• Journal of Bio-Environment Control
• /
• v.11 no.1
• /
• pp.18-22
• /
• 2002

Diseases occurrence of hydroponic culture was less than that of soil culture, especially gummy stem blight, which was 39.9-53.3% of infection rate at soil culture, was not almost observed at hydroponic culture. Development of fermented fruit was higher at Shintozoa, Hongtozoa and self-rooting seedling in order at soil cultured but critically dropped at hydroponic culture without rootstock sort. Therefore proper moisture management at root zone can decrease the development of fermented fruit.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.153-153
• /
• 2019

Evapotranspiration (ET) is an important component of hydrological processes. Accurate estimates of ET variation are of vital importance for natural hazard adaptation and water resource management. This study first developed a soil water index (SWI)-based Priestley-Taylor algorithm (SWI-PT) based on the enhanced vegetation index (EVI), SWI, net radiation, and temperature. The algorithm was then compared with a modified satellite-based Priestley-Taylor ET model (MS-PT). After examining the performance of the two models at 10 flux tower sites in different land cover types over East Asia and Australia, the daily estimates from the SWI-PT model were closer to observations than those of the MS-PT model in each land cover type. The average correlation coefficient of the SWI-PT model was 0.81, compared with 0.66 in the original MS-PT model. The average value of the root mean square error decreased from $36.46W/m^2$ to $23.37W/m^2$ in the SWI-PT model, which used different variables of soil moisture and vegetation indices to capture soil evaporation and vegetative transpiration, respectively. By using the EVI and SWI, uncertainties involved in optimizing vegetation and water constraints were reduced. The estimated ET from the MS-PT model was most sensitive (to the normalized difference vegetation index (NDVI) in forests) to net radiation ($R_n$) in grassland and cropland. The estimated ET from the SWI-PT model was most sensitive to $R_n$, followed by SWI, air temperature ($T_a$), and the EVI in each land cover type. Overall, the results showed that the MS-PT model estimates of ET in forest and cropland were weak. By replacing the fraction of soil moisture ($f_{sm}$) with the SWI and the NDVI with the EVI, the newly developed SWI-PT model captured soil evaporation and vegetation transpiration more accurately than the MS-PT model.

• Korean Journal of Plant Resources
• /
• v.32 no.5
• /
• pp.478-485
• /
• 2019

As environmentally sound agriculture emphasize gradually as well as the importance of environment, many studies on weed and soil nematode control of new concept which does not affect adversely environment are in progress. For this purpose, plant seeds which are representative weed species in field were selected and treated with microwave having generating capacity of $17.73kw/m^3$, and investigated germination rates of weed seeds and the number of soil nematode according to soil moisture contents, soil depth and irradiation times. The microwave effect on the germination rates was extremely high in soil moisture content of 40% and irradiation time over 40 seconds for irradiation time, while soil depth did not affect germination rate. In view of the results so far achieved, it seems that universal dispersed microwave system is effective for the control of weed seeds.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1611-1623
• /
• 2021

Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R² were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R² were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.

• Journal of People, Plants, and Environment
• /
• v.23 no.6
• /
• pp.655-665
• /
• 2020

Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.1
• /
• pp.1-9
• /
• 2011

In this paper, Wireless sensor network technology applied to various greenhouse agro-industry items such as horticulture and local specialty etc., we was constructed automatic control system for optimum growth environment by measuring growth status and environmental change. existing monitoring systems of greenhouse gather information about growth environment depends on the temperature. but in this system, Can be efficient collection and control of information to construct wireless sensor network by growth measurement sensor and environment monitoring sensor inside of the greenhouse. The system is consists of sensor manager for information processing, an environment database that stores information collected from sensors, the GUI of show the greenhouse status, it gather soil and environment information to soil and environment(including weather) sensors, growth measurement sensor. In addition to support that soil information service shows the temperature, moisture, EC, ph of soil to user through the interaction of obtained data and Complex Growth Environment information service for quality and productivity can prevention and response by growth disease or disaster of greenhouse agro-industry items how temperature, humidity, illumination acquiring informationin greenhouse(strawberry, ginseng). To verify the executability of the system, constructing the complex growth environment measurement system using wireless sensor network in greenhouse and we confirmed that it is can provide our optimized growth environment information.

• Journal of Korean Society of Disaster and Security
• /
• v.7 no.2
• /
• pp.1-8
• /
• 2014

Smart Pole Measurement System was constructed with not only the core sensors of a GNSS receiver, a TRS sensor and a soil moisture sensor but supplementary installation of power supply and radio communication for monitoring steep slope sites. Also a data processing software for displacement extraction and visualization was developed. Smart Pole Measurement sensor is composed of a GNSS antenna at the top of the pole, a TRS sensor and a gyro sensor vertical below right of the antenna and a soil moisture sensor at the bottom of the pole. The sensor combination extracts not only ground combination in real time but transltion, slide, settlement and soil moisture content. This measuring/monitoring system which cosists of data receiving part, data collection/transfer part and data processing part was built to exercise their functions and then test measuring/monitoring was conducted by introducing artificial displacement and the results were analyzed to evaluate field applicability.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.56 no.5
• /
• pp.77-87
• /
• 2014

The impacts of climate change on upland crops is great significance for water resource planning, estimating crop water demand and irrigation scheduling. The objective of this study is to predict upland crop evapotranspiration, effective rainfall and net irrigation requirement for upland under climate change, and changes in the temporal trends in South Korea. The changes in consumptive use and net irrigation requirement in the six upland crops, such as Soybeans, Maize, Potatoes, Red Peppers, Chinese Cabbage (spring and fall) were determined based on the soil moisture model using historical meteorological data and climate change data from the representative concentration pathway (RCP) scenarios. The results of this study showed that the average annual upland crop evapotranspiration and net irrigation requirement during the growing period for upland crops would increase persistently in the future, and were projected to increase more in RCP 8.5 than those in RCP 4.5 scenario, while effective rainfall decreased. This study is significant, as it provides baseline information on future plan of water resources management for upland crops related to climate variability and change.

• Journal of Korea Water Resources Association
• /
• v.51 no.5
• /
• pp.417-424
• /
• 2018

This study analyzed the effect of irrigation reservoirs, antecedent soil moisture conditions (AMC) and Huff time distribution on peak discharge using Monte Carlo simulation. The peak discharge was estimated for four different cases in combination of irrigation reservoir capacity, AMC, and Huff time distribution. Applying 100% reservoir capacity or AMC-III, the peak discharges corresponding return periods of 50~300 years were overestimated by 25~30% compared to those of cases that considered the probability of occurrence for individual condition. Applying the 3rd quantile huff distribution, the peak discharges were overestimated by 5% over the peak discharge that considered the probability of occurrence. The overall results indicated that the effect on the peak flood of Huff distribution was less than AMC and reservoir storage.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2023.04a
• /
• pp.79-79
• /
• 2023

With the development of digital technology, the size of the smart agriculture market at home and abroad is rapidly expanding. It is necessary to establish a foundation for sustainable precision agriculture in order to respond to the aging of rural areas and labor shortages. This study was conducted to establish an automated digital agricultural test bed for soybean production management using data suitable for agricultural environmental conditions in Korea and to demonstrate the field of leading complexes. In order to manage water smartly, we installed a subsurface drip irrigation system in the upland field and an underground water level control system in the paddy field. Based on data collected from sensors, water management was controlled by utilizing an integrated control system. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. The main growth characteristics and yield, such as stem length, number of branches, and number of nodes of the main stem, were investigated during the main growth period. During the operation of the test bed, drought appeared during the early vegetative growth period and maturity period, but in the open field smart agriculture test bed, water was automatically supplied, reducing labor by 53% and increasing yield by 2%. A test bed was installed for each field digital farming element technology, and it is planned to verify it once more this year. In the future, we plan to expand the field digital farming technology developed for leading farmers to the field.