Inland Farms Research Articles

Host specificity and virulence of Flavobacterium psychrophilum: a comparative study in ayu (Plecoglossus altivelis) and rainbow trout (Oncorhynchus mykiss) hosts

Flavobacterium psychrophilum, the causative agent of bacterial cold-water disease, is a devastating, worldwide distributed, fish pathogen causing significant economic loss in inland fish farms. Previous epidemiological studies showed that prevalent clonal complexes (CC) differ in fish species affected with disease such as rainbow trout, coho salmon and ayu, indicating significant associations between particular F. psychrophilum genotypes and host species. Yet, whether the population structure is driven by the trade of fish and eggs or by host-specific pathogenicity is uncertain. Notably, all F. psychrophilum isolates retrieved from ayu belong to Type-3 O antigen (O-Ag) whereas only very few strains retrieved from other fish species possess this O-Ag, suggesting a role in outbreaks affecting ayu. Thus, we investigated the links between genotype and pathogenicity by conducting comparative bath infection challenges in two fish hosts, ayu and rainbow trout, for a collection of isolates representing different MLST genotypes and O-Ag. Highly virulent strains in one host species exhibited low to no virulence in the other. F. psychrophilum strains associated with ayu and possessing Type-3 O-Ag demonstrated significant variability in pathogenicity in ayu, ranging from avirulent to highly virulent. Strikingly, F. psychrophilum strains retrieved from rainbow trout and possessing the Type-3 O-Ag were virulent for rainbow trout but not for ayu, indicating that Type-3 O-Ag alone is not sufficient for pathogenicity in ayu, nor does it prevent pathogenicity in rainbow trout. This study revealed that the association between a particular CC and host species partly depends on the pathogen’s adaptation to specific host species.

Japanese Immigration in America: Fleeing Riots, Escaping Imprisonment, and Assimilating.

When 13-year-old Teruichi Nakayama, my grandfather, came to San Francisco from Osaka in 1906, he was assured of an education in a public school by an 1894 treaty between the United States and Japan that gave the latter most-favored-nation status. In 1906, racist mobs forced a decision by the school board to assign 41 school aged Japanese children, including him, to a segregated school for Asian children in violation of the pact. In 1907, he escaped street violence to work as a migrant laborer on inland farms. Settling in the state's Central Coast, he started a confectionary, the family business he knew from his childhood in Japan. He eked enough money to raise a family with a wife arranged for him in the traditional manner by a go-between in Japan. The school board action opened a diplomatic rift between the 2 countries that never resolved and ended in war in 1941. Just days ahead of the imprisonment of Japanese living in California in 1942, he and his family fled to Colorado, a sanctuary state where he reestablished the confectionery. He faced every misapprehension of the current immigration crisis: racism, unfair labor competition, the impossibility of assimilation, and suspicion of a fifth column. Now 5 generations later, none of the fearful predictions when he first arrived came true. His legacy proves immigration as an essential rejuvenating force in America.

Blue economy in the green fields: rethinking value chain analysis of inland fisheries in Bangladesh

Bangladesh ranks as the third largest country in terms of inland freshwater resources. This study seeks to explore the current development of the inland cultured fish market value chain and the criteria for its expansion. A field survey was conducted across inland fishery farms in eight districts, representing all eight divisions of Bangladesh. From each district, four farms were selected, including small, medium, and large operations. Regression analyses were performed on various covariates in relation to total sells, with and without resampling. Key factors identified as significant include total production, farmer's age, farm size, electricity costs, minnow expenses, culture duration, loan transactions, and specific regional divisions. The findings suggest that as farmer’s age, expand their farm areas, and extend the culture period, total sells are likely to increase. According to the survey data, retailers enjoy the highest profit margin at 29%, while farm owners or farmers hold the second highest margin at 26% for inland carp fish.

Removal of the red tide dinoflagellate Cochlodinium polykrikoides using chemical disinfectants

For decades, red tide control has been recognized as necessary for mitigating financial damage to fish farms. Chemical disinfectants, frequently used for water disinfection, can reduce the risk of red tides on inland fish farms. This study systematically evaluated four different chemical disinfectants (ozone (O3), permanganate (MnO4−), sodium hypochlorite (NaOCl), and hydrogen peroxide (H2O2)) for their potential use in inland fish farms to control red tides by investigating their (i) inactivation efficacy regarding C. polykrikoides, (ii) total residual oxidant and byproduct formation, and (iii) toxicity to fish. The inactivation efficacy of C. polykrikoides cells by chemical disinfectants from highest to lowest followed the order of O3 > MnO4− > NaOCl > H2O2 for different cell density conditions and disinfectant doses. The O3 and NaOCl treatments generated bromate as an oxidation byproduct by reacting with bromide ions in seawater. The acute toxicity tests of the disinfectants for juvenile red sea bream (Pagrus major) showed that 72-h LC50 values were 1.35 (estimated), 0.39, 1.32, and 102.61 mg/L for O3, MnO4−, NaOCl, and H2O2, respectively. Considering the inactivation efficacy, exposure time of residual oxidants, byproduct formation, and toxicity toward fish, H2O2 is suggested as the most practical disinfectant for controlling red tides in inland fish farms.

Probabilistic power curve estimation based on meteorological factors and density LSTM

Wind power curve describes the relationship between wind speed and wind power output, which is useful for wind farm design and wind turbine condition monitoring. However, most research on power curves modeling neglected the effect of historical meteorological factors. Also, the research on probabilistic power curve is still limited. Therefore, this paper proposes a novel probabilistic power curve modeling approach. The effect of both current and historical meteorological variables, such as wind speed, wind direction, ambient temperature and turbulence intensity, on the power curve is studied by binning method and kernel density estimation. Next, instead of forecasting the wind power or its quantiles, a new probabilistic power curve model, Density LSTM with Negative Log-Likelihood Loss, is proposed to forecast the parameters of the probability density function of wind power directly. Finally, different probability distribution of wind power output is studied. Gamma, Laplace and Weibull distributions prove to be more suitable than Gaussian distribution. Based on the datasets of inland and offshore wind farms, it is verified that adding useful historical meteorological variables can improve the forecasting performance of the test dataset. Besides, the proposed probabilistic power curve can effectively improve the prediction performance in the probabilistic prediction task and can improve the prediction precision of the annual energy production.

Antibiotics usage practices in aquaculture in Bangladesh and their associated factors

BackgroundIrrational and inappropriate use of antibiotics in aquaculture can contribute to the development of antibiotic resistance. ObjectivesIn this study, we aimed to assess antibiotic usage in inland and coastal fish farms in Bangladesh and identify factors associated with this practice. MethodsWe conducted a cross-sectional study to collect antibiotic usage information from 672 fish farmers in Bangladesh. The frequency of use, the types of antibiotics, the purpose of usage, and antibiotic prescribing practices were estimated. Adjusted odds ratios (aOR) were calculated to measure the association between antibiotic usage and factors related to the characteristics of the farms and farmers using multivariable logistic regression models. ResultsTwenty-two farms reported using antibiotics in the last 24 h preceding the interview (3%, 95% CI: 2–5%); 36 farms (5%, 95% CI: 4–7%) in the last 72 h, 141 farms (21%, 95% CI: 18–24%) in the last 14 days, and 478 farms (71%, 68–75%) reported antibiotic usage at least once since the start of their production cycle. Antibiotics usage in the last 14 days preceding the interviews was higher in freshwater fish farms (98%) than in brackish water farms (2%). Oxytetracycline, ciprofloxacin, and amoxicillin were the most frequently used antibiotics. Most of the antibiotics were reported to be used for both therapeutic and prophylactic purposes (71%, 95% CI: 63–78%). Antibiotics used within the last 14 days were mainly advised by feed dealers or drug sellers (51%, 95% CI: 43–60%), followed by farmers themselves (31%, 95% CI: 23–38%) and local service providers (18%, 95% CI, 12–25%). Fish farms having history of antibiotic use within the last 14 days preceding interviews was significantly associated with illness in fish (aOR 1.98, 95% CI:1.21–3.29) compared to farms with healthy fish and fishes cultured in ponds (aOR 9.34, 95% CI: 3.69–23.62) compared to enclosure cultures. ConclusionsImprovement of fish health through better farming practices and changes in feed dealers' and farmers' attitudes towards self-prescription of antibiotic without veterinarian diagnostics may help to reduce the levels of antibiotic usage and thus contribute to mitigating antimicrobial resistance.

Measurement and analysis of regional agricultural water and soil resource composite system harmony with an improved random forest model based on a dragonfly algorithm

To expand the field of harmony theory research, new paths for sustainable development of agricultural regions are explored. The uncertainty problem is selected to determine the optimal parameters of the random forest (RF) model. This paper uses the Dragonfly algorithm (DA) to calibrate the RF model parameters, proposes an improved model (DA-RF), and applies it to measure the agricultural water and soil resources composite system harmony (AWSRCSH) of the Jiansanjiang Branch of the Heilongjiang Great Northern Wilderness Agribusiness Group Corporation. The results show that the DA-RF model can effectively improve the simulation ability and stability with a running time that is longer than that of an empirical method. The annual variation in the AWSRCSH of the Jiansanjiang Branch presents an “N-type” trend. From 1997 to 2005, the branch had not yet entered a peak period of resource and agricultural development, while the AWSRCSH had steadily improved during this period. From 2005 to 2008, due to predatory operations, the AWSRCSH decreased, and the speed of this decrease increased. From 2008 to 2016, since local water and soil resource development was strictly controlled and agricultural modernization increased, the AWSRCSH gradually increased. Due to the advantages of water resources and topography, the AWSRCSH in the farms adjacent to the river was greater than that in inland farms. To address the slow growth rate of the AWSRCSH, some adaptive regulation strategies were proposed according to key driving factors, and the effect of harmonious regulation was predicted.

The influence of multiple industries on the behaviour of breeding gulls from four colonies across the eastern Gulf of Maine, Canada

Opportunist gulls use anthropogenic food subsidies, which can bolster populations, but negatively influence sensitive local ecosystems and areas of human settlement. In the eastern Gulf of Maine, Canada, breeding herring gulls Larus argentatus have access to resources from aquaculture, fisheries and mink farms, but the relative influence of industry on local gull populations is unknown. Our objectives were to 1) assess use of natural and anthropogenic habitats by herring gulls from multiple colonies, 2) evaluate variation among colonies in use of distinct resource types within these habitats and 3) highlight areas of high gull:industry interaction. Using GPS devices on 39 gulls from four colonies, we identified visitation behaviour (slow, localized movements) and assigned visits to nine resource types. To evaluate the spatial distribution of visits, we created a use intensity index, reflecting both fidelity (i.e. repeated visits) and time spent in specific areas. All four anthropogenic resource types were heavily used (56 ± 11% of visiting time across colonies), notably, fish plants and mink farms. Despite large distances among three colonies, birds overlapped at particular distant, inland mink farms. In contrast, birds from close colonies overlapped in visitation to specific nearby resources (e.g. fish plants and human settlement), and otherwise diverged in distribution and use of offshore and coastal areas. Birds from three colonies also made frequent, long visits to uninhabited islands. Industry is clearly influencing the behaviour of breeding gulls in the eastern Gulf of Maine, Canada, where birds are travelling great distances or spending large proportions of time interacting with anthropogenic resources, while otherwise paying lengthy visits to nearby coastal islands. Studies have shown that concentrations of gulls can have harmful direct and indirect ecological and societal impacts. Our findings have implications for the management and regulation of industry to mitigate detrimental effects on local ecosystems and humans.

An initial survey on the occurrence of staphylococcal infections in Turkish marine aquaculture (2013–1014)

A tentative survey on selected marine fish farms was undertaken to delineate the extent to which infections with Staphylococcus species occur in Turkish aquaculture systems. To determine the presence and the distribution of fish pathogenic staphylococci, representative farm types such as marine cages as well as inland pond farms working with saline-ground water and a large hatchery were selected. Field sampling was performed in a total of 13 commercial fish farms that are located in the most-popular aquaculture sites of Turkey. Samples were taken between October 2013 and August 2014. Almost all size classes of the most commonly marine cultured fish species in Turkey were investigated, including Dicentrarchus labrax, Sparus aurata, Argyrosomus regius, Diplodus puntazzo, Dentex dentex, Onchorhynchus mykiss and Salmo labrax. After a visual check, specimens with various clinical signs were sampled for bacteriological and histopathological investigations. Mixed infections of staphylococci along with Vibrio and Aeromonas representatives were detected in Dicentrarchus labrax, Sparus aurata and Diplodus puntazzo samples obtained from 7 farms. The following pathogens were identified: Staphylococcus. epidermidis, S. aureus, S. capitis subsp. capitis, S. lentus, S. hominis subsp. hominis and S. sciuri subsp. sciuri. Main clinical and histopathological effects of the infections in fishes were revealed. The pathogenicity of some isolates was confirmed with in vivo pathogenicity assay and SDS-PAGE analysis.

Bioremediation with freshwater bivalves: A sustainable approach to reducing the environmental impact of inland trout farms

Integrated multi trophic aquaculture (IMTA) is well developed in seawater, while the only suitable organisms for bioremediation in freshwater are bivalves. The aim of this research has been to investigate a novel system, based on freshwater bivalves integrated with rainbow trout, for the bioremediation of inland aquaculture systems. The Unionid species selected for the experiments was Sinanodonta woodiana. Five mesocosm experiments were conducted to evaluate the efficiency of mussels in filtering the total bacteria and Aeromonas hydrophila, as well as their clearance efficiency on trout farm wastewater. The temperatures, dissolved oxygen, nitrates, and phosphates were monitored and were all within the physiological tolerance range of the species in all the experiments. The feasibility of bioremediation with S. woodiana in trout farming has thus been demonstrated, and among the tested rearing densities (3.75; 7.5; 15; 30 and 60 kg m−3) that of 7.5 kg m−3 was found to be optimal. The net reduction of the total bacterial concentration was as much as 72%, while that of A. hydrophila reached a level of 95–98%. No relevant effects of the mussels on particulate suspended material or sedimented material was observed, regardless of the temperature. The efficiency of freshwater bivalves in reducing the bacterial load, in particular toward A. hydrophila, indicates a bioremediation system with the possibility of interesting applications on inland fish farms, and as a biotechnological tool against the diffusion of antibiotic resistance in aquaculture.

Analysis of the cloud-to-ground lightning characteristics before and after installation of the coastal and inland wind farms in China

The effects of wind turbines (WTs) on cloud-to-ground (CG) lightning activities have not been fully understood. Based on the CG lightning data obtained from lightning location system (LLS), this paper quantified and compared the characteristics of CG lightning activities, including lightning density, multiplicity, polarity, peak current, and seasonal distribution, before and after the erection of the wind farms (WFs) in China. The shielding effect of offshore WTs was also analyzed. The results showed that, since the WF located in the southeast China was constructed, the return stroke density, flash density and multiplicity within a radius of approximately 0.5 km around the WTs increased by 27.9%, 7.3% and 10.9% in terms of change rate, respectively; within the same distance, the negative median peak current was -23.9 kA, and the positive median peak current was 12.3 kA. WTs located at the edge of the offshore WF had a shielding effect on the internal WTs. The proportion of spring lightning was up to 41.4% in southwest China. Winter lightning was rare in southern China. The results suggest more detailed factors, such as the local terrain, climate and the layout of WFs, are needed when assessing the lightning risk to WTs.

Portable Pumpless 3D-Printed Chip for On-Site Colorimetric Screening of Hg2+ in Lake Water

The early detection of mercury ions in water sources should be emphasized to prevent human exposure to mercury through drinking water or food consumption. Here, we used a three-dimensional (3D)-printed multiarray chip to achieve colorimetric detection of inorganic mercury ions in environmental matrices such as lake water. The chip designed for the multidetection of inorganic mercury did not require an electrical syringe pump or a complex analytical system, thereby making it suitable for on-site detection. The chip could detect inorganic mercury ions via rolling circle amplification, by selectively harnessing thymine-Hg2+-thymine coordination chemistry. Additionally, the activities of rolling circle amplification in simple and environmental matrices were compared. The limits of detection for inorganic mercury ions were 3.4 and 4.1 ??g/L in the simple and environmental matrices, respectively. Further, the chip was successfully applied for the detection of mercury in actual lake water samples collected from locations nearby inland fish farms. The results were quantitatively comparable to those obtained using a conventional mercury analyzer.

Non-contact vibration monitoring of rotating wind turbines using a semi-autonomous UAV

With the recent demands for more efficient clean renewable energy sources, wind turbines are designed that have large rotor blade diameters. These large-sized wind turbines need to be periodically monitored to prevent catastrophic failures. This paper aims to develop a practice for obtaining the vibration characteristics of wind turbine blades that can be eventually used for structural health monitoring of these structures. This monitoring technique needs to be robust and non-contact to prevent any interference with the operation of the wind turbine. In this work, a digital image correlation (DIC) system installed on a drone is used as a sensing technique to obtain the dynamic characteristics of rotating wind turbine blades. The DIC uses a stereo-camera system to record the deflections of the blades and provides non-contact measurements. The unmanned aerial vehicle (UAV) enables on-site robust measurements. Furthermore, a dynamic stitching technique is used after DIC measurement to obtain vibration characteristics of the entire blade with high accuracy. The proposed health monitoring technique can be used by engineers for remote structural health monitoring of wind turbines during operation in both offshore and inland wind farms.

Economic and sustainability promises of wind energy considering the impacts of climate change and vulnerabilities to extreme conditions

A dramatic expansion of the worldwide wind power capacity is underway which is critical to an effective mitigation of climate change. However, wind tower infrastructure is susceptible to extreme weather conditions such as tropical cyclones and thunderstorms. Under the context of global climate changes and intense weather events, it is imperative to assess the impacts of extreme conditions on the susceptibility of the global wind power with important implications on energy security and power system resilience. In this paper, we discuss the necessity and rationality of wind power deployment considering extreme weather perspectives on enhancing the global sustainability, security, economics, and resilience. We assess the vulnerability of wind power to extreme weather events under climate change and present the correlation of wind power proliferation, extreme weather events, and climate change issues. Our results indicate that, if extreme wind speed increases by 20% considering a 50-year return wind speed and load safety factor is changed from 1.35 to 1.7, the initial capital cost of wind unit installation by the end of this century could increase by about 12% because of the higher strength in tropical cyclones. In this period, upward lightning strike will be intensified due to the use of taller wind turbines and higher angular speed of blades. Also, additional storm surges and sea ices will potentially cause higher risks to inland and offshore wind tower structures and foundations because of the continuously rising sea levels. It is confirmed in our discussion that the proliferation of wind power generation would be beneficial despite its vulnerabilities by curbing the use of fossil-based power generation units, mitigating severe carbon emission, and reducing climatic changes and extreme weather events, which could also cause significant structural damages to wind turbines installations globally. The article concludes that it is vital in the scientific community to further analyze the relationship among global wind energy integration, extreme weather events, and climate changes, and for politicians to formulate a comprehensive energy policy strategy, as engineers continue to investigate the means of deploying additional inland and offshore wind farms and consider other types of renewable energy resources with a direct link with weather conditions, for a sustainable, economic, secure, and resilient energy production.

Molecular characterisation of infectious pancreatic necrosis viruses isolated from farmed fish in Finland

Infectious pancreatic necrosis virus (IPNV) has been isolated annually since 1987 from salmonids without clinical signs at coastal fish farms in Finland. In the inland area, viral isolations were rare until 2012, when IPNV was detected at several freshwater fish farms. Between 2013 and 2015, the infection spread and IPNV was continuously isolated from several farms, both inland and on the coast. The aim of this study was to genetically characterise the IPNV isolates collected from Finnish coastal and inland fish farms over the last 15 years, and to detect genetic changes that may have occurred in the virus populations during the study period. The partial VP2 gene sequence from 88 isolates was analysed. In addition, a complete genomic coding sequence was obtained from 11 isolates. Based on the genetic analyses, Finnish IPNV isolates belong to three genogroups: 2, 5 and 6. The genetic properties of the isolates appear to vary between inland farms producing juveniles and food fish farms in the coastal region: the inland farms harboured genogroup 2 isolates, whereas at coastal farms, all three genogroups were detected. Little genetic variation was observed within the Finnish genogroup 2 and 5 isolates, whereas among the genogroup 6 isolates, two subgroups were detected. All isolates studied demonstrated amino acid patterns in the viral VP2 gene previously associated with avirulence. However, increased mortality was detected at some of the farms, indicating that more research is needed to clarify the relationship between the pathogenicity and genetic properties of IPNV isolates from different genogroups.

Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study

This paper presents an academia-industry joint study concerning effective methods to estimate and quantify the effect of vortex generator installation on wind power production. This problem has presented a challenge to the wind industry, because (a) vortex generator installation may lead to a moderate 1–5% extra power production, but this level of improvement is difficult to be accurately detected; and (b) it is equally difficult to validate the estimated effect of vortex generator installation because a controlled experiment is practically impossible to conduct to provide a credible baseline. An academic institute and a wind technology company team up to tackle this challenge. The two teams develop their own version of quantification methods, which are profoundly different. The academic method uses 10-min data and makes use of both power and environmental data, whereas the company method uses high-frequency data via primarily a direct power comparison approach that relies less on the environmental data. When applying the respective methods to two inland wind farms, each of which presents four pairs of turbines, the quantification results from the two methods are surprisingly consistent. We believe the consistent outcome presents a strong case of cross validation, testifying to the respective method's capability and credibility.

Forecasting high proportions of wind energy supplying the Brazilian Northeast electricity grid

This study examines the optimal integration of high proportions of wind energy into an electricity grid which traditionally depends on hydroelectricity. Wind power in the Brazilian Northeast (NE) is expected to generate 57% of the NE’s electricity supply by 2020. As rainfall in the NE region is susceptible to climate change, it is anticipated that wind energy could substitute lost hydroelectric availability. The Weather Research and Forecasting (WRF) Model is used to simulate wind speeds for all of 2014 and calculate wind power across the entire NE region of Brazil. The NE region’s aggregate hourly wind generation and net load curve are then estimated for increasing wind penetrations using the planned rollout of wind farms in the region as a baseline. The maximum wind energy penetration in the region is estimated to be approximately 50% before significant amounts of energy would need to be curtailed or exported to other Brazilian regions. It was found that wind energy generation from coastal wind farms in the region best correlates with the hourly and monthly variations of the NE subsystem’s load curve. Conversely, inland wind farms on the NE’s elevated plateaus typically generate more power late at night, but have higher capacity factors.

Energy performance of wind power in China: A comparison among inland, coastal and offshore wind farms

China has the largest wind power installation across the world due to the tremendous inland wind capacity and the government has begun to pay much more attention to develop offshore wind power in recent years. During the shift from inland to offshore, it is very important to identify the difference of energy performance between them. This paper establishes 4 indicators; energy consumption intensity (EI), energy payback time (EPT), energy payback ratio (EPR) and energy return intensity (ERI) to measure the energy performance of wind farms. Meanwhile, coastal wind farms are introduced as a smooth transition cases from inland to offshore wind farms. Each of the 8 farms for inland, coastal and offshore wind are taken as the examples to assess. The results show that inland and coastal wind farms have the similar energy performance, which pose significant difference with that of offshore wind farms. Based on the relatively lower EI, EPT and higher EPR, land-based inland and coastal wind farms are better for energy efficiency. From the energy performance route of wind farms, the energy performance strength of offshore wind farms only appear after 9.2 years of operation when compared to the land-based wind farms. Therefore, it is wise to set a long-term moderate target for offshore wind power development in China, just as the highest ERI of offshore wind farms can only be obtained in a long-term period.

Infectious pancreatic necrosis virus (IPNV) strain with genetic properties associated with low pathogenicity at Finnish fish farms.

Infectious pancreatic necrosis (IPN) is a contagious viral disease of fish that causes economic losses in aquaculture worldwide. In Finland, IPN virus (IPNV) has been isolated since 1987 from adult fish showing no signs of clinical disease at fish farms located in the coastal areas of the Baltic Sea. The inland area of Finland, however, remained free of IPN until 2012, when fish on several rainbow trout farms were diagnosed IPNV-positive. The fish mortalities detected at the farms were low, but clinical signs and histopathological changes typical for IPNV infection were seen in juvenile salmonids. IPNV was isolated at high water temperatures up to 22°C. In 2013 and 2014, IPNV detections continued at inland farms, indicating that infections have spread. The aim of this study was to describe the epidemiology of the outbreak and to characterise the Finnish inland IPNV isolates using histopathological, immunohistochemical and genetic approaches. In order to determine the epidemiological origin of the inland IPNV infections, the partial viral capsid protein (VP2) gene sequences of the inland IPNV isolates were compared with the sequences of the isolates from the coastal farms. Based on the genetic analysis, the inland isolates belong to IPNV Genogroup 2 (Serotype A3/Ab), and the origin of the isolates appears to be one or several coastal fish farms.

Effect Analysis about Inland Fish Farm for Development of Underground Seawater

Due to red tide and abnormal currents that take place every year, the damage of inland fish farms that takes sea water is increasing frequently. Also, the households of inland fish farm due to the increase in the cost of fuel and electricity are struggling many hardships economically. In relation to underground seawater for it`s farm analyzed economic effect based on the actual conditions for 1,700 inland fish farms, from this I have deduced policy implications for direction this project to be pursued from now on. The saving rate of costs of the fuel and electricity through the development of an underground seawater were approximately analyzed to decline about 3.4~9.7%, if utilizing only about 5% of the undeveloped farms, it was estimated effect of about 61 billion won, if 10%, it was estimated effect of about 122 billion won. Consideration in selecting the developer of underground seawater will be selected an character of farm method. It is expected this study will be helpful for business analysis related government in the fisheries.