco Amaral , Sinan Haliyo , Abdelkrim Mannioui","doi":"10.1016/j.aquaeng.2025.102662","DOIUrl":"10.1016/j.aquaeng.2025.102662","url":null,"abstract":"<div><div>The accurate quantification and continuous monitoring of <em>Brachionus plicatilis.</em> rotifer cultures are essential for aquaculture and aquatic animal research laboratories. Manual counting methods are labor-intensive, error-prone, and inefficient for large-scale operations, necessitating automated solutions. This study presents the Rotiferometer, an automated and cost-effective system that integrates mechanical design, deep learning, and automation for precise rotifer detection, classification and counting. Using a YOLOv8 model, the system achieves a mean average precision ([email protected]) of 94.7 % in distinguishing gravid and non-gravid rotifers. It proceeds by scanning a 1 mL Sedgewick Rafter slide under 3 min, ensuring rapid and accurate enumeration. A strong correlation was observed between manual and Rotiferometer counts, (with R2 values of 0.9729 and 0.9868 for gravid (egg-bearing) and non-gravid (non-egg-bearing) rotifers, respectively), confirming the system’s accuracy. Additionally, the analysis of operator variability using the Rotiferometer delivered consistent results regardless of the user, minimizing the need for specialized expertise. Finally, a 45-day monitoring experiment with the Rotiferometer effectively tracked rotifer population changes, identifying key phases of growth, decline, and recovery. These results highlight the device’s potential to enhance rotifer culture management by providing real-time, reliable, and automated monitoring, thereby optimizing aquaculture productivity and research efficiency.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102662"},"PeriodicalIF":4.3,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145462656","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}
Pub Date : 2025-11-05DOI: 10.1016/j.aquaeng.2025.102661
Qi Chen , Weifeng Zhou
The larvae of Anguilla japonica in the so-called "glass eel" stage are characterized by their small body size, transparent appearance, and prominent eye structure. Their transparency makes it difficult for conventional models to accurately detect and count individuals. To address the challenges of detecting and calculating glass eels from images, particularly given the morphological phenotype of these elvers, this study proposes a dual-channel attention fusion network model based on YOLOv10, named DPAF-YOLO (Adaptive Feature Fusion Module-YOLO). Firstly, the images containing high-density and overlapping glass eels were collected in situ from the fishing site. Then it takes the processing of sharpening to enhance the eye features of glass eel and to construct the necessary dataset. Based on the YOLOv10-m model, this study expands the detection heads to four by introducing an additional one, adopts an attention mechanism to achieve feature fusion of two different channels and Simplified SPPF module, and improves the loss function with the Focal DIoU to enhance detection accuracy and robustness. The effectiveness of the improvements was verified through ablation and comparative experiments. The result shows that the DPAF-YOLO model achieved an accuracy rate of 94.6 % and a recall rate of 95.2 %, with mAP50 and mAP50–95 reaching 96.8 % and 42.8 %, respectively. Compared with other YOLO models, this model demonstrates a significant improvement in accuracy for glass eel’s detection. Furthermore, we employ Eigen-CAM to generate heatmaps that highlight the image regions most critical to the model's classification decisions enhancing model interpretability, which indicates that the proposed algorithm performs well in both dense and sparse scenarios, with a particular focus on the eye region of glass eels, providing a reliable solution for glass eel detection and fry counting in the fishery domain.
{"title":"DPAF-YOLO: YOLO-based dual-path attention fusion for glass eel detection and counting","authors":"Qi Chen , Weifeng Zhou","doi":"10.1016/j.aquaeng.2025.102661","DOIUrl":"10.1016/j.aquaeng.2025.102661","url":null,"abstract":"<div><div>The larvae of <em>Anguilla japonica</em> in the so-called \"glass eel\" stage are characterized by their small body size, transparent appearance, and prominent eye structure. Their transparency makes it difficult for conventional models to accurately detect and count individuals. To address the challenges of detecting and calculating glass eels from images, particularly given the morphological phenotype of these elvers, this study proposes a dual-channel attention fusion network model based on YOLOv10, named DPAF-YOLO (Adaptive Feature Fusion Module-YOLO). Firstly, the images containing high-density and overlapping glass eels were collected in situ from the fishing site. Then it takes the processing of sharpening to enhance the eye features of glass eel and to construct the necessary dataset. Based on the YOLOv10-m model, this study expands the detection heads to four by introducing an additional one, adopts an attention mechanism to achieve feature fusion of two different channels and Simplified SPPF module, and improves the loss function with the Focal DIoU to enhance detection accuracy and robustness. The effectiveness of the improvements was verified through ablation and comparative experiments. The result shows that the DPAF-YOLO model achieved an accuracy rate of 94.6 % and a recall rate of 95.2 %, with mAP50 and mAP50–95 reaching 96.8 % and 42.8 %, respectively. Compared with other YOLO models, this model demonstrates a significant improvement in accuracy for glass eel’s detection. Furthermore, we employ Eigen-CAM to generate heatmaps that highlight the image regions most critical to the model's classification decisions enhancing model interpretability, which indicates that the proposed algorithm performs well in both dense and sparse scenarios, with a particular focus on the eye region of glass eels, providing a reliable solution for glass eel detection and fry counting in the fishery domain.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102661"},"PeriodicalIF":4.3,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525329","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}
Pub Date : 2025-11-05DOI: 10.1016/j.aquaeng.2025.102663
Zhiyu Zou , Wei Fan , Yonggang Zhao , Hang Zhang , Bingxiao Bai , Zongpei Jiang , Yiwen Pan
The escalating global demand for seafood necessitates the development of sustainable aquaculture practices. Bivalves represent a critical solution for food security due to their dual roles as protein sources and natural carbon sinks, positioning them as key contributors to climate change mitigation. However, high-density farming structures in bivalve aquaculture impede natural water circulation, reducing phytoplankton availability as food supply and increasing mortality rates. This study introduces air-lift artificial upwelling (AU) as a novel approach to restore culture conditions by generating bubble-entrained plumes (BEPs). The plumes entrain and transport the food-rich water at a lower water level to the bivalve canopy layer, consequently enhancing productivity. We systematically characterized BEP hydrodynamics in stratified environments. A transport capacity evaluation method was developed using chlorophyll-a (Chl-a) fluorescence as a proxy for food concentration. By maximizing the transport capacity, the AU system is capable of providing maximum food delivery capacity with limited energy. Theoretical approaches were validated through laboratory experiments and computational fluid dynamics (CFD) simulations, demonstrating the model's ability to predict BEP trajectories and entrainment rates. Field deployment of an optimized air-lift AU system in a mussel farm revealed a 40.2 % increase in Chl-a concentration within the farming layer, corresponding to a 16.4 % increase in energy supply for mussel growth based on the Dynamic Energy Budget (DEB) model, confirming its efficacy in improving productivity.
{"title":"Implementation strategies for artificial upwelling to improve productivity in intensive bivalve aquaculture","authors":"Zhiyu Zou , Wei Fan , Yonggang Zhao , Hang Zhang , Bingxiao Bai , Zongpei Jiang , Yiwen Pan","doi":"10.1016/j.aquaeng.2025.102663","DOIUrl":"10.1016/j.aquaeng.2025.102663","url":null,"abstract":"<div><div>The escalating global demand for seafood necessitates the development of sustainable aquaculture practices. Bivalves represent a critical solution for food security due to their dual roles as protein sources and natural carbon sinks, positioning them as key contributors to climate change mitigation. However, high-density farming structures in bivalve aquaculture impede natural water circulation, reducing phytoplankton availability as food supply and increasing mortality rates. This study introduces air-lift artificial upwelling (AU) as a novel approach to restore culture conditions by generating bubble-entrained plumes (BEPs). The plumes entrain and transport the food-rich water at a lower water level to the bivalve canopy layer, consequently enhancing productivity. We systematically characterized BEP hydrodynamics in stratified environments. A transport capacity evaluation method was developed using chlorophyll-a (Chl-a) fluorescence as a proxy for food concentration. By maximizing the transport capacity, the AU system is capable of providing maximum food delivery capacity with limited energy. Theoretical approaches were validated through laboratory experiments and computational fluid dynamics (CFD) simulations, demonstrating the model's ability to predict BEP trajectories and entrainment rates. Field deployment of an optimized air-lift AU system in a mussel farm revealed a 40.2 % increase in Chl-a concentration within the farming layer, corresponding to a 16.4 % increase in energy supply for mussel growth based on the Dynamic Energy Budget (DEB) model, confirming its efficacy in improving productivity.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102663"},"PeriodicalIF":4.3,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525327","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}
Pub Date : 2025-11-03DOI: 10.1016/j.aquaeng.2025.102659
Ajitha Eliza , Diwan Baskaran
<div><div>Eichhornia crassipes has an extreme rapid growth rate, and has capability to doubling its population in approximately two to three weeks under optimal conditions, with biomass accumulation. It is required to protect the safety of water resources with rigorous ecological environment by detecting Eichhornia crassipes using deep learning techniques. The conventional techniques of Eichhornia crassipes paves more attention to reduce the growth rate of Eichhornia crassipes on the aquatic environment, but real-time monitoring of large areas is critical and it becomes challenging issue. Moreover, conventional models provide low accuracy and poor detection results on target species with unclear satellite image characteristics. Hence, to overcome these issues a new developed strategy for segmenting the Eichhornia crassipes is implemented to identify the growth rate and formulate effective control strategies. Initially, the required multi-spectral images are fetched from the distinct standard datasets for recognizing the Eichhornia crassipes growth rate. The acquired images are fed to the Region-Vision Transformer-based Adaptive Yolo (RViT-Yolo-Unet++) for performing joint detection and segmentation. The RViT-Yolo detection model captures long-range contextual dependencies and global relationships, which leads to more comprehensive understanding of complex patterns. RViT-Yolo improves the accuracy and speed by adapting the visual characteristics of the Eichhornia crassipes. While, the Unet++ segmentation model provide better growth rate through resource partitioning, and allows for propagation. The RViT-Yolo-Unet++ segmentation process manage its invasive growth by identifying and removing irrelevant boundaries of the image, leading improved water quality, enhanced biofuel production, and optimized pollution control. The detection and segmentation networks are serially connected to provide efficient growth rate detection results. Initially, the garnered images are applied to the Eichhornia crassipes detection module, where the RViT-Yolo is utilized for detecting the Eichhornia crassipes in a specific region. Moreover, for improving the detection performance of Eichhornia crassipes, the parameters of Yolo are optimally selected by an Improved Crayfish Optimization Algorithm (TI-COA). While optimizing Eichhornia crassipes, it enhances growth rate, and provides greater quantity of biomass production to recover the resources. Also, it improves the water quality and reduces the operating costs and making wastewater treatment more economically feasible. Subsequently, the detected region images are passed to the segmentation module, where the Unet++ model is used for segmenting the Eichhornia crassipes affected regions that help to discover the Eichhornia crassipes growth rate. Finally, the research experiments are performed for the implemented framework by comparing the best measure of accuracy shows 7.98 % Unet, 7.52 % Unet3 + , 7.06 % ResUnet, and 4.8
{"title":"A novel detection and segmentation system for eichhornia crassipes growth rate using region vision transformer-based adaptive Yolo with Unet++","authors":"Ajitha Eliza , Diwan Baskaran","doi":"10.1016/j.aquaeng.2025.102659","DOIUrl":"10.1016/j.aquaeng.2025.102659","url":null,"abstract":"<div><div>Eichhornia crassipes has an extreme rapid growth rate, and has capability to doubling its population in approximately two to three weeks under optimal conditions, with biomass accumulation. It is required to protect the safety of water resources with rigorous ecological environment by detecting Eichhornia crassipes using deep learning techniques. The conventional techniques of Eichhornia crassipes paves more attention to reduce the growth rate of Eichhornia crassipes on the aquatic environment, but real-time monitoring of large areas is critical and it becomes challenging issue. Moreover, conventional models provide low accuracy and poor detection results on target species with unclear satellite image characteristics. Hence, to overcome these issues a new developed strategy for segmenting the Eichhornia crassipes is implemented to identify the growth rate and formulate effective control strategies. Initially, the required multi-spectral images are fetched from the distinct standard datasets for recognizing the Eichhornia crassipes growth rate. The acquired images are fed to the Region-Vision Transformer-based Adaptive Yolo (RViT-Yolo-Unet++) for performing joint detection and segmentation. The RViT-Yolo detection model captures long-range contextual dependencies and global relationships, which leads to more comprehensive understanding of complex patterns. RViT-Yolo improves the accuracy and speed by adapting the visual characteristics of the Eichhornia crassipes. While, the Unet++ segmentation model provide better growth rate through resource partitioning, and allows for propagation. The RViT-Yolo-Unet++ segmentation process manage its invasive growth by identifying and removing irrelevant boundaries of the image, leading improved water quality, enhanced biofuel production, and optimized pollution control. The detection and segmentation networks are serially connected to provide efficient growth rate detection results. Initially, the garnered images are applied to the Eichhornia crassipes detection module, where the RViT-Yolo is utilized for detecting the Eichhornia crassipes in a specific region. Moreover, for improving the detection performance of Eichhornia crassipes, the parameters of Yolo are optimally selected by an Improved Crayfish Optimization Algorithm (TI-COA). While optimizing Eichhornia crassipes, it enhances growth rate, and provides greater quantity of biomass production to recover the resources. Also, it improves the water quality and reduces the operating costs and making wastewater treatment more economically feasible. Subsequently, the detected region images are passed to the segmentation module, where the Unet++ model is used for segmenting the Eichhornia crassipes affected regions that help to discover the Eichhornia crassipes growth rate. Finally, the research experiments are performed for the implemented framework by comparing the best measure of accuracy shows 7.98 % Unet, 7.52 % Unet3 + , 7.06 % ResUnet, and 4.8","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"112 ","pages":"Article 102659"},"PeriodicalIF":4.3,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525328","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}
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