• The Journal of Fisheries Business Administration
• /
• v.51 no.1
• /
• pp.1-17
• /
• 2020

This study is an analysis of the Aquaculture Industry Development Act that has recently been passed by the National Assembly. In order to improve the structural problem of Korea's aquaculture, a large revision of aquaculture related laws and regulations is needed. The enactment of Aquaculture Industry Development Act is necessary to that effect. It is adequate to aim for development as aquaculture industry not as aquaculture, to alleviate entry restriction of aquaculture, and to provision diverse promotion and support policies. However, it is a concern whether the current Aquaculture Industry Development Act can achieve its goal of enhancing the competitiveness of aquaculture and sustainability. Rather than to solve the problem, the act holds the possibility of further fixing or exacerbating the problem. So there is concern for side-effects after the enactment. This is due to the fact that it complicates terminologies by unnecessarily differentiating aquaculture related concepts from the existing Fisheries Act, lacks regulations regarding voluntary participation in aquaculture, and has limited methods to alleviate entry restriction. In addition, there are very few measures for the scale improvement of aquaculture along with the unlikeliness of a significant effect of the review and evaluation for re-licensing. Thus, the Aquaculture Industry Development Act should promptly be revised after its enactment.

• Smart Media Journal
• /
• v.11 no.2
• /
• pp.39-52
• /
• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• The Journal of Fisheries Business Administration
• /
• v.47 no.2
• /
• pp.1-14
• /
• 2016

This study applied the Stochastic Frontier Analysis to estimate which independent variable affects to efficiency of aquaculture household. This study used wage and facility scale as input variables, sales volume as an output variable to estimate efficiency. Also, the study used region, species, water quality to estimate technical inefficiency factors of the model. The data used for this study were obtained by the operating costs survey using 1:1 interview method. The study selected translog production model with technical inefficiency term estimated as half-normal distribution. In addition, the study used pearson and spearman correlation coefficient among efficiency estimating models. Also, the study analysed differences among estimated efficiencies through t-test, and showed us 0.1793 in species, 0.4677 between Geojae and Masan.

• The Journal of Fisheries Business Administration
• /
• v.44 no.3
• /
• pp.77-84
• /
• 2013

While some steps in laver aquaculture production can be controlled artificially to a certain extent, the culturing process is largely affected by natural factors, such as the characteristics of seawater, climatic and oceanographic conditions, etc. This study aims to find a direct relationship between climatic and oceanographic factors (water temperature, air temperature, salinity, rainfall, sunshine duration and wind speed) and laver aquaculture production in Wando region, the biggest aquaculture production area of laver, located in the southwest coast of Korea using a multiple regression analysis. Despite the small sample size of a dependent variable, the goodness of model fit appeared acceptable. In addition, the R-squared value was 0.951, which means that the variables were very explanatory. Model results indicated that duration of sunshine, temperature, and rainfall during the farming period from the end of September to the end of April would be important factors affecting significantly to the laver aquaculture production.

• The Journal of Fisheries Business Administration
• /
• v.46 no.2
• /
• pp.43-57
• /
• 2015

The study aims to identify the current status of aquaculture information in Korea and suggests policy directions for its integrated management. Firstly, the study focuses on the identification of the current status of aquaculture information by reviewing how aquaculture information is managed. Secondly, this study identifies problems such as lacks in necessary aquaculture information, inefficiency caused by dispersion and overlapping of information, absence of integrated management system and insufficient sharing of information. After identifying the current status of aquaculture information and its problems, the study suggests three basic directions to systematically integrate and manage the information such as establishment of infrastructure for promoting the integrated management of aquaculture information, generation and systematic management of useful aquaculture information and enhancement of user convenience. Finally, the study suggests detailed strategies such as establishment of a foundation to facilitate integrated management of aquaculture information, organization of organic network, sharing of more information, creation of necessary information through demand survey, creation of systematic management system, provision of a customized total service, and increase in education and PR activities on information use.

• The Journal of Fisheries Business Administration
• /
• v.54 no.2
• /
• pp.045-058
• /
• 2023

This study aims to analyze the cost of climate change damages to laver and sea mustard aquaculture, which are considered to be highly vulnerable to climate change in Korea. For this purpose, the correlation between aquaculture production and climate factors such as water temperature, salinity, air temperature, and precipitation was estimated using a panel regression model. The SSP scenario was applied to predict the changes in production and damage costs due to changes in future climate factors. As a result of the analysis, laver production is predicted to decrease by 18.0-27.2% in 2050 and 20.6-61.6% in 2100, and damage costs are predicted to increase from 29.7-50.8 billion KRW in 2050 to 35.7-116.1 billion KRW in 2100. Sea mustard production is projected to decrease by 24.5-37.2% in 2050 and 24.0-34.5% in 2100, with similar damage costs of 41.1-61.8 billion KRW and 41.1-58.6 billion KRW, respectively. These damage costs are expected to occur in the short term as damage caused by fishery disasters such as high temperatures, and in the long term as a decrease in production due to changes in aquaculture sites. Therefore, measures such as strengthening the forecasting system to prevent high-temperature damage, developing high-temperature-resistant varieties, and relocating fishing grounds in response to changes in aquaculture sites will be necessary.

• The Journal of Fisheries Business Administration
• /
• v.39 no.2
• /
• pp.109-123
• /
• 2008

This study is aimed to establish an investment decision model for offshore aquaculture project of rock bream in Korea using a certainty equivalent method (CEM) based on the expected utility theory and to investigate its economic viability under risk and uncertainty. In the analysis with CEM, the effects of risk attitude and risk level on investment and risk premium were examined and the impacts of various risk and uncertainty factors on the investment decision were also assessed. In addition, the outcomes were compared to those evaluated by the traditional net present value (NPV) method. Results show that risk premium grew as the investors became more risk averse and uncertainty level (the variance of NPV) increased. Consequently, the certainty equivalent value was predicted to decrease from the value assessed by the traditional NPV method.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.56 no.2
• /
• pp.243-252
• /
• 2023

Fluctuations in the price of aquaculture products have recently intensified. In particular, wholesale price fluctuations are adversely affecting consumers. Therefore, there is an emerging need for a study on forecasting the wholesale price of aquaculture products. The present study forecasted the wholesale price of olive flounder Paralichthys olivaceus, a representative farmed fish species in Korea, by constructing multivariate long-short term memory (LSTM) and gated recurrent unit (GRU) models. These deep learning models have recently been proven to be effective for forecasting in various fields. A total of 191 monthly data obtained for 17 variables were used to train and test the models. The results showed that the mean average percent error of LSTM and GRU models were 2.19% and 2.68%, respectively.

• Ocean and Polar Research
• /
• v.41 no.1
• /
• pp.35-46
• /
• 2019

The purpose of this study is to identify factors influencing fish production of shallow-sea aquaculture in South Korea. This study employed the two-way fixed effect and random effect models based on the panel models and also the difference between GMM and system GMM models based on the dynamic panel models using the amount of fish farming production, the number of stocked fry, the number of cultured fish, the amount of inputted feed, the farming area, the number of workers, and the sales price data from 2010 to 2017. First, the two-way fixed effect model of the panel models was selected by panel characteristics, time characteristics and Hausman tests and also the model was statistically significant. As a result of the two-way fixed effect model, the number of stocked fry, the amount of inputted feed, and the number of workers were identified as factors that increase the fish production of shallow-sea aquaculture. However, the number of cultured fish and the sales price were analyzed as factors that reduce the fish production of shallow-sea aquaculture. Second, the system GMM model of the dynamic panel models was selected by Hansen test and Arellano-Bond test in order to identify whether or not the over-discrimination condition is appropriate. Based on the system GMM model, the number of stocked fry, the amount of inputted feed, the number of workers in this year and 1 year ago, the number of cultured fish 2 years ago, and the sale price 3 years ago were analyzed as factors that increase the fish production of shallow-sea aquaculture. However, the amount of fish farming production 1, 2, 3 years ago, the farming area in this year, and the number of cultured fish in this year and 1 year ago were identified as factors that reduce the fish production of shallow-sea aquaculture. In conclusion, this study suggests that it is desirable to control the amount of stocked fry rather than to expand the farming area for fish farming in shallow-sea aquaculture, so as to keep the sale price at a certain level by maintaining the appropriate amount of fish production.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.56 no.6
• /
• pp.930-935
• /
• 2023

This study aimed to analyze the structure of the value chain of the olive flounder aquaculture industry to increase the value of this industry. Based on the value chain theory, olive flounder aquaculture industry activities were classified as primary and support activities. The primary activities included seed production, fish production, producer distribution, consumer distribution, and consumption. The support activities were production infrastructure, organization and specialization, R&D, and government policy. A survey was conducted on the costs of seed and fish production in the primary activities to investigate the business structure, and the distribution structure was analyzed to examine distribution costs and margins. In the support activities, the recent trends in R&D and government policy were mainly examined, based on which, a measure to reduce costs and maximize profits was suggested. It is necessary to reduce costs across the production processes by improving seed quality and reducing labor, feed, and management costs, which are strongly associated with support activities. Therefore, lowering costs will be possible in the olive flounder aquaculture industry when R&D outcomes, such as species development, feed quality improvement, and aquaculture system development, are stably diffused and applied in tandem with government policy regarding the industry.