• Journal of Biosystems Engineering
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• v.14 no.2
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• pp.128-136
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• 1989

The purpose of this study was to develop a computer operated automatic drip irrigation system for application in vinyl-house cultivation. The results can be summarized as follows: 1) The T-type ice compensation wire was used to measure the temperature. The voltage level measured up to 0.02 volt was used as input to an 8-bit A/D converter. 2) A specially devised tensiometer was used to content the watering system. When the needle of the pressure gauge reaches the lower threshold position it turns on the pumping system and turns off when it reaches higher threshold position. 3) In order to use the multiple gypsum blocks for one transducer, reed relays and a D/O board were used to make the sequential switching possible. 4) It was possible to automate the trickle irrigation system for the whole growth period of vinyl-house crops with the help of microcomputer. 5) In terms of furrow irrigation, the irrigation water consumption was the smallest, 2.8 times less than conventional method of surface trickle irrigation, 3.4 times less than subsurface trickle irrigation method. 6) In terms of productivity of cucumber, there was a drop in productivity when compared to furrow irrigation method, 7.2% for surface trickle irrigation, 27.4% for subsurface irrigation method.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.87-87
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• 2022

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.88-88
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• 2023

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.10a
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• pp.144-144
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• 2021

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.2
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• pp.87-97
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• 2007

The aim of this study was to compare crop contamination between two irrigation methods using microbial-contaminated water. The effect of relative humidity on microbial survival of the three indicator microorganisms was also investigated. Escherichia coli ATCC 25922, Clostridium perfringens ATCC 3624, and coliphage PRD1 were applied to irrigation water to grow cantaloupe, lettuce, and bell pepper. Half of the sixteen plots were subsurface drip irrigated (SDI) and the other half were furrow irrigated (FI). Two relative humidity levels were controlled at 15-65 % and 55-80 % for the dry and humid condition experiments, respectively. Samples of produce, surface soil, and subsurface soil at a depth of 10 cm were collected over a two-week period following the application of the study microorganisms. Overall, greater contamination of both produce and soil occurred in the FI plots. For the SDI plots, preferential water paths and resulting water appearance on the seed beds seemed to be responsible for produce contamination. Relative humidity levels did not appear to affect microbial survival in soil. PRD 1 showed lower inactivation rates than 5. coli in both dry and humid conditions. C. perfringens did not experience significant inactivation over the experimental period, suggesting this microorganism can be an effective indicator of fecal contamination.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.4
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• pp.253-259
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• 2013

The use of subsurface drip fertigation using slurry composting bio-filtration (SCB) as nitrogen (N) fertilizer source can be beneficial to improve fertilizer management decision. The objective of this study was to evaluate effects of SCB liquid fertilizer by subsurface drip fertigation on cucumber (Cucumis sativus L.) yield and soil nitrogen (N) distribution under greenhouse condition. Cucumber in greenhouse was transplanted on April $4^{th}$ and Aug $31^{st}$ in 2012. N sources were SCB and urea. Four N treatments with 3 replications consisted of control (No N fertilizer), SCB 0.5N + Urea 0.5N (50:50 split application), SCB 1.0N, Urea 1.0N. 100% of N recommendation rate from soil testing was denoted as 1.0N. The subsurface drip line and a tensiometer were installed at 30 cm soil depth. An irrigation was automatically started when the tensiometer reading was -15 kPa. The growth of cucumber at 85 days after transplanting was 5% higher in all N treatment than control. Semi-forcing culture produced more fruit yield than retarding culture. Fruit yields were 62.2, 76.3, 76.4, and 75.1 Mg $ha^{-1}$ for control, SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, respectively. Although fruit yields were similar under SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, 176 kg K $ha^{-1}$ can be over applied if cucumber is grown twice a year under SCB 1.0N that may result in K accumulation in soil. N uptake was 172, 209, 213, 207 kg $ha^{-1}$ for control, SCB 1.0N, Urea 1.0N, and SCB 0.5N + Urea 0.5N, respectively. N use efficiency was the highest (37%) at SCB 0.5N + Urea 0.5N under semi-forcing culture. Nitrate-N concentration in soil for all N treatments except control in semi-forcing culture was the highest between 15 and 30 cm soil depth at the 85 days after transplanting and between 0 and 15 cm soil depth after cucumber harvest. These results suggested that SCB 0.5N + Urea 0.5N can be used as an alternative N management for cucumber production in greenhouse if K accumulation is concerned.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. 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. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

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