• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.5
• /
• pp.717-721
• /
• 2011

In case of plastic film greenhouses cultivating fresh vegetables on paddy soil, soil characteristics must be considered as more important factor than any other factors. Generally after the four years of cultivation, soils tend to increase electrical conductivity value, nutrient unbalance and soil pests. As a result, degradation of agricultural products occurred, therefore it is necessary to improve soil conditions. In this study, yield and economic cost of cucumber were analyzed. The best soil conditions for cucumber cultivation were alluvial or valley in soil topology, moderately or poorly drainage in soil drainage classes, coarse loamy soil in texture. In addition, rich-sunlight and-deep groundwater would be proper for the cucumber cultivation. Good environmental managements of plastic film greenhouse were as follows. The temperature needed to be adjusted three times. The optimal daytime temperature could be $22{\sim}28^{\circ}C$, the one from 12 until night could be $14{\sim}15^{\circ}C$, and the temperature from 24 to sunrise could be $10{\sim}12^{\circ}C$. During plant growth period, soil moisture content was as low as 10~15%, and it needed to be maintained as 15~20% during reproductive growth period. To control pests, catch crop cultivation and solar treatment were carried out, after those EC was reduced and the root-knot nematode was controled too. Cucumber yield from the plot with improved soil managements increased to $158.4Mg\;ha^{-1}$, but plot with successive cropping injury yielded $140.3Mg\;ha^{-1}$. The income from the plot with improved soil managements was 215,676 thousand won $ha^{-1}$, the plot with successive cropping injury was 131,649 thousand won $ha^{-1}$. Income rate of each plot was 51.8% and 38.4%, respectively.

• Journal of The Korean Astronomical Society
• /
• v.52 no.1
• /
• pp.11-21
• /
• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.8 no.2
• /
• pp.47-60
• /
• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.