This study is aimed to evaluate the technology levels of shellfish farming in southern coast of Korea and status analysis on research of shellfish aquaculture. With achieving these objectives, it will be possible to present the direction of shellfish farming research and related project. Five major breed of shellfish aquaculture that would be adaptive and sustainable were proposed through consultation and agreement with professional group with more than 15 years of working experience. Moreover also evaluated that levels of technology, industry and market are also evaluated. The evaluation result of the expert group showed that the shellfish farming level occupied the third place in comparison with the US, Japan, Europe, and China. It is estimated that about 13~14 years will reach the level of the highest on average. In addition, most countries are expected to grow by about 10% on average over the next five years. Based on the result of the analysis of 670 research projects (2008~2017), there was little research on climate change and shellfish aquaculture. Besides some of shellfish have not been studied since 2008 and 2013, so it can be mentioned as a future task to be overcome.

The purpose of this paper is to discuss possibilities of applying growth curve models, such as Logistic, Log-Logistic, Log-Normal, Gompertz and Weibull, to three specific technology areas of Fishery Science and Technology in the process of measuring their technology level between Korea and countries with the state-of-the art level. Technology areas of hazard control of organism, environment restoration, and fish cluster detect were selected for this study. Expert panel survey was conducted to construct relevant panel data for years of 2013, 2016, and a future time of approaching the theoretical maximum technology level. The size of data was 70, 70 and 40 respectively. First finding is that estimation of shape and location parameters of each model was statistically significant, and lack-of-fit test using estimated parameters was statistically rejected for each model, meaning all models were good enough to apply for measuring technology levels. Second, three models other than Pearl and Gompertz seemed very appropriate to apply despite the fact that previous case studies have used only Gompertz and Pearl. This study suggests that Weibull model would be a very valid candidate for the purpose. Third, fish cluster detect technology level is relatively higher for both Korea and a country with the stateof- the-art among three areas as of 2013. However, all three areas seem to be approaching their limits(highest technology level point) until 2020 for countries with the state-of-the-art. This implies that Korea might have to speed up her research activities in order to catch up them prior to 2020. Final suggestion is that future study may better apply various and more appropriate models respectively considering each technology characteristics and other factors.