Fish Farming Water Research Articles

Endoparasite infestation of red hybrid tilapia (Oreochromis sp.) in relation to water quality and fish farm types

Endoparasite infestation of red hybrid tilapia (Oreochromis sp.) in relation to water quality and fish farm types

Preference for water sources and agricultural utilisation among rural households: a case of Akoko district of Ondo State, Nigeria

The increasing challenge of freshwater scarcity amid rising demand and diminishing availability has led to a critical issue threatening sustainable development, especially in rural areas of developing countries like Nigeria. Despite the abundance of studies on rural water use, gaps remain in understanding the interplay between socio-economic factors, and agricultural practices in shaping these preferences and utilisation. Thus, the study investigates the preference for water sources and their utilisation in agricultural activities among rural households in the Akoko district of Ondo State, Nigeria. Cross-sectional data from randomly sampled 240 rural households were collected with the aid of a questionnaire, and employed for the data analysis. Descriptive statistics, logit, and multinomial regressions were used for the data analysis. The findings revealed a dominant preference for rainwater and well water. Factors such as access to safe water sources, time spent, extension service, technology adoption, soil type, experience, and proximity to water sources significantly influence the choice of water source utilization in the area using multinomial logit regression. Again, the results from logit regression revealed that water source, technology adoption, soil type, fish farming, crop farming, farming experience, and distance to water sources significantly affect the use of water for agricultural purposes. Therefore, the policy should enhance water access, consider soil characteristics in agricultural planning, and facilitate knowledge transfer among farmers for optimal water use, recognizing the symbiotic relationship between water access and agricultural sustainability.

Study of nitrogen and phosphorus nutrient dynamics in concentrated marine fish farming water environment in Long Son - Vung Tau

The nutritional content of N and P in concentrated marine fish farming water in the Cha Va - Long Son - Vung Tau estuary area increased sharply during 2013–2016; notably, the N-NH4+ content increased in 2017–2019. The N-NO2- and N-NO3- content in the dry season (0.051 mg/L and 0.190 mg/L) was higher than in the rainy season (0.044 mg/L and 0.133 mg/L). In contrast, the N-NH4+ and P-PO43- contents in the rainy season (0.321 mg/L and 0.1 mg/L) are higher than in the dry season (0.154 mg/L and 0.093 mg/L). The N and P nutrient dynamics in water fluctuate according to the semi-diurnal tide regime; the nutrient content decreases during high water - daytime, increases during low water in the evening, and is high during high water at night and in the morning, early the next day. In dry and rainy seasons, the N-NH4+ content is always the highest (0.024–0.761 mg/L) among the nitrogen-based nutritional parameters. N and P nutrients in water are correlated: N-NH4+ parameter pairs with Total P, N-NO2- with Total P, Total N with Total P, N-NO2- and N-NO3-, P-PO43- with Total P, and the parameter pair N-NO2- with P-PO43- have low positive correlation coefficients (r), from 0.1–0.21. Conversely, the parameter pairs N-NO3- and Total N, N-NO3- and N-NH4+, and N-NO2- and N-NH4+ have low negative correlation coefficients (r), from -0.12 to -0.26. From 2010–2021, the number of cages increased beyond planning, causing environmental pollution in the water in the farming area. The nutritional RQ value of the water is high at level 4 every year (very high risk of environmental pollution).

Mapping the Future: Revealing Habitat Preferences and Patterns of the Endangered Chilean Dolphin in Seno Skyring, Patagonia.

Species distribution modeling helps understand how environmental factors influence species distribution, creating profiles to predict presence in unexplored areas and assess ecological impacts. This study examined the habitat use and population ecology of the Chilean dolphin in Seno Skyring, Chilean Patagonia. We used three models-random forest (RF), generalized linear model (GLM), and artificial neural network (ANN)-to predict dolphin distribution based on environmental and biotic data like water temperature, salinity, and fish farm density. Our research has determined that the RF model is the most precise tool for predicting the habitat preferences of Chilean dolphins. The results indicate that these dolphins are primarily located within six kilometers of the coast, strongly correlating with areas featuring numerous fish farms, sheltered waters close to the shore with river inputs, and shallow productive zones. This suggests a potential association between dolphin presence and fish-farming activities. These findings can guide targeted conservation measures, such as regulating fish-farming practices and protecting vital coastal areas to improve the survival prospects of the Chilean dolphin. Given the extensive fish-farming industry in Chile, this research highlights the need for greater knowledge and comprehensive conservation efforts to ensure the species' long-term survival. By understanding and mitigating the impacts of fish farming and other human activities, we can better protect the habitat and well-being of Chilean dolphins.

Impact of Salinity on Growth and Physiological Responses of Striped Catfish Pangasionodon hypophthalmus Fingerling

Background: A 90-day experiment was conducted to study the impact of salinity on growth and physiological response of Pangasionodon hypophthalmus fingerling at the Brackish water fish farm of Central Institute of Fisheries Education (CIFE), Kakinada Centre, Kakinada, East Godavari District, Andhra Pradesh, India. Method: The study used different salinities condition such as 0 (control), 5 (T1), 10 (T2) and 15 (T3) ppt. Fingerlings (8.47±0.46 g) were gradually acclimatized to different salinities in 1000 l fibre reinforced plastic (FRP) tanks, in triplicates and fed with a commercial feed (crude protein 30%). Result: Growth indicators such as specific growth rate (SGR), feed conversion ratio (FCR), feed efficiency ratio (FRR) and protein efficiency ratio (PER) revealed that growth and survival were negatively affected above 10 ppt salinity. Significantly higher amylase and protease activities were observed up to 10 ppt group. In contrast, significantly higher cortisol (97.71±1.94 ng/ml) and glucose (113.32±2.66 mg/dl) levels in the blood were recorded in 15 ppt group. Overall, the study proved that P. hypophthalmus can be cultured in low saline water (up to 10 ppt) without affecting its growth and physiological homeostasis.

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditional fish farming methods incur enormous economic costs owing to labor-intensive schedule monitoring and care, illnesses, and sudden fish deaths. Another ongoing issue is automated fish species recommendation based on water quality. On the one hand, the effective monitoring of abrupt changes in water quality may minimize the daily operating costs and boost fish productivity, while an accurate automatic fish recommender may aid the farmer in selecting profitable fish species for farming. In this paper, we present AquaBot, an IoT-based system that can automatically collect, monitor, and evaluate the water quality and recommend appropriate fish to farm depending on the values of various water quality indicators. A mobile robot has been designed to collect parameter values such as the pH, temperature, and turbidity from all around the pond. To facilitate monitoring, we have developed web and mobile interfaces. For the analysis and recommendation of suitable fish based on water quality, we have trained and tested several ML algorithms, such as the proposed custom ensemble model, random forest (RF), support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), logistic regression (LR), bagging, boosting, and stacking, on a real-time pond water dataset. The dataset has been preprocessed with feature scaling and dataset balancing. We have evaluated the algorithms based on several performance metrics. In our experiment, our proposed ensemble model has delivered the best result, with 94% accuracy, 94% precision, 94% recall, a 94% F1-score, 93% MCC, and the best AUC score for multi-class classification. Finally, we have deployed the best-performing model in a web interface to provide cultivators with recommendations for suitable fish farming. Our proposed system is projected to not only boost production and save money but also reduce the time and intensity of the producer's manual labor.

Study of Parasitary Fauna in Tilapia of Fish Cultures in the Distrito Federal

Objective: This article discusses the parasitic fauna found in tilapia, the most produced in the DF, collected in fish farms and presents an analysis of water quality, a relative condition factor and the influence of seasonality on the average abundance of parasites. Methodology: For each acquisition campaign, ten fish were collected from each visited fish farm, totaling 180 sampled fish. The fish were collected by fishing nets with mesh 14 and transported in thermal boxes, with each specimen properly packed in a plastic bag, to ensure protection during transport to the Aquaculture Laboratory of the University of Brasília (AcquaUnB). Results and Conclusion: In the two acquisition campaigns, parasitism by Trichodina sp., Monogenoids, Ichthyophthirius multifiliis and Apiosoma sp. Infestations by Trichodina sp. presented higher prevalence and average intensity than other parasites in general, followed by infections by Monogenoides, Ichthyophthirius multifiliis and Apiosoma sp, respectively. The average abundance of Trichodina sp., monogenenoids, Ichthyophthirius multifiliis and Apiosoma sp. showed a positive correlation with temperature and the concentration of ammonium and phosphate in fish farm water. On the other hand, the average abundance of parasites showed a negative correlation with the levels of dissolved oxygen and nitrate concentration. The ectoparasites found do not directly affect human health. There was a significant difference between the average abundance of parasites found in fish collected in the months of February and August, so that the highest parasitic rates were observed in February, when there is greater rainfall in the Federal District and when the values of water parameters were findings. less suitable.

Improving the water quality of fish aquaculture effluents after treatment by microalgae

Water improvements in aquaculture are among the critical solutions to remove ammonia resulting from biological processes. In this study, t algae Chlorella vulgaris was used to remove ammonia from the fish farm water of catfish Clarias garepienus. Ammonia chloride was used with algae to study the response by algae to the removal rates of ammonia and the best concentration of alga. The concentration and time rates were then used in the aquaculture, in addition to measuring the water's improvement rate again. The results revealed that the improvement and treatment of variable ammonia concentration (NH4+) by using a volume of algae C. vulgaris (350 ml) recorded the highest percentage (75%) at ammonia concentration (10 mg L−1). Approximately 60% of ammonia were removed (30 mg L−1). When applied to the water fish farms for 24 and 48 h, the ammonia concentration (NH4 +) was markedly decreased from 10 mg L−1 to 3.7 mg L−1 (63%) and 2.3 mg L−1 (77%) after 24 h and 48 h, respectively. Through applied on the fish pond, noted reduced the water used by 60% compared to the control pond. It was observed that most of the items positively influenced by algae were mainly implemented, including ammonia and other elements. This implementation is recommended in intensive aquaculture to improve the water quality and reduce the operating costs in water usage and expected wast water recycling towards achieving progress and sustainable development.

XANTHOPHYLL CONCENTRATION IN LYMNAEA STAGNALIS CAUSED BY CHROMIUM IONS

Currently the pollution of natural waters by heavy metal ions is a particularly serious problem which results in the disruption of the balance of food chains and the overall ecosystem balance. In this regard the study of the reaction of the biotic components of the hydroecosystem to toxic effects is relevant, and will allow to expand the understanding of the adaptive mechanisms of aquatic organisms and to determine sensitive test objects and test functions for assessing the degree of pollution of natural waters.
 The influence of chromium ions (Cr3+ and Cr2O72-) in concentrations corresponding to 0.5 and 2 TLV in fish farming water basins was studied based on the concentration of xanthophylls in hemolymph, hepatopancreas, mantle and leg of Lymnaea stagnalis, which is a permanent component of most hydrobiocenoses of Zhytomyr Polissia. The dynamics of the discussed carotenoids at different durations of exposure (2, 7, 14 and 21 days) of the studied shellfish in a toxic environment were observed.
 It was found that 48-hour exposure of shellfish in solutions of chromium ions (Cr3+ and Cr2O72- ) regardless of their concentration (0.5 and 2 TLV) causes 2.45–3.23 times increase of xanthophylls in all the studied organs and tissues of L. stagnalis (p ≤ 0.001) which indicates the development of an immediate reaction of animals to toxic elements. Further prolongation of exposure to chromium ions (7, 14, and 21 days) resulted in non-linear organ-dependent dynamics of the xanthophyll content which is related to the specificity of the action of ions, the duration of exposure of animals to toxic solutions, and the metabolic features of the studied organs and tissues. It is shown that the content of xanthophylls in the body of L. stagnalis is characterized by tissue-organ specificity. The minimum amounts of the discussed carotenoid were recorded in the hemolymph of animals and the maximum values varied significantly between the studied components depending on the experimental conditions.

Physicochemical and Organoleptic Analysis of Tomato Irrigated with fish farms water; at URERMS-ADRAR. Algeria

The objective of the developed system is to encourage efficient water management practices that optimize the usage of water by keeping crop health and yield intact through the implementation of an automated irrigation system. The study aimed to determine the impact of irrigation by fish farming on growth rates and concentrations of macro- and micronutrients in tomatoes. Results indicated that irrigation with fish farm effluent significantly increased and effluent water, depending on its composition to feed the fish, can supply nutrients and increase the concentrations of these elements in tomatoes irrigated with this water with a refractive index = 1.3391 and a calorie value of 19.927 Calorie in the first sampling and 16.696 calories in the second sampling for 100 g for the year 2021 and for the year 2022 we have a refractive index = 1.3495 and a calorie value of 20.66 Calorie for 100 g. Here we show for the first time that is more than the standard norm (Cotte.2000) which is 18 Calories. Also, after carrying out microbiological analyzes, there is a total absence of pathogenic bacteria, as well as the organoleptic parameters are heading in the right direction where tomatoes irrigated by fish farming water is concentrated compared to the tomatoes irrigated by normal fresh water with Light red of 53 %, Cooked acid of 47 %, spherical form of 94 % and a pleasant smell of 88 %. Therefore, using fish farm effluent in irrigation provides water requirements for plants and also can improve the availability of nutrient elements for tomatoes.

Heavy Metal Levels and Cancer Risk Assessments of the Commercial Denis, Sparus aurata Collected from Bardawil Lake and Private Fish Farm Waters as a Cultured Source, Egypt

Heavy metal pollution of natural and cultivated habitats may be caused by agricultural, industrial, and human activities. Fish living in these habitats easily accumulate metals in their organs; for food safety and human health, the heavy metals in fish flesh are of major concern due to the harmful nature of these pollutants even in low quantities. In this study, metals (Iron, Fe; Lead, Pb; Cadmium, Cd; Nickel, Ni; Copper, Cu and Zinc, Zn) in the muscle, liver, intestine, and gill of gilthead seabream (Sparus aurata, Denis is local name) were monitored to determine the contamination levels and to investigate the protective impact of cooking methods on the reduction or mitigation of metal levels. Although the Denis samples exhibited relatively low Pb and Cd levels, most fish samples had elevated levels of Fe and Zn. The examined metals accumulated at the highest level in the liver and gills compared to the other organs. Results showed that cooking methods had a considerable effect on concentrations of metals. However, the levels of metal in S. aurata from various sources were reduced significantly (P < 0.05) by frying, microwave, and grilling cooking, which was ordered in the following sequence as microwave cooking < grilling < frying. The consumption of Denis fish from different sources (wild and cultured) has no negative effects on health, according to a study of health hazards based on indices of carcinogenic and non-carcinogenic. The metal results indicated that different fish sources (wild and cultured) could be acceptable for human consumption. Data hypothesized a positive impact of awareness among the native community.

Monitoring of Mycotoxigenic Fungi in Fish Farm Water and Fumonisins in Feeds for Farmed Colossoma macropomum.

This study aimed to evaluate the occurrence of mycotoxigenic fungi in fish farm water and mycotoxins in feeds for farmed tambaqui (Colossoma macropomum). A total of 40 samples of freshwater from fish farms and 16 samples of feed were collected and analyzed for microbiology. A total of five species of free-living fungi were identified in fish farms: Aspergillus fumigatus, Penicillium citrinum, P. implicatum, Fusarium oxysporum and Alternaria alternata. These fungi species were counted in water samples at 35.14 CFU mL-1 and 24.69 CFU mL-1 in the dry seasons. In all fish farms, there was a higher abundance of fungi species in the rainy season. During visits to the fish farmers, it was possible to verify poor feed storage conditions. Concerning mutations in blood cells, in tambaqui (C. macropomum), a total of 159 anomalies were found, and in Leptodactylus petersii, 299 anomalies were found, with higher incidences in conditions above 1.0 CFU mL-1 in log10(x+1) fungi and in the rainy season. The occurrence of mycotoxicological contamination was confirmed in 81.25% of the analyzed samples. The quantified mycotoxin was Fumonisins B1 + B2 (375 to 1418 μg kg-1). Pearson's correlation analysis showed a significant positive correlation between Fumonisins and feed samples (r = 0.83). There was also a significant positive correlation between the abundance of fungi in water and the quantification of Fumonisins (r = 0.79). Based on the results obtained, it can be concluded that free-living fungi can be used as bioindicators of water quality in fish farms. Consequently, the lack of good management practices caused microbiological contamination of the aquatic environment.

Influences of chronic copper exposure on intestinal histology, antioxidative and immune status, and transcriptomic response in freshwater grouper (Acrossocheilus fasciatus).

Copper (Cu) contamination is commonly found in both natural water environments and fish farms, and it can cause severe damage to different fish organs, but Cu-induced intestinal damage has been rarely studied. This study subjected three groups of freshwater grouper (Acrossocheilus fasciatus) (initial weight: 1.56±0.10g) to 0mg/L, 0.01mg/L, and 0.04mg/L Cu2+ for 30 days, named Con, Cu0.01, and Cu0.04 groups, respectively. The histological observation indicated that the Cu0.04 group caused a significant decrease in villus length, lamina propria width, and muscular thickness compared to the Con group (P<0.05). Additionally, the Cu0.04 group significantly increased intestinal superoxide dismutase (SOD), glutathione peroxidase (GPx), lysozyme (LZM) activities, as well as malondialdehyde (MDA) content than the Con group (P<0.05). Meanwhile, the Cu0.01 and Cu0.04 groups showed significantly increased immunoglobulin M (IgM), complement 3 (C3), and glutathione (GSH) contents than the Con group (P<0.05). Transcriptomic analysis revealed a total of 101 differentially expressed genes (DEGs), including 47 up-regulated and 54 down-regulated DEGs, were identified between the Cu0.04 and Con groups. Notably, the DEGs were mainly related to intestinal structure construction, immune functions, apoptosis, and resistance to DNA damage and pathogen infection. The findings suggest that chronic Cu exposure caused intestinal histological alterations, activated the antioxidative and immune systems, and induced systematic adaptation to cope with the physical barrier injury, DNA damage, and potential pathogen growth.

Ultrasound assisted based solid phase extraction for the preconcentration and spectrophotometric determination of malachite green and methylene blue in water samples

In this study, magnetic ferrite nanoparticles CoFe2O4 were synthesized by combustion method. Magnetic solid phase extraction was carried out by ultrasonic assisted (UAMSPE) followed by UV/Vis spectrophotometer (UAMSPE-UV/Vis) to extract malachite green (MG) and methylene blue (MB) from water samples. To investigate the effects of adsorbent dosage, solution pH, ultrasonication time and volume of eluent solvent parameters on the extraction of MG and MB by CoFe2O4, the extraction experiments through the response surface methodology (RSM) were mathematically modeled and described as parameter performance. The results of extraction tests under optimal conditions showed that CoFe2O4 had a high extraction percentage. In optimal conditions, linear range of 70–550 ng mL−1 (R2 = 0.9977) and 40–450 ng mL−1 (R2 = 0.9983) were observed for MG and MB, respectively. Limit of detection (LOD) for MG and MB were 16.5 ng mL−1 and 11 ng mL−1, respectively. Relative standard deviation (RSD) was obtained in good and low values of 2.9% and 2.3% was achieved for MG and MB, respectively. The results of investigating the reusability of CoFe2O4 adsorbent showed that the adsorbent can be used for up to 5 absorption and desorption cycles. Also, the developed method was finally used successfully in determining MG and MB in fish, fish farming water, tap water and wastewater samples with recoveries ranged in 96.46–99.82%.

Growth Performance and Survival of Climbing Perch (Anabas testudineus Bloch) Raised in Conventional and Bioflocs System

The aim of this research is to analyze the performance of growth and survival of climbing perch (Anabas testudineus Bloch) which was raised in bioflocs and conventional systems. It investigated the difference in the initial size of the fry stocked with climbing perch has effect. The experimental design used in this study was a Factorial Completely Randomized Design (CRD) with 2 factors and 3 replications: Factor A: climbing perch aquaculture Systems; A1: climbing perch in conventional system of; A2: the climbing perch in bioflocs system; Factor B: Initial Size of fry Stocking; B1: fry size 3 ± 0.5cm; B2: fry size 5 ± 0.5cm and B3: fry size 7 ± 0.5cm. The research was conducted for 90 days with daily growth parameters (SGR), weight and length growth, survival rate, food conversion, flocsvolume density (FVD), and main water quality parameters (water temperature, pH, dissolved oxygen and dissolved ammonia).The results showed that the bioflocs system was able to increase the average growth in the range of 12-67% with an average of 29.73% when compared to conventional systems. The highest value for the daily growth rate or Specific Growth Rate (%/day) was for fry with a size of 7 cm in the bioflocs system (8,419%). The fry size of 3 ± 0.5cm in the bioflocs system had the highest difference in standard length (4.33 cm) while the highest average length during maintenance was the seed size of 7 ± 0.5 cm in the bioflocs system. The survival results of climbing perch fish during the study were based on the highest score on the seed size of 3 ± 0.5cm in the bioflocs system. The survival range of the bioflocs system is 94.89 - 99.67% and that of the conventional system is 82.00 - 94.26%. Thus the bioflocs system is able to increase survival in the range of 5-14% when compared to conventional systems. The bioflocs system is able to provide better feed efficiency than conventional systems in the range of 34-39%. The average value of floc volume density (FVD) in the bioflocs system is in the range of 5.35 – 8.16 ml/L, which is still ideal but can still be improved. Water temperature during the study period, air and water temperatures ranged from 28.54 to 28.71 (ºC), the degree of acidity in all treatments was in the range 6.34 – 7.27, dissolved oxygen levels were in the range 5.77 – 6.90 mg /L) while the average measurement results for ammonia levels (mg/L) were in the range of 0.49 – 0.57 mg/L. The temperature ranges in the studies on conventional and bioflocs systems are within the acceptable range for fish farming Water temperature during the study period, air and water temperatures ranged from 28.54 to 28.71 (ºC), the degree of acidity in all treatments was in the range 6.34 – 7.27, dissolved oxygen levels were in the range 5.77 – 6.90 mg /L) while the average measurement results for ammonia levels (mg/L) were in the range of 0.49 – 0.57 mg/L.

Water quality image classification for aquaculture using deep transfer learning

With the development of high-density and intensive aquaculture production and the increasing frequency of water quality changes in aquaculture water bodies, the number of pollution sources in aquaculture ponds is also increasing. As the water quality of aquaculture ponds is a crucial factor affecting the production and quality of pond aquaculture products, water quality assessment and management are more important than in the past. Water quality analysis is a crucial way to evaluate the water quality of fish farming water bodies. Traditional water quality analysis is usually obtained by practitioners through experience and visual observation. There is an observability deviation caused by subjectivity. Deep transfer learning-based water quality monitoring system is easier to deploy and can avoid unnecessary duplication of efforts to save costs for aquaculture industry. This paper uses the transfer learning model of artificial intelligence to analyze the water color image automatically. 5203 water quality images are collected to create a water quality image dataset, which contains five classes based on water color. Based on the dataset, a deep transfer learning-based classification model is proposed to identify water quality images. The experimental results show that the deep learning model based on transfer learning achieves 99% accuracy and has excellent performance.

Antibiotic resistant bacteria in diverse ecological water samples are a threat to Human Food security

Antibiotic resistance is increasing with every passing day globally and it has become common not only in clinical settings but also in different environments. Aquatic systems are major reservoirs of antibiotic resistance genes in the environment. In this study, we have isolated the antibiotic resistance bacteria from aquatic systems including river Ravi, fish farm and underground drinking water source. Physical, chemical and microbiological parameters were studied, bacteria were isolated, gram staining and genus identification was done by following the Burgey’s manual of systematic bacteriology. While, antibiotic susceptibility testing was done by following the disk diffusion method and CLSI guidelines. Multiple antibiotic resistant indexes were calculated. There was no significant discrepancy in physical and chemical parameters of water samples whereas in microbiological parameters, a variable number of bacteria were found in all 3 water samples indicating the presence of microbial contamination. A total of 33 bacterial strains were identified including Enterobacteriaceae, Pseudomonas, Bacillus, Lactobacillus and Staphylococcus species. Out of 10 classes of antibiotics, resistant against 8 classes were identified. Organisms isolated from river Ravi were the most resistant isolates. Most of the organisms were resistant to Penicillins, Carbapenems and Cephalosporins. MAR index of isolated strains ranges from 0.43 to 0.88. AMR is common in all environmental water samples indicating a threat to human food safety

IoT-Based Fish Farm Water Quality Monitoring System.

Typhoons in summer and cold snaps during winter in Taiwan often cause huge aquaculture losses. Simultaneously, the lack of human resources is a problem. Therefore, we used wireless transmission technology with various sensors to transmit the temperature, pH value, dissolved oxygen, water level, and life expectancy of the sensor in the fish farm to the server. The integrated data are transmitted to mobile devices through the Internet of Things, enabling administrators to monitor the water quality in a fish farm through mobile devices. Because the current pH sensors cannot be submerged in the liquid for a long time for measurements, human resources and time are required to take the instrument to each fish farm for testing at a fixed time. Therefore, a robotic arm was developed to complete automatic measurement and maintenance actions. We designed this arm with a programmable logic controller, a single chip combined with a wireless transmission module, and an embedded system. This system is divided into control, measurement, server, and mobility. The intelligent measurement equipment designed in this study can work 24 h per day, which effectively reduces the losses caused by personnel, material resources, and data errors.

Embedded system in handheld water turbidity meter for smallholders

The periodical assessment of water quality in response to increased pollution has become increasingly crucial. Water turbidity, which indicates the growth of pathogenic microorganisms in water, is a well-known water quality indicator. In fish farming, water turbidity affects fish health. Commercially available tools for estimating water turbidity are expensive, which is an obstacle for small-scale farmers. In this study, a low-cost (<20 USD) embedded meter that allows near real-time assessment of water turbidity was developed. The developed tool was integrated into an Android-based mobile application and comprised a turbidity sensor, RGB sensor, LED as the light source, and electronic components. Light source uniformity is essential for obtaining reliable measurement results and instrument replication. Uniformity is performed by calculating the luminance index from the RGB sensor value and then determining the light intensity. Moreover, two developed tools were tested by comparing their results against those of a commercial turbidimeter (Eutech TN-100). The comparison indicated a strong coefficient of determination (0.96 and 0.98), with root-mean-square error (RMSE) values of 30.48 and 22.08, in the turbidity evaluation range of 300–500 NTU. However, upon measuring samples with turbidity levels of 0–300 NTU, the developed tools showed better performance based on the RMSE results of 20.63 and 11.87. Thus, the developed meter is proven useful for smallholders to manage water resources and fish farming activities.

Investigation of Some Biochemical Parameters and Mineral Values in the Blood of Rainbow trout Growing in Dam and Sea water

In this study, it was aimed to investigate the effect of the difference in the breeding environment (pH, temperature, salinity, oxygen content and saturation) of rainbow trout grown in dam and sea water on the level of some minerals (calcium, magnesium, zinc, iron) and biochemical parameters in the serum. The study material consisted of 20 rainbow trout (Oncorhynchus mykiss) weighing about 800-1000 gr in the dam water of Samsun (Derbent Dam) and the Black Sea water (Yakakent). Blood samples were taken from both groups on the same day in December and the pH, temperature, oxygen content and saturation level of the water were determined by YSK oxygen meter, and salinity was determined by refractometry. Total protein (TP), albumin (Alb), cholesterol (TK), glucose (Glu), urea, creatinine (Cre), uric acid (UA), Aspartate transaminase (AST), Alanine Aminotransferase (ALT), triglyceride (TG) Calcium, magnesium, iron and zinc and ALT, AST enzyme activities were determined by spectrophotometric method in an autoanalyzer. It was observed that the salinity, oxygen and saturation levels of the sea water were higher than those of the dam water, and the pH and temperature were close to each other. It was determined that TP, Alb, Alb/Glo, TK, TG, UA and Ca levels in rainbow trout raised in the dam were significantly higher than those raised in the sea (P&amp;lt;0.05). Glu, Cre, Mg and Fe levels were found to be higher in the blood serum of rainbow trout (P&amp;lt;0.05). Zn, urea, AST and ALT levels of rainbow trout raised in sea and dam were similar. In our study where the same fish species were provided with the same feeding conditions, it was observed that the differences in salinity and dissolved oxygen levels of fish farming waters caused changes in some mineral and blood parameter levels in fish. It was concluded that determining the supplementation of the missing minerals in fish according to the salinity and dissolved oxygen level in the environment may be important for the development of the fish.