• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.211-217
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• 2018

The purpose of this paper is to explore the possibility and strategic directions of Korean agriculture in the future by analyzing domestic and foreign successful cases leading to the 6th industrialization of agriculture by utilizing 4th Industrial Revolution technologies. To do this, we surveyed the key technologies of the 4th Industrial Revolution, and examined successful cases of the US, Korea and China. As results of these case studies, we recognized that 4th Industrial Revolution technologies could play important roles in the 6th industrialization of agriculture, and suggested meaningful strategic implications using ABCD model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.61-71
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• 2009

Most deciduous trees in temperate zone are dormant during the winter to overcome cold and dry environment. Dormancy of deciduous fruit trees is usually separated into a period of rest by physiological conditions and a period of quiescence by unfavorable environmental conditions. Inconsistent and fewer budburst in pear orchards has been reported recently in South Korea and Japan and the insufficient chilling due to warmer winters is suspected to play a role. An accurate prediction of the flowering time under the climate change scenarios may be critical to the planning of adaptation strategy for the pear industry in the future. However, existing methods for the prediction of budburst depend on the spring temperature, neglecting potential effects of warmer winters on the rest release and subsequent budburst. We adapted a dormancy clock model which uses daily temperature data to calculate the thermal time for simulating winter phenology of deciduous trees and tested the feasibility of this model in predicting budburst and flowering of Niitaka pear, one of the favorite cultivars in Korea. In order to derive the model parameter values suitable for Niitaka, the mean time for the rest release was estimated by observing budburst of field collected twigs in a controlled environment. The thermal time (in chill-days) was calculated and accumulated by a predefined temperature range from fall harvest until the chilling requirement (maximum accumulated chill-days in a negative number) is met. The chilling requirement is then offset by anti-chill days (in positive numbers) until the accumulated chill-days become null, which is assumed to be the budburst date. Calculations were repeated with arbitrary threshold temperatures from $4^{\circ}C$ to $10^{\circ}C$ (at an interval of 0.1), and a set of threshold temperature and chilling requirement was selected when the estimated budburst date coincides with the field observation. A heating requirement (in accumulation of anti-chill days since budburst) for flowering was also determined from an experiment based on historical observations. The dormancy clock model optimized with the selected parameter values was used to predict flowering of Niitaka pear grown in Suwon for the recent 9 years. The predicted dates for full bloom were within the range of the observed dates with 1.9 days of root mean square error.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.342-350
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• 2016

This study aims to make the stand density management diagram which is very useful for establishing systematic management plan and obtaining management goal in Pinus densiflora forest. To estimate 5 models mainly composed of stand density management diagram, we used total of 1,886 sample plots having more than 75% of the total basal area of the pine trees in each stand. To test the goodness of fit, $X^2$ was computed with a significance level of 5%, and the acceptable error range as 20%. Also standard deviation of the model was $34.59m^3{\cdot}ha^{-1}$, minimum acceptable error range was 16.59% and coefficient of variation was 22.11%. If we use the stand density management diagram, it would be useful to establish the timber yield and thinning plan understanding the pathway of stand density management.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.255-259
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• 2022

Solar membrane steam generation is a very promising technology that can harvest purified water from seawater or wastewater during the current danger of running out of pure water. However, solar Membrane steam generation had direct contact with water, making it difficult to increase the efficient amount of evaporation. Here, we propose solar membrane steam generator composed of polydimethylsiloxane (PDMS) and graphene oxide (GO) and improved evaporation through wettability control in part throughout the water-absorbing membrane. Wettability control has shown significant improvements in thermal localization and temperature rise in the area of heat exchange with sunlight. The evaporator has an evaporation rate of 1.54 kg m^-2 h^-1 under 1 sun irradiation. The results showed that Solar membrane steam evaporation can effectively harvest pure water through an increase in evaporation.

• Korean Journal of Agricultural Science
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• v.22 no.1
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• pp.1-10
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• 1995

All agricultural crops and products should be cultured, harvested, handled and processed by the proper mechanical methods in the mechanized farming systems. Agricultural crops might be injured or deformed through various working stages due to static or dynamic forces of machines. Mechanical forces had to be applied with proper degrees to the agricultural crops in incoincidence with properties of crops without any damage of crops so as to increase the work efficiency qualitatively. Knowledges of mechanical properties of agricultural materials are essential to prevent of agricultural crops in relation with mechanical farming system. This study was carried out to examine and analyze the creep behavior of the rice stalk on growing and harvesting periods by mechanical model with computer measurement system in radial directional compressive force and bending force. The creep behavior of the rice stalk could be predicted precisely and its results approached closely to the measured values. The creep behaviors were increased greatly with increase of compressive force, namely, the steady state creep behavior occurred at the force less then 25N and the logarithmic creep behavior at the force bigger than 30N. The instantaneous elastic modulus $E_o$ and the retardation time ${\tau}_K$ were increased together with increase of applied forces, meanwhile the retarded elastic modulus $E_r$ and viscosity ${\eta}_v$ were decreased with increase of applied forces in mechanical model being expected the creep behavior in relation with the level of applied forces, which was well explained that the rice stalk might be visvo-elastic material. In the creep test along the stalk portion with compressive force and bending force, the intermediate portion showed greatest values and also the lower portion showed the least values, which implied that the intermediate portions of rice stalk were very weak. The steady state creep behavior occured at the intermediate portion and the upper portion in the rice stalk at the compressive force larger than 25.0N, which showed the possibility of injury due to external forces.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.709-720
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• 2018

In order to optimize the evaluation of biomass in crop monitoring, accurate and timely data of the crop-field are required. Evaluating above-ground biomass helps to monitor crop vitality and to predict yield. Unmanned Aerial Vehicle (UAV) imagery are being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study reports on the development of remote sensing techniques for evaluating the biomass of winter crop. Specific objective was to develop statistical models for estimating the dry weight of barley and wheat using a Excess Green index ($E{\times}G$) based Vegetation Fraction (VF) and a Crop Surface Model (CSM) based Plant Height (PH) value. As a result, the multiple linear regression equations consisting of three independent variables (VF, PH, and $VF{\times}PH$) and above-ground dry weight provided good fits with coefficients of determination ($R^2$) ranging from 0.86 to 0.99 with 5 cultivars. In the case of the barley, the coefficient of determination was 0.91 and the root mean squared error of measurement was $102.09g/m^2$. And for the wheat, the coefficient of determination was 0.90 and the root mean squared error of measurement was $110.87g/m^2$. Therefore, it will be possible to evaluate the biomass of winter crop through the UAV image for the crop growth monitoring.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.1-11
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• 1999

Rice yield and primary productivity (NPP) are dependent upon the variability of climate and soil. The variability and regionality of the rice yield and net primary productivity were evaluated with the meteorological data collected from Korea Meteorology Administration and the actual rice yield data from the Ministration of Agriculture and Forestry, Korea. The estimated NPP using the three models, dependent upon temperature(NPP-T), precipitation(NPP-P) and net radiation(NPP-R), ranged from 10.87 to 17.52 Mg ha$^{-1}$ with average of 14.69 Mg ha$^{-1}$ in the South Korea and was ranged 6.47 to 15.58 Mg ha$^{-1}$ with average of 12.59 Mg ha$^{-1}$ in the North Korea. The primary limiting factor of NPP in Korea was net radiation, and the secondary limiting factor was temperature. Spectral analysis on the long term change in air temperature in July and August showed periodicity. The short periodicity was 3 to 7 years and the long periodicity was 15 to 43 years. The coefficient of variances, CV, of the rice yield from 1989 to 1998 ranged 3.23 percents to 12.37 percents which were lower than past decades. The CV's in Kangwon and Kyeongbuk were high while that in Chonbuk was the lowest. The prediction model based on th e yield index and yield response to temperature obtain ed from the field crop situation showed reasonable results and thus the spatial distributions of rice yield and predicted yield could be expressed in the maps. The predicted yields was well fitted with the actual yield except Kyungbuk. For better prediction, modification should be made considering radiation factor in further development.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.1-14
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• 2021

Onions are a representative produce that requires supply-demand control measures due to large fluctuations in production and price by growing season. Accurate forecasts of crop production can improve the effectiveness of such measures. However, it is challenging to obtain accurate estimates of crop productivity for onions because they are mainly grown on the open fields. The objective of this study was to perform the empirical analysis of the relationship between factors for crop growth and meteorological conditions, which can support the development of models to predict crop growth and production. The growth survey data were collected from open fields. The survey data included the weight of above ground organs as well as that of the bulbs. The estimates of meteorological data were also compiled for the given fields. Correlation analysis between these factors was performed. The random forest was also used to compare the importance of the meteorological factors by the growth stage. Our results indicated that insolation in early March had a positive effect on the growth of the above-ground. There was a negative correlation between precipitation and the growth of the above-ground at the end of March although it has been suggested that drought can deter the growth of onion. The negative effects of precipitation and daylight hours on the growth of the above-ground and under-ground were significant during the harvest period. These meteorological factors identified by growth stage can be used to develop models for onion growth and production forecast.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.5
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• pp.386-395
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• 2006

The core questions for determining nitrogen topdress rate (Npi) at panicle initiation stage (PIS) are 'how much nitrogen accumulation during the reproductive stage (PNup) is required for the target rice yield or protein content depending on the growth and nitrogen nutrition status at PIS?' and 'how can we diagnose the growth and nitrogen nutrition status easily at real time basis?'. To address these questions, two years experiments from 2001 to 2002 were done under various rates of basal, tillering, and panicle nitrogen fertilizer by employing a rice cultivar, Hwaseongbyeo. The response of grain yield and milled-rice protein content was quantified in relation to RVIgreen (green ratio vegetation index) and SPAD reading measured around PIS as indirect estimators for growth and nitrogen nutrition status, the regression models were formulated to predict PNup based on the growth and nitrogen nutrition status and Npi at PIS. Grain yield showed quadratic response to PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict grain yield had a high determination coefficient of above 0.95. PNup for the maximum grain yield was estimated to be 9 to 13.5 kgN/10a within the range of RVIgreen around PIS of this experiment. decreasing with increasing RVIgreen and also to be 10 to 11 kgN/10a regardless of SPAD readings around PIS. At these PNup's the protein content of milled rice was estimated to rise above 9% that might degrade eating quality seriously Milled-rice protein content showed curve-linear increase with the increase of PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict protein content had a high determination coefficient of above 0.91. PNup to control the milled-rice protein content below 7% was estimated as 6 to 8 kgN/10a within the range of RVIgreen and SPAD reading of this experiment, showing much lower values than those for the maximum grain yield. The recovery of the Npi applied at PIS ranged from 53 to 83%, increasing with the increased growth amount while decreasing with the increasing Npi. The natural nitrogen supply from PIS to harvest ranged from 2.5 to 4 kg/10a, showing quadratic relationship with the shoot dry weight or shoot nitrogen content at PIS. The regression models to estimate PNup was formulated using Npi and anyone of RVIgreen, shoot dry weight, and shoot nitrogen content at PIS as predictor variables. These models showed good fitness with determination coefficients of 0.86 to 0.95 The prescription method based on the above models predicting grain yield, protein content and PNup and its constraints were discussed.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.2
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• pp.272-277
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• 1998

Filtering rates of two farming ascidians Styela clava and S. plicata, and of a farming mussel Mytilus edulis were experimentally investigated with reference to effects of water temperature and size. Absorptiometric determinations of filtering rates were carried out in a closed system with experimental animals being decreased indicate dyes neutral red. Optical density (OD) of 440 nm in path length 22 mm cell used as the indication of food particles absorption was appeared directly in proportion with the concentration of neutral red dyes. The filtering rate F is calculated by Kim's equation $F\;=\;V(1-e^{-z})$, where V is the water volume ($\ell$) in the experimental jar, and Z is the decreasing coefficient of OD as meaning of instantaneous removal speed as In $C_t\;=\;In\;C_{o}-Z{\cdot}t$, in this formula $C_t$ is OD at the time t. Filtering rate of S. clava increased as exponential function with increasing temperature while not over critical limit, and the critical temperature for filtering rate was assumed to be between $28^{\circ}C$ and $29^{\circ}C$. In case of S. plicata, the critical temperature was to be below $13^{\circ}C$, and through the temperature range $15\~25^{\circ}C$ appeared a little difference in level even though with significant. M. edulis was not appear any significant effects by water temperature less than $29^{\circ}C$. The model formula derived from the results is as below, where F is filtering rate (${\ell}/hr/animal$), T is water temperature ($^{\circ}C$), and DW is dry meat weight (g) of experimental animal. $$S.\;Clava;\;F\;=\;e xp\;(0.119\;T-4.540)\;(DW)^{0.6745},\;T<29^{\circ}C$$) $$S.\;plicata;\;F\;=\;e xp\;(A_t)\;(DW)^{0.5675},\;(13^{\circ}C $$[A_t =-8.56+0.6805\;T-0.0153\;T^2]$$ $$M.\;edulis;\;F\;=\;0.3844\;(DW)^{0.4952},\;<29^{\circ}C$$)