Aquaculture Ponds Research Articles

Eurasian Sparrowhawk (Accipiter nisus) Population Trend and Productivity in Central Israel

ABSTRACT Israel’s nationwide multiyear campaigns, particularly in the late 18th and early 19th centuries, involved deforestation and the development of natural areas for agriculture and human settlement, and resulted in the local extirpation of several animal species. However, reforestation began in the 1940s and promoted the resurgence of extirpated populations. One species that has benefited from these landscape changes is the Eurasian Sparrowhawk (Accipiter nisus). Based on the analysis of population trends in the Judea region (central Israel), we found that this species’ abundance increased by 8.9% over a 5-yr study period (2006–2010). We also found that hatching day was the only reproductive parameter in our study area that varied significantly among years. This breeding parameter depended on three habitat characteristics: (1) the height of the nest; (2) the amount of mixed forest with sparse cover in the area around the nest; and (3) the amount of herbaceous vegetation around the nest. Hatching began earlier in higher nests, and hatching began later in nests surrounded by a high percentage of mixed forest and herbaceous vegetation. However, productivity was independent of the habitat type surrounding the nest site. Our descriptive analysis of prey types suggested that most species in the prey remains and pellets likely came from outside the forest, typically from open areas such as agricultural fields, water reservoirs, or aquaculture ponds. Further, only three species dominated the prey remains and pellets below the nests. We documented reproductive parameters and changes in population size during the early years of this population increase. We predict that the population will continue to thrive and spread into the surrounding areas, as there have been no significant changes in land management in the study area over the past 13 yr.

Categorization of antibiotic resistant bacterial populations from Shrimp and its culture environment of Andhra Pradesh, India

Antibiotic resistance is one of the major concern for rapidly growing food sectors including shrimp aquaculture. A total of 2304 heterotrophic bacteria were isolated, categorized and screened for antibiotic resistance. Identification by conventional and molecular methods confirmed the presence of sixteen bacterial genera with the predominance of Vibrio sp. (38.54 %), Bacillus sp. (19.79 %), Tenacibaculum sp. (6.46 %), Halomonas sp. (6.03 %) etc. in the shrimp ponds. The isolates showed highest resistance to oxytetracycline (Vibrio sp. 79.3 %), followed by ciprofloxacin & co-trimoxazole (Exiguobacterium sp. 66.66 %) and chloramphenicol & erythromycin (Microbacterium sp. 50 % & 66.7 %). Overall resistance by all bacteria was highest for oxytetracycline (22 %). Among different bacterial isolates, majority of Vibrio sp. exhibited resistance to all the five antibiotics that varied from 1.4 % to 87.5 % from all the sampling sites (A to L). Among different antibiotic resistant genes (ARGs) screened by PCR, the most prevalent was tetA (44 %) followed sul1 (11.8 %). Vibrio sp. and Bacillus sp. showed the presence of all screened ARGs. Shrimp aquaculture ponds harboured antibiotic resistant bacteria and act as a main reservoir of ARGs.

Soil carbon pools and microbial network stability depletion associated with wetland conversion into aquaculture ponds in Southeast China

Wetlands, which are ecosystems with the highest soil surface carbon density, have been severely degraded and replaced by artificial reclamation for fish and shrimp ponds in recent years. This transformation is causing intricate shifts in soil carbon pools and microbial stability. In this study, we examined natural wetlands and reclaimed aquaculture ponds in Southeast China to analyze the structure and network stability of soil microbial communities following the reclamation of estuarine wetlands and to elucidate the microbial-mediated mechanisms for regulating soil organic carbon (SOC). The aquaculture ponds presented significantly less average SOC content than the natural wetlands (p < 0.05). ACE, Chao1, and Shannon's indices of bacteria and fungi were decreased in aquaculture ponds. Less numbers of nodes and edge links in the co-occurrence network of soil fungi and bacteria in aquaculture ponds. This suggests reduced correlation and stability within the microbial network of aquaculture ponds. Decomposers in soil fungi (e.g. Dung Saprotroph) reduced. Reduced proportions of key phyla Ascomycota, Basidiomycota and Rozellomycota in the soil fungal network. Reduced proportions of key phyla Proteobacteria, Chloroflexi and Desulfobacterota in the soil bacterial network. In conclusion, our results suggest that converting wetland paddocks to intensive aquaculture ponds results in carbon pool loss and reduces soil microbial network stability. The results highlight the importance of protecting or moderately restoring mangrove wetlands along the coast of southeastern China. It is also predicted that such measures may enhance the storage capacity of soil carbon pools and improve the stability of carbon sequestration by soil microorganisms, thus offering a potential solution for mitigating global climate change.

Effects of cyanotoxins on nitrogen transformation in aquaculture systems with microplastics coexposure: Adsorption behavior, bacterial communities and functional genes

Microcystin-LR (MC-LR) and microplastics (MPs) have attracted increasing attention as important new pollutants in freshwater fishery environments. However, there are few reports on the effects of long-term combined MC-LR and MPs pollution on nitrogen transformation and microbial communities in aquaculture ponds, and the resulting risks have yet to be determined. Therefore, in this study, traditional refractory MPs (polystyrene, PS), biodegradable MPs (polylactic acid, PLA) and MC-LR, which are common in freshwater fishery environments in China, were selected as pollutants to construct a microcosm that simulates freshwater aquaculture ponds. MC-LR coexposure to PS and PLA was tested to reveal the effects of these pollutants on nitrogen transformation and microbial communities in aquaculture ponds, as well as to elucidate the potential risks posed by traditional refractory MPs and biodegradable MPs to freshwater aquaculture ecosystems. The results revealed that the MPs had a relatively high adsorption rate for MC-LR and that PS presented a relatively high adsorption capacity, whereas PLA presented a relatively high desorption capacity. Single or combined MPs and MC-LR pollution disrupted the normal nitrogen cycle in the aquaculture system, causing an overall loss of nitrogen in the water, and denitrification and nitrogen fixation in the water were inhibited to a certain extent through the inhibition of nitrogen cycle-related functional genes, with the PS + MC-LR group having the greatest inhibitory effect. In addition, compared with single-pollutant exposure, combined exposure to MC-LR and MPs had a greater effect on the microbial community composition. Analysis of the integrated biomarker response (IBR) index revealed that the risk of combined exposure to MC-LR and PS was greater than that of single exposure, so this phenomenon merits further attention.

Optimizing Catfish Farming Through IoT-Driven Water Quality Management

General Background: Catfish play a significant role in the global fishing industry, necessitating effective farming practices to enhance productivity and sustainability. Specific Background: However, challenges such as maintaining optimal water quality in aquaculture ponds, particularly concerning ammonia levels and temperature fluctuations, pose threats to catfish health and production efficiency. Knowledge Gap: Previous research has often focused on single-parameter monitoring, lacking comprehensive systems that integrate real-time data for both ammonia and temperature management. Aims: This study aims to develop an advanced Internet of Things (IoT) system for real-time monitoring and control of ammonia levels and water temperature in catfish ponds, facilitating optimal farming conditions. Results: The implemented system utilizes two sensors to measure ammonia and temperature, integrated with the Blynk IoT platform for remote monitoring. The findings indicate that when water temperature exceeds 26 °C, the water pump activates to regulate temperature, while ammonia levels above 5 NH3 trigger the aerator to enhance oxygen levels and reduce ammonia toxicity. Novelty: This research innovatively combines multiple sensors and modern IoT applications, offering a more robust solution for aquaculture management compared to previous studies. Implications: The monitoring system effectively maintains water quality, enhancing catfish farming sustainability and efficiency, emphasizing the need for technology integration in aquaculture to effectively tackle environmental challenges. Highlights: Real-time Monitoring: Continuous tracking of ammonia and temperature levels. Automated Control: Activates pumps and aerators based on set thresholds. Enhanced Sustainability: Supports healthier catfish and optimizes production efficiency. Keywords: Catfish Farming, IoT, Water Quality Monitoring, Ammonia Control, Temperature Management

Estimating water quality parameters of freshwater aquaculture ponds using UAV-based multispectral images

UAV imaging technology has become one of the means to quickly monitor water quality parameters in freshwater aquaculture ponds. The change of sunlight during a long flight affects the quality of UAV images, which will reduce the accuracy of monitoring water quality. This study aims to propose a method to correct spectral variation during UAV imaging and apply it to detect dissolved organic matter (DOM) concentration and dissolved oxygen (DO) content in freshwater aquaculture ponds. Firstly, a spectral correction method was used to transform UAV-based multispectral images. The spectral data before and after correction was extracted. Secondly, 18 spectral indices before and after correction were constructed. The optimal combination of indices was identified using correlation analysis algorithm. The estimation models of water quality parameters were then constructed and compared using the Random Forest (RF), Support Vector Regression (SVR), and BP neural network (BP) methods. The results showed that the accuracy of estimating DOM concentration using corrected spectral indices was significantly improved compared to pre-correction models, with the highest improvement of 38 % (SVR), the lowest of 23 % (BP), and an average improvement of 31 %. The RF model performed best, achieving R² = 0.81, RMSE = 3.34 mg/L, and MAE = 2.17 mg/L. For DO content estimation, the accuracy of models using corrected spectral indices was also improved significantly, with the highest improvement of 97 % (RF), the lowest of 39 % (SVR), and an average improvement rate of 67 %. The Random Forest model was again optimal, with R² = 0.69, RMSE = 1.97 mg/L, and MAE = 1.47 mg/L. This study indicates that the proposed spectral correction method helps to map the concentration of DOM and DO in freshwater aquaculture ponds with high accuracy using UAV-based multispectral images.

Remote sensing extraction of aquaculture ponds in China’s coastal zone based on random forest

Remote sensing extraction of aquaculture ponds in China’s coastal zone based on random forest

Monitoring water quality parameters of freshwater aquaculture ponds using UAV-based multispectral images

Monitoring water quality is crucial for water exchange, precise feeding, and quality control of water products in freshwater aquaculture. In light of the issue of spatial heterogeneity in freshwater aquaculture pond waters and the constraints of conventional sensor detection techniques and traditional machine learning models. In this study, UAV multispectral images were combined with four machine learning algorithms (Ridge, XGBoost, CatBoost, RF) and the Stacking model to model the estimation of Chlorophyll a (Chl-a) and Turbidity and map their spatial distribution. The findings indicate that, in contrast to machine learning models, the Stacking model of water quality parameter performs better with higher accuracy. Meanwhile,for Chl-a and Turbidity the optimal sub-model combination in the Stacking model varies, with the most effective estimation model for Chl-a concentration identified as RF-XGB-Ridge (R2 = 0.84, RMSE=1.882 µg/L, MAE=3.433 µg/L and Slope = 0.791). As to Turbidity, the RF-CAB-Ridge model demonstrates superior performance, with macro-averaged precision (macro-p) of 93.3 %, macro-averaged recall (macro-R) of 88.8 %, macro-averaged F1-score (macro-F1) of 0.895, and Kappa coefficient of 0.813. Furthermore, the results of the joint analyses, which included measured samples and management measures at the test site, demonstrated that the spatial distribution maps of Chl-a and Turbidity were in alignment with the current status of water quality at the test site. This consistency was observed across both temporal and spatial scales. The results demonstrate that the integration of UAV multispectral images with the Stacking model can enhance the precision of water quality parameter models, facilitates the examination of the spatial and temporal distribution of water quality parameters and the underlying influencing factors, and advances the capability for dynamic monitoring of water quality parameters in freshwater aquaculture regions. Concurrently, it offers fundamental theoretical and methodological assistance for the precise regulation of water quality in freshwater aquaculture ponds and the formulation of optimal production management strategies.

Temporal dynamics of protist communities and environmental factors in the horizontal flow-polyculture pond aquaculture model of Sinonovacula constricta

The horizontal flow (HF)–polyculture pond (PP) model has emerged as a new aquaculture model that has attracted considerable attention. The growth of Sinonovacula constricta in the HF is highly dependent on phytoplankton in the PP; however, the current understanding of the basic microbes in the HF-PP model research remains insufficient. To address this knowledge gap, we analyzed the temporal dynamics of protist communities in water and sediment samples obtained from the HF and PP in this study. In addition, we measured the temporal variations in physicochemical factors in these water and sediment samples. A comparison of water quality data between HF and PP revealed that HF effectively reduced the total nitrogen (TN) and total phosphorus (TP) levels in the polyculture ponds. Furthermore, Diatomea and Ciliophora were the predominant phyla in all samples. In the horizontal-flow water samples, significant alterations were observed over time in Skeletonema, Strombidium, and Gyrodinium genera. The dynamic pattern of the genus in the polyculture pond water (PPW) was similar to that in the horizontal flow water (HFW). Furthermore, Skeletonema abundance decreased over time in the horizontal flow sediment (HFS). Skeletonema and Cyclotella were dominant in polyculture pond sediment (PPS). There was a certain degree of community succession throughout the experiment in the HFW and PPW, but not in the HFS or PPS. Correlation analysis revealed that water temperature (WT), salinity(SAL)，dissolved oxygen (DO), pH, phosphate, and silicate played key roles in driving variations in the protist community. These findings contribute to our understanding of complex protist community dynamics within the HF-PP aquaculture model, shedding light on the roles of various environmental factors in shaping protist communities and water quality.

Complete genome sequence of aquaculture pond isolate, Bacillus velezensis M4019.

Bacillus velezensis is commonly found in soil and has various antibacterial activities against animal and plant pathogens. Here, we present the complete genome sequence of Bacillus velezensis strain M4019, isolated from a euryhaline aquaculture pond water in Yong-An, Kaohsiung City, Taiwan. This pond-water-derived isolate, unlike common soil-derived isolates, may provide potentially different adaptations and antimicrobial cues for future research.

Study on the purification of aquaculture tailwater under Sulfamethoxazole stress using algae-bacteria biofilms: Nutrient removal efficiency, microbial community, and ARGs

This study explored the dynamic processes of algae-bacteria biofilms in the remediation of aquaculture pond effluents as a novel treatment strategy. The purification capacity of the biofilms, changes in community composition, and their impact on the dissemination of antibiotic resistance genes (ARGs) were investigated under the application of sulfamethoxazole (SMX) at concentrations ranging from 100 to 1000 μg/L. The study also considered the factors influencing the abundance and diversity of ARGs and mobile genetic elements (MGEs) across different seasons, including the roles of environmental parameters and microbial community structure.The results showed that, although exposure to SMX reduced nutrient removal efficiency, photosynthetic activity, and increased oxidative stress levels, the biofilms maintained relatively high purification efficiency (with nutrient removal rates ranging from 67.62 % to 93.23 % and SMX removal rate reaching 50.13 % ± 12.34 %), demonstrating adaptability to SMX stress. Network analysis identified key microbial carriers responsible for ARG dissemination, highlighting the complex interactions between environmental factors, microbial communities, and resistance gene propagation. These findings enhance our understanding of biofilm-based water treatment systems and the seasonal factors affecting the dynamics of ARGs and MGEs.

Degradation of Emamectin Benzoate in the Aquaculture Pond Environment under Tropical Climatic Condition

Emamectin Benzoate (EMB), is an anti-parasitic drug, commonly used in aquaculture for prevention and control of parasitic infestations. The drug enters the environment through uneaten feed and faeces, ultimately accumulating in aquaculture pond sediment. Present study reports the influence of abiotic factors like, sunlight exposure (2,454 to 117,500 lux), pH, salinity and soil texture on the degradation of EMB in aquaculture pond water and sediment as per Organization for Economic Cooperation and Development (OECD). Results showed that the degradation of EMB in both water and sediment followed first-order kinetics, resulting in half-life of 5.6 days in water and 12.4 days in sediment when exposed to natural sunlight. Higher degradation of EMB was observed under alkaline conditions (pH 8.5) and at lower salinity (0.5ppt). EMB degradation is accelerated in loamy sand soil when exposed to sunlight. Results of the study suggest that in countries like India, where ample sunlight exposure is prevalent throughout the year, EMB degradation in aquaculture pond environment occurs at a rapid pace reducing the risk of accumulation in water or sediment.

Assessing sediment CO2 effluxes in the coastal ecosystem of North Sumatra, Indonesia

Coastal wetlands including mangrove play a vital role in regulating the local and global carbon cycle. Coastal areas contribute greatly to the carbon exchange process due to the complex interactions that occur between the atmosphere, land, and oceans. One of the important components in coastal carbon dynamics is CO2 gas exchange between soil, water and the atmosphere. This study aims to assess CO2 efflux across various land covers (namely natural mangrove, restored mangrove, and converted mangroves to oil palm and aquaculture pond) in the coastal areas of North Sumatra Province, and analyze the effect of sea tides and ebbs on the rate of CO2 efflux and their connection with the number and area of macrozoobenthos burrows. We applied direct sampling by using the static closed chamber method attached to portable CO2 analyzer. The mean of CO2 efflux in natural mangrove forest land covers was 866±585 mgCO2/m2/h during low tide conditions and 1137±792 mgCO2/m2/h during high tide conditions, followed by oil palm plantations at 760.71±341 mgCO2/m2/h, restored mangroves during low tide of 575.24±326 mgCO2/m2/h and 597.11±180 mg CO2/m2/h during high tide conditions, and the lowest was recorded in ponds at 588.55±358 mgCO2/m2/h. Further, we observed that tidal conditions affect the magnitudes of CO2 efflux in natural and restored mangrove forests, and we did not observe similar pattern in oil palms and ponds since these land covers were not influenced by regular tidal input. We also observed that no significant relationship between the number and area of macrozoobenthos burrows and CO2 efflux. Our findings suggest that CO2 effluxes in coastal wetlands are highly dynamic and presumably driven by complex factors and therefore, understanding their magnitudes and drivers requires extensive measurement covering large spatial and temporal scales.

Variability in N2O emission controls among different ponds within a hilly watershed

While it is well established that small water bodies like ponds play a disproportionately large role in contributing to N2O emissions, few studies have focused on lowland ponds in hilly watersheds. Here, we explored the characteristics of N2O concentrations and emissions from various typical ponds (village, tea, forested, and aquaculture ponds) in a hilly watershed and examined the specific controls influencing N2O production. Our findings revealed that tea ponds exhibited the highest N2O flux (8.42 ± 8.23 μmol m-2 d-1), which was 2.8 to 3.3 times greater than other types of ponds. Remarkable seasonal variations were observed in tea and forested ponds due to the seasonality of nutrient-enriched runoff, whereas such variations were less pronounced in village and aquaculture ponds. Key factors such as nitrogen levels, temperature, and dissolved oxygen (DO) emerged as the primary controls of N2O concentrations in ponds, heavily influenced by land use and human activities in their drainage areas. Specifically, N2O production in tea and aquaculture ponds was driven by N inputs from fertilization and feed, respectively, while DO levels governed the process in village and forested ponds, influenced by abundant algae and forest vegetation. This study emphasizes that environmental factors predominantly drive N2O production in ponds within hilly watersheds, but land use in the pond drainages acts as an indirect yet crucial influence. This highlights the need for future research to develop targeted emission reduction strategies based on land use to effectively mitigate N2O emissions, promising a path toward more sustainable and climate-friendly watershed management.

Wetland mapping in the Liaohe River Estuary using multi-source remote sensing image feature selection

ABSTRACT As a crucial node in the East Asia–Australasia migratory bird network, the Liaohe River Estuary Wetland (LREW) contributes significantly to coastal ecological balance and biodiversity. Accurate and timely mapping of the LREW is essential for monitoring ecological changes and understanding shifts in the wetland’s ecosystem structure and functions. In this study, an innovative approach that integrates radar (Sentinel-1), optical (Sentinel-2), and DEM data on Google Earth Engine (GEE) is proposed to achieve a more optimized and accurate wetland mapping. Recursive Feature Elimination (RFE) is employed to improve feature collection, facilitating the construction of an optimal feature set for Random Forest (RF) classification to extract detailed LREW information. Mapping conducted from 2017 to 2023 using the proposed approach demonstrates its effectiveness and stability in mapping the LREW, achieving overall accuracies ranging from 89.84% to 93.73% and Kappa from 0.85 to 0.91. Compared to single-source methods, the integration of multi-source data substantially enhances mapping accuracy, while RF-RFE effectively eliminates redundant features, further refining classification precision. Texture features (Sum Average, SAVG) and the Water Index 2019 (WI2019) were found to significantly influence wetland mapping. The importance of different feature types is ranked as follows: spectral features > vegetation/water body index > PCA features > SAR texture features > red-edge index > other spectral index > spectral texture features > backscatter coefficient > H-Alpha. During the study period, the wetland area increased from 849.60 km2 to 979.49 km2. This expansion was caused primarily by wetland protection policies that led to the dismantling of coastal aquaculture ponds, resulting in a reduction of 90.28 km2 in waterbodies over 7 years, with many areas transitioning to tidal flats and Suaeda salsa habitats. In conclusion, the proposed method is effective in mapping the LRE wetlands and provides reliable data support for wetland ecological protection and restoration.

Optimal balance of organic detritus and feed for fish growth and water quality improvement through regulating nutrients cycling

In order to explore the effects of different feed composition on the nutrient level and microbial loop structure in aquaculture ponds, a field simulation experiment in aquaculture ponds was conducted by adding different proportions (0%, 20%, 40% and 60%) of bagasse to fish feed for combined feeding. The addition of bagasse significantly reduced the levels of various forms of nitrogen and phosphorus in the water, especially with the addition of 60% bagasse. In the treatments without addition and with 20% bagasse added, nitrogen and phosphorus levels remained relatively high, which should be attributed to the decomposition of feed and the release of sediment, ultimately stimulating the abundant reproduction of algae. Bacterial growth was limited due to insufficient supply of organic carbon, and the growth of fish relied more on the components of the feed. With the addition of 60% bagasse, the high organic carbon and low nitrogen and phosphorus levels could not support the growth of phytoplankton, bacteria, and zooplankton. It is inferred that organic carbon may be more degraded into carbon dioxide, ultimately limiting the growth of fish. Adding 40% bagasse achieved a balanced level of carbon, nitrogen, and phosphorus, establishing a healthy and stable microbial loop structure (including phytoplankton, bacteria, and zooplankton). Most nutrients were converted into plankton, which then became natural food for fish, ensuring complete nutrient utilization. This is beneficial for both water quality improvement and fish reproduction. Therefore, adding a moderate proportion of bagasse to the feed can maximize the effects of water quality improvement, fish reproduction, and even the quality of fish meat.

Optimization of water supply parameters for enhanced thermal uniformity in aquaculture ponds under varied working conditions: An experimental study

Aquaculture ponds are critical for the successful rearing of fish larvae, and achieving consistent temperature distribution within these systems is essential for optimal growth conditions. This study explores methods for precise temperature regulation on both the water and atmospheric sides of the pond ecosystem. Based on the original design, systematic changes were made to parameters such as water supply pipe layout, bend angles, perforation rates, and working conditions. Metrics including average temperature, average temperature difference, and extreme temperature difference were utilized to extensively discuss the impacts of these parameters. Through this, temperature distributions across five distinct water supply layouts were analyzed, and the impacts of four different bending angles and perforation rates were evaluated using optimized configurations. Our findings demonstrate that a water supply layout radius of 2000 mm, coupled with a 60° bending angle and a 25 % perforation rate, increased overall temperature uniformity in the pond by 5 %. Additionally, seasonal variations significantly impact temperature distribution in ponds, particularly with different extreme temperature differences observed in winter and summer. Compared to the transitional season and summer, the average temperature difference in the pond during winter decreased by 30 % and 45 %, respectively. It was further revealed that winter conditions naturally yield more uniform water-side temperatures, making seasonal fluctuations irrelevant in determining optimal perforation rates. After the implementation of a water agitator, the average extreme temperature difference decreased from 0.6 K to 0.52 K. In the shallow water layer, the water agitator reduced the extreme temperature difference in the pond by 26 %. The use of water agitators has enhanced thermal uniformity in ponds, thereby improving the growth environment for fish larvae and providing valuable insights for environmental management in aquaculture.

Optimization of water supply parameters for enhanced thermal uniformity in aquaculture ponds: An experimental study based on orthogonal experimental design

The temperature distribution in aquaculture ponds plays a crucial role in the rearing of fish larvae. To achieve a more uniform temperature distribution in the pond and alleviate the problem of thermal stratification, precise control of pond temperature is essential. A recirculating aquaculture pond was taken as the test object. Single-factor experiments and orthogonal experiments were conducted to comprehensively test the aquaculture pond's water supply pipe layout, bend angle, perforation rate, and environmental conditions. Three evaluation indicators were used to analyze the temperature distribution of the aquaculture pond under various water supply pipe structures, leading to the identification of optimal structural configurations. The optimal structure I, obtained from single-factor experiments, was determined to be 2.5 m, 50 %, and 60°, while the optimal structure II, derived from orthogonal experiments, was 1.25 m, 75 %, and 30°. Both optimized structures exhibited significant temperature fluctuations in the pond during the summer season. However, Structure II demonstrated the lowest average temperature difference in the winter season, indicating its superior adaptability during winter. Moreover, Structure II could provide higher temperatures for shallow areas with depths greater than 600 mm, making it more suitable for fish larvae cultivation. Additionally, local devices effectively decreased temperature variations by 17.5 % within the pond. Furthermore, energy consumption output was evaluated for different operational conditions. The results showed that Structure II had the lowest energy consumption output during the summer season. In contrast, during the winter season, the energy consumption output increased by approximately 12 %, indicating significant energy-saving potential in aquaculture ponds during winter.

Efficacy of Terminalia arjuna (Roxb.) bark extracts against Salmonella sp. isolated from aquaculture ponds

The present study was conducted to determine the efficacy of Terminalia arjuna bark extracts against Salmonella sp. isolated from 15 aquaculture ponds located adjacent to Bangladesh Agricultural University, Mymensingh. T. arjuna barks was dried, powdered and extracted using cold water (polar) and hexane (non-polar) and stored at 10ºC while Salmonella sp. were isolated using SS (Salmonella Shigella) Agar and selected 2 isolates were confirmed by Hi Assorted biochemical test kit. Antimicrobial activities of the bark extract of T. arjuna against fifteen selected isolates of Salmonella were then determined. Two of those selected isolates (Sa-2 and Sa-5) shown zone of inhibition against crude bark extract (hexane extract) of T. arjuna. The isolates were also screened for antibiotic resistance to eleven antibiotics. Salmonella isolates were serotyped and the antimicrobial resistance was determined by a disk diffusion method. About 100% of the isolates were resistant to antibiotic discs among which ampicillin (10 μg), and chloramphenicol (30 μg) showed 15%, azithromycin (10 μg) showed 45%, erythromycin (15 μg) showed 60%, tetracycline (10 μg) showed 40%, ampicillin (10 μg) showed 100%, doxycycline (30 μg) showed 46.67%, kanamycin (30 μg) and gentamycin (10 μg) showed 6%, streptomycin (25 μg) and ciprofloxacin (10 μg) showed 20%, and cefotaxime (30 μg) showed 30% resistant to isolated Salmonella sp. and all Salmonella sp. isolates were found to be 100% resistant to cold water extract but sensitive to hexane extract of T. arjuna. The study showed hexane extract of T. arjuna would be potential, ecofriendly and biodegradable herbal medicine to control multi drug resistant Salmonella sp. as well as aquaculture health management. Res. Agric. Livest. Fish. Vol. 11, No. 2, August 2024: 255-269

Occurrence and risk assessment of quinolones and sulfonamides in freshwater aquaculture ponds in Northeast Zhejiang, China

Antibiotics play an essential role in the aquaculture industry, but their overuse and weak degradability inevitably lead to light to severe residues in natural and aquaculture environments. Most studies were interested in the occurrence, distribution, and ecological risks of a limited number of antibiotics in natural environments (rivers, lakes, and coastal regions) with a minor focus on antibiotic presence in either water, sediments, or organisms in aquaculture environments located in specific regions. In this study, we conducted a comprehensive investigation into the occurrence and distribution of up to 32 antibiotics [including 15 quinolones (QNs) and 17 sulfonamides (SAs)] in organisms and their corresponding environmental matrices from 26 freshwater aquaculture ponds in Northeast Zhejiang, China. A total of 13, 9, 7, and 7 antibiotics were detected in pond water, sediments, feeds, and aquaculture organisms, respectively, with concentration ranges of 0.6–92.2 ng/L, 0.4–1169.3 ng/g dw, <LOD–17.5 ng/g dw, and < LOD–234.3 ng/g ww, respectively, where enrofloxacin (ENR) was the main component in different matrix samples, with a proportion range of 51 %–88 %. There were differences in the predominant antibiotic and concentration abundance among fishponds, shrimp ponds, crab ponds, and turtle ponds. Feed was likely one of the most essential source of antibiotics in freshwater aquaculture ponds. The risk quotient (RQ) results revealed that ciprofloxacin (CIP) and ENR showed high risks to algae in water at the maximum measured concentrations and norfloxacin (NOR), CIP, ENR, and ofloxacin (OFL) exhibited high risks in sediments. However, the joint probability curve (JPC) showed acceptable risk in water. On the basis of the calculated hazard quotients (HQ < 1), the risk of human antibiotic ingestion through aquaculture organisms was acceptable. These results suggest that the rational control of antibiotic use is necessary for human health and ecological security.