Water Quality In Farms Research Articles

Assessment of Animal Drinking Water Quality in Livestock Farms in Galapagos Islands

The purpose of this research was to determine the quality of water for bovine consumption on livestock farms in the El Progreso parish - Galapagos by applying a quality index following the Brown methodology proposed by the National Sanitation Foundation of the United States. Information was collected from the livestock farms through a socio-environmental diagnosis of the area, where five localities were considered: San Joaquín, Las Goteras, Cerro Verde, Puerto Chino and El Progreso from which fifteen livestock farms were selected for the respective sampling of the sources. of water. Therefore, nine parameters were considered for the analysis of the respective water sources: pH, TDS, Fecal Coliforms, electrical conductivity, hardness, nitrites, phosphates, temperature and turbidity. Of the total livestock farms monitored, three of them presented a rating of Good quality in a range of 70 to 90, while the remaining farms recorded values with a Medium classification, which are those that recorded AQI values between 51 to 70 according to the criteria established by the NSF. This research highlights the importance of frequently carrying out analyzes of the water sources from which cattle drink to determine the quality of the resource, and also provide technical advice to ranchers in the area on the management and cleaning of the reservoirs.

Long-term analysis of drinking water quality in poultry and pig farms in Northwest Germany

Hygienically safe drinking water is essential for the health, well-being, and efficient production of livestock. In contrast to drinking water for human consumption, there are guidelines but no legal limits for drinking water for animals. Risk factors due to hygienically relevant microorganisms or chemical compounds in drinking water are known from literature, but there is little information on the quality of drinking water for livestock in Germany. To gain an overview of the quality of drinking water, data from samples collected from pig and poultry farms in Northwest Germany over a 10-year period were analyzed retrospectively. Data consisted of 326 samples analyzed chemically, and 519 samples analyzed microbiologically. Of these, 80 water samples were analyzed for both chemical and microbial contaminants. There was no correlation between samples exceeding chemical and microbial guideline levels. The number of samples exceeding the chemical guideline values (58.0%) was higher than the number of samples exceeding the microbiological guideline values (47.4%). This long-term study illustrated the potential risk to pigs and poultry from drinking water and highlights the need for effective hygiene measures to prevent the transmission of microorganisms and chemicals residues through water to maintain animal health and safe food products.

Hybrid Power Source in Fish Farming With Help of IoT Technology

Fish farming is a difficult, task that involves growing fish without risk. Maintaining the pond's water quality allows for safe fish production. This will go over the creation of a real-time water quality system to monitor fish farms. The water quality monitoring system includes a dissolved oxygen sensor, a pH sensor, and a water temperature sensor. The Arduino Nano microcontroller is linked with the Internet of Things (IoT) platform to provide real-time remote water monitoring. The system is intended to efficiently monitor water quality in freshwater fish farms, specifically water parameters suitable for fish. Instead of testing the system in the real fish farm, it is tested using water that is simulated to the water quality for the fish farm. If the water was above and below the fixed parameter it gives us an alert and water exchange mechanism get started by remove the dirty water from the pond through the solenoid valve and provide the fresh water into the pond. By measuring the dissolved oxygen level if is any deviation occurs water circulation mechanism should be established and circulate the water for increasing the oxygen level by using the padding wheel which all these done automatically. It also done the automatic food feeding at the periodic interval time without the manual involvement sometimes it may cause a manual error such as underfeeding and overfeeding which may affect the fish health to reduce such stuffs we use this automatic food feeding system. Keywords: Fish farming; IoT; Solar energy; Solar PV.

Optimizing Predictive Modeling for Water Quality in Farms with Blended Artificial Neural Network

Optimizing Predictive Modeling for Water Quality in Farms with Blended Artificial Neural Network

Assessing the effect of β-glucan diets on innate immune response of tilapia macrophages against trichlorfon exposure: an in vitro study

The widespread use of pesticides in some areas where fish species such as tilapia are farmed may cause damage to the environment and affect commercial fish and therefore, human health. Water leaching with the pesticide trichlorfon, during the fumigation season in the field, can affect water quality in fish farms and consequently affect fish health. At the same time, the use of immunomodulatory compounds such as β-glucan supplied in the diet has become widespread in fish farms as it has been shown that improves the overall immune response. The present research examines the immunomodulatory impacts observed in macrophages of Nile tilapia (Oreochromis niloticus) after being fed a diet supplemented with β-glucan for 15 days, followed by their in vitro exposure to trichlorfon, an organophosphate pesticide, at concentrations of 100 and 500 µg mL−1 for 24 h. The results showed that β-glucan diet improved the viability of cells exposed to trichlorfon and their antioxidant capacity. However, β-glucan did not counteract the effects of the pesticide as for the ability to protect against bacterial infection. From the present results, it can be concluded that β-glucan feeding exerted a protective role against oxidative damage in cells, but it was not enough to reduce the deleterious effects of trichlorfon on the microbicidal capacity of macrophages exposed to this pesticide.

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.

An IoT framework for quality analysis of aquatic water data using time-series convolutional neural network.

Water quality monitoring and analysis in fish farms are of paramount importance for the aquaculture sector; however, traditional methods can pose difficulties. To address this challenge, this study proposes an IoT-based deep learning model using a time-series convolution neural network (TMS-CNN) for monitoring and analyzing water quality in fish farms. The proposed TMS-CNN model can handle spatial-temporal data effectively by considering temporal and spatial dependencies between data points, which allows it to capture patterns and trends that would not be possible with traditional models. The model calculates the water quality index (WQI) using correlation analysis and assigns class labels to the data based on the WQI. Then, the TMS-CNN model analyzed the time-series data. It produces high accuracy of 96.2% in analysis of water quality parameters for fish growth and mortality conditions. The proposed model accuracy is higher than the current best model MANN, which has only had an accuracy of 91%.

An ecological economic comparison between integrated rice-fish farming and rice monocultures with low and high dikes in the Mekong Delta, Vietnam.

This study makes an ecological economic comparison between three different rice farming strategies in the Mekong Delta. Interviews were made with 30 farmers with two crops of rice and low dikes (2RLd), 30 farmers with three crops of rice and high dikes (3RHd) and 18 farmers with two crops of rice and one crop of fish (2RF). 2RF farmers had the highest annual net income and benefit cost ratio, because oflow production costs and high yields of rice and fish. 2RLd farmers had the lowest annual net income. 3RHd had the highest annual rice yield, but also used the highest amount of rice seeds and agrochemicals, generating the lowest benefit cost ratio. Most farmers (70%) preferred two crops because of a higher production efficiency. High dikes and frequent use of pesticidesand fertilizers were seen to decrease the water and rice quality, connectivity and biodiversity in farms with three crops. It is concluded that rice farming with two crops, and especially if integrated with fish and applying IPM, provides a sustainable alternative to rice farming with three crops and high dikes, because it makes use of the high connectivity within the rice-field ecosystem for an efficient production of healthy food through increasedrecycling of nutrients and natural pest control mechanisms.

Implications of irrigation water quality in tropical farms

BACKGROUND AND OBJECTIVES: Irrigation system water quality is a complex issue that involves the combined effects of various surface water management parameters. Monitoring of irrigation water quality is essential for the sustainability of crop production and productivity. The department of Sucre, in northern Colombia, is predominantly a ranching and agricultural region where agriculture is the main source for livelihoods. The purpose of this study was to assess the physicochemical quality of surface water in irrigation systems at 141 farms.METHODS: To this end, 141 water samples were taken to determine 22 physicochemical parameters. All in-situ measurements and laboratory analysis were performed using standard methods. The results obtained were compared with the international standards proposed by the United Nations’ Food and Agriculture Organization and the World Health Organization. Salinity and sodicity were measured using the irrigation water classification diagram, and the level of correlation between the 22 variables was assessed by means of correlation analysis.FINDINGS: The results obtained indicate that based on the measured parameters, the water is classified as appropriate for use in irrigation systems. The maximum and minimum pH values were 9.32 and 4.40, respectively; the maximum and minimum values of electrical conductivity were 669 and 19.80 µS/cm respectively; the maximum and minimum values of total dissolved solids were 478 and 11.80 mg/L respectively, and the maximum and minimum values of the sodium adsorption ratio were 1.72 and 0.01 mEq/L, respectively. CONCLUSION: Cation and anion concentrations were within the limits allowed by the Food and Agriculture Organization and the WHO. According to the irrigation water classification diagram, the waters were classified as C1S1 and C2S1, which implies that there are no restrictions for their use in irrigation systems, water type (I) and type (II).

An application of waste algae biochar in aquaculture water to remove co-existed cadmium and PAHs and the corresponding mechanism

ABSTRACT Water quality in aquaculture farms is highly related to the quality of aquaculture products and the connected environment. Cadmium (Cd2+) and polycyclic aromatic hydrocarbons (PAHs) are two of the most common pollutants in the aquaculture water, while biochar derived from waste algae (Enteromorpha prolifera), namely BE, was applied in farms ponds to improve water quality. Firstly, the adverse environmental impact of BE was minor, while the concentrations of the heavy metal (Cd2+ in the present study) and PAHs (FLU, PHE, FLT and PYR) were removed with efficiencies of 49%, 88%, 90%, 91% and 88%, respectively. The ecological risk values (RQs) were reduced subsequently with a rate of 58 ± 11%. After dosing BE, the ecological risk values in all the studied ponds were lower than 1, indicating no ecological risk in the corresponding aquaculture environment. The sorption capacities (qm ) of BE were 15, 12, 6.3, 0.41, 0.29 and 0.56 mg·g−1 for Cd2+, FLU, PHE, FLT, PYR and BaP, respectively. The sorption capacities were acceptable compared with those derived from other types of biomass. The removal mechanisms were partition (PAHs), complexation (Cd2+), π-π interaction (Cd2+ and PAHs), precipitation (Cd2+) and ion-exchange (Cd2+). Practically and theoretically, the algae biochar is applicable in the aquaculture environment, where Cd2+ and PAHs co-exist.

Feasibility study and seasonal variations in physico-chemical parameters of water and soil quality analysis and management of the Vannamei shrimp farms in Kerala, India

This study aims at assessing the Physico-chemical properties of water and bottom soil quality in semi-intensive vannamei shrimp farms in Kerala, India. Six different farms were selected from four districts of Kerala based on the stocking density and the technical experience in vannamei shrimp farming, as designated as Farm1, 2, 3, 4, 5 and Farm 6 including triplicates of ponds with a stocking density of 15, 25, 30, 40, 50 and 60/m2. The majority of the water quality parameters do not show any significant (p

Factors affecting water quality and shrimp production in the mixed mangrove‐shrimp systems in the Mekong Delta of Vietnam

The aim of the study was to identify key factors of water environmental parameters affect shrimp productivities in the mixed mangrove-shrimp system using multivariate approach. Water quality assessment was conducted at four mangroves stand ages (MAs) of 2–4, 5–7, 9–12 and >12 years old, with two water level (WLs) regimes in the ponds at 0–20 cm and 20–40 cm, and at every interval of 15-day grow-out cycle of shrimp in the systems based on the moon. Water quality in the study farms was within the appropriate range for shrimp growth. Mangrove ages affected alkalinity, pH, COD, N-NO2, N-NO3 and H2S, but did not influence the rest of water quality parameters. Shrimp productivity had moderate-to-fair positive correlation (rp = >0.36 and <0.5; and rp > 0.5) with N-NH4, N-NH3, water level on the platform and water level regimes management in the shrimp ponds respectively. The stepwise multiple regression model fitted very well with 19 independent variables (p = 0.0000; R2 = 0.63) and shrimp productivity. The equation of the fitted model is given as: Shrimp productivity = 18.4552 + 2.34394*DO - 1.01044*Salinity - 1.49646*H2S + 2.97012*Water level.

Energy budgets for Greenlip Abalone (Haliotis laevigata Donovan) fed graded dietary crude protein levels at seasonal water temperatures

Understanding the energy budgets of cultured abalone fed graded dietary crude protein levels at different water temperatures gives us the ability to optimise diets for different seasons. In this 91-d study we investigated the effects of feeding four diets containing graded levels of crude protein (CP; 27, 30, 33 and 36%) at three seasonal water temperatures (14, 17 and 20 °C) on the energy budget components for 6-month-old Greenlip Abalone, Haliotis laevigata, (0.91 g; 19.46 mm shell length). The increase of water temperature significantly increased individual energy budget components, rates for somatic growth energy, respiration energy and shell growth energy of abalone. Ammonia excretion energy rate was positively related to increasing dietary CP levels. In contrast, there were significant interactions between water temperature and dietary CP levels for ingested feed energy rate, absorbed energy rate and egested faecal energy rate. For energy budgets, respiration energy accounted for the largest proportion and ranged between 34.1 and 43.9% of the ingested feed energy. Somatic growth energy (16.80–28.10%) also accounted for a large proportion of the energy budget. Although egested faecal energy was lower, it still accounted for 8.2–17.9% of the ingested feed energy. In contrast, pedal mucus production energy (4.12–6.20%), ammonia excretion energy (0.28–1.40%) and shell growth energy (0.22–0.46%) accounted for relatively smaller proportions of ingested feed energy. Water temperature significantly impacted energy budgets more than dietary CP level. To maximise energy transfer to somatic growth, a water temperature of 20 °C is recommended for culturing Greenlip Abalone. Additionally, to minimise energy loss through faecal egestion, a dietary CP level of 36% is recommended for the diet of 6-month-old Greenlip Abalone at optimum water temperatures. However, the increase in ammonia excretion energy at high dietary CP should also be considered when managing water quality and waste production in abalone farms, especially where tank water exchange is limited. These findings provide a better understanding of the energy budgets for Greenlip Abalone, in relation to temperature and dietary protein levels, and will aid in the development of sustainable diets applicable to the three-four years of culture.

The Status of Water Quality in Various Fish and Shrimp Farms of Sindh Province, Pakistan: Abundance of Planktonic Biomass in Relation to Physicochemical Properties of Pond Water

The Status of Water Quality in Various Fish and Shrimp Farms of Sindh Province, Pakistan: Abundance of Planktonic Biomass in Relation to Physicochemical Properties of Pond Water

An integrated ROV solution for underwater net-cage inspection in fish farms using computer vision

This paper reports the integration of a remotely operated vehicle (ROV) solution for monitoring water quality in fish farms. The robotic system includes a RGB camera for real-time video capturing and a set of integrated sensors to measure hydro-climatic data. Computer vision algorithms were implemented with the aim of inspecting net-cages in fish farms. A comprehensive software solution was developed to allow a seamless use of the vision algorithms proposed in this work. Our system was designed to process underwater imagery captured by the ROV in order to determine net patterns associated with net failure. The system was tested in a dam under real conditions. ROC data were computed to demonstrate the accuracy of the proposed system during underwater fish cage inspection. On average, we obtained an accuracy of 0.91 regarding net pattern reconstruction tasks, while an accuracy of 0.79 for net damage detection under different underwater scenarios.

Hygienic assessment of water quality and its impact on the body of pigs

The results of research on the overall impact of drinking water quality, microclimate parameters and adopted in the farms of FE PE “Hlyniany Agro” and LLC “Miasni Resursy” options for growing weaned young (single- and three-phase) on morphological and biochemical parameters of blood, the level of natural resistance and their growth indicates that single-phase cultivation is more favorable for the growth and development of young animals. This is confirmed by the live weight of animals at birth and at the age of 120 days. Thus, in the case of single-phase cultivation of FE PE “Glynyany Agro” the live weight of piglets at birth was 1.11 kg, and in the case of three-phase LLC “Miasni Resursy” – 1.07 kg. When the animals reached 120 days of age, the live weight of piglets was 53.2 kg in FE PE “Glynyany Agro” and 50.2 kg in LLC “Miasni Resursy”. It should be noted that according to most indicators, water quality in both farms is within acceptable limits of sanitary and hygienic requirements, although it needs to be improved. With regard to microclimatic indicators, an overestimated level of ammonia was found in FE PE “Glynyany Agro”, which exceeded the MPC by 6 and 3.33 mg/m3, respectively, in the lines and transition periods, and in LLC “Miasni Resursy” was close to its upper borders. In a farm with single-phase animal husbandry, a slight decrease in erythrocytes in the blood of piglets aged 30 and 60 days was found. Since the animals reached the 120th day of life, an increase in this indicator was noted and the number of erythrocytes in the blood of animals of both farms, within the physiological norm, was 6.47 T/l (FE PE “Hlyniany Agro”) and 7.31 T/l (Miasni Resursy LLC). The concentration of hemoglobin was low in animals of both farms, but the highest rates were in animals of FE PE “Hlyniany Agro” at 30 and 60 days of age, and at 120 days of age this figure (3.28 g/l) was higher already in piglets of Miasni Resursy LLC. The content of total protein in the blood of piglets from both farms was also low, but by the time the animals reached 120 days of age, it was already within the physiological norm. Violation of the albumin-globulin ratio with the vast majority of globulins was also noted. Regarding cellular immunity, it was noted that the content of T-lymphocytes only in animals 120 days of age was normal, exceeding the lower limit of physiological norm by 0.27 % in animals with FE PE “Hlyniany Agro” and 2.09 % in animals with Miasni Resursy LLC. Our research once again confirms that the health, growth, development, and productivity of animals are influenced by a number of factors, both hygienic and technological.

Water quality in equine production in Buenos Aires Province, Argentina

One of the key factors for equine production is water, its availability in sufficient quantity and adequate quality. Studies about water quality in equine production worldwide are limited and even more limited in Argentina (South America). However, the amount of horses in Argentina declared by National Service of Agri-Food Health and Quality is of 2.5 million heads approximately, being most of them in Buenos Aires Province. The aim is to characterize the water quality in equine production farms in Buenos Aires Province, Argentina. Groundwater samples were taken from 26 equine production farms where physicochemical parameters (pH, conductivity, total hardness, chlorides, nitrates and total dissolved solids), water wells’ depth and the distance from the farms to the city of Buenos Aires were registered. The values of physicochemical parameters were correlated with the distance to the city of Buenos Aires to assess the influence of the alterations in groundwater quality resulting from pollution in the city of Buenos Aires and its periphery and the depth of the wells using the Spearman correlation (p < 0.05). The results of the work show that there is an association between farms’ water quality and the distance to the city of Buenos Aires. The depth presents significant positive correlation with the conductivity, chloride and total dissolved solids and negative correlation with nitrates. This suggests that sources of groundwater near to the city of Buenos Aires present a lower water quality. In conclusion, the water equine production farms in Buenos Aires Province were negatively related to the distance from Buenos Aires city. Equine farms closest to the city (< 80 km) may present different problems to be considered: the excessive salinity and the presence of nitrates from anthropic origin.

An intelligent IoT-based control and traceability system to forecast and maintain water quality in freshwater fish farms

The quality and safety of aquatic products are increasingly important in China. In this study, we developed an Internet of Things (IoT)-based intelligent fish farming and tracking control system that includes a forecasting method that enables automatic water quality management and supports tracking the breeding and selling of freshwater fish. This system can assist fish farmers to intelligently control and manage fishpond water-quality treatment equipment and assist consumers in tracking and viewing historical farming process data using the QR code tag of an aquatic product, which can raise revenue of fish farmers and safeguard the food safety of consumers. We also propose a set of water-quality indicator forecasting methods for a fishpond intelligent management module that first detect and remove abnormal data using the local outlier factor (LOF) algorithm after compared with DBSCAN. Then, the key fishpond data are analysed, modelled and predicted using the model tree algorithm, allowing water-quality indicators to be addressed in advance and maintained within a safe range that complies with standards. The experiments verified that the mean values of the predicted data generated by the M5 model tree algorithm were closer to those of the training data than Cubist, RF, GBM algorithm, and strong correlations were found between the predicted data and the verification data. Moreover, the mean absolute errors of our method are small relative to the data means, indicating that the proposed method can effectively and accurately forecast water-quality indicators.

Perfil parasitológico de Oreochromis niloticus y su relación con la calidad del agua en granjas acuícolas Tierra Caliente de Guerrero

La investigación se realizó en la región Tierra Caliente del Estado de Guerrero entre los meses de Enero a Octubre del año 2018. El objetivo fue determinar el perfil parasitológico de Oreochromis niloticus y su relación con la calidad del agua en granjas acuícolas de dicha Región Calentana ( representada por nueve municipios), ya que representa la zona de producción acuícola más grande y su principal fuente de abastecimiento de agua es el Rio Balsas y rio Cutzamala siendo uno de los ríos más contaminados del estado y país; por lo tanto utilizar sus aguas sin tratamientos de descontaminación para la producción de alimentos, representa un enorme riesgo a la salud humana. Para el estudio se muestrearon un promedio de siete granjas encontradas en las localidades de cada municipio de la región y se analizaron un total de 70 tilapias por municipio, teniendo un total 630 organismos, utilizando las técnicas de Disección, Raspado de piel y Coproparasitologicas, para la detección de parásitos adultos y huevos. Se encontraron 14 géneros de parásitos de los cuales cuatro son específicos de peces y diez de otros vertebrados, los géneros Phagobranchium sp y Trichodina sp presentaron mayor prevalencia con un 34.44% y 32.22% respectivamente, siendo los de menor prevalencia Ascaris sp, Enterobious sp, Heterakis sp y Paragonimus sp con 14.11% cada género. Se determinó que los parámetros indicadores de calidad de agua en los cultivos de tilapia en región Calentana, no influye sobre la presencia de parásitos ya que no se encontró relación significativa entre dichas variables según el Coeficiente de Correlación de Pearson, ya que el p-valor es mayor que 0.05, por lo tanto la presencia de parásitos en los cultivos de tilapias en región se le atribuye a la contaminación microbiológica de la fuente de abastecimiento de agua.

A Review: Drinking Water and Wastewater Quality Assessment in Ruminant Farms

Water is an essential part in any livestock production and it is more so in ruminant production that is highly water intensive. Water is not only essential as a medium of animal metabolism, but it is also an important cleaning medium. Therefore, it is important that the quality of drinking water is maintained at a certain level so as to lessen the possible adverse effects on the animals. Despite there being some standards set by the various agencies on the minimal water quality deemed suitable for livestock consumption, they are still vague and this, combined with poor compliance and the water sourcing of dubious sources in ruminant farms makes it hard to regulate the drinking water quality in ruminant farms. This, in turn, might lead to possible adverse effects in livestock production due to water contaminants. At the same time, most ruminant farms in Malaysia do not do proper treatment of their wastewater before releasing them into water bodies such as drains, rivers and lakes which could lead to possible adverse effects to the environment.