• Korean Journal of Environmental Agriculture
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• v.36 no.1
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• pp.1-6
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• 2017

BACKGROUND: Bone meal is commonly used as a phosphorus (P) fertilizer in organic farming. Effectiveness of bone meal was compared with mineral P fertilizer to elucidate the optimum application rates of bone meal in crop production. METHODS AND RESULTS: The effects of bone meal and fused phosphate on plant growth and P uptake were determined in a pot experiment with maize (Zea mays L.) in a clay loam soil. Bone meal and fused phosphate were applied at 150 and 300 mg $P_2O_5/kg$ soil, and maize was grown for 3 consecutive growth periods of 4 to 5 weeks each. As compared with fused phosphate, total shoot growth of maize per pot was 3-6% lower in bone meal fertilization, and the difference was not significant in the application of 300 mg $P_2O_5/kg$. At the same P application rate, uptake of P by maize plants was 7-9% lower in bone meal treatment. The P use efficiency in bone meal treatments ranged from 11.9-13.6%, equivalent to 73-84% of the efficiency for fused phosphate treatments. CONCLUSION: The equivalence of immediate effectiveness of bone meal as a P fertilizer was at least 90% compared with fused phosphate in the pot experiment with maize. The results indicate that bone meal could be a reasonable alternative to chemical P fertilizers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.307-316
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• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.

• Applied Biological Chemistry
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• v.18 no.2
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• pp.65-70
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• 1975

The cultivation of ginseng plant (Panax ginseng C.A. Meyer) in Korea as an eminent medicinal herb may be traced far back in history. However, the practices in cultivation have not much improved in terms of efficiency and scientific farming. In the present study some experiments were undertaken for the search of the soil and nutrition conditions, because of the nutritional requirement of ginseng plant shaws quite unique compared with other crops. In both the seed bed and the field 'Yakto' has been traditionally employed or the prime source of nutrition of the crop. Yakto is a complex matter prepared from raw foliage of the broad-leaved trees as the main portion with the admixture of a variety of organic nitrogen source through fermentative processes. The composition of Yakto may be classified coarsely into the decomposed and undecomposed substances, the former being further fractionated according their solubilities, comprising also various colloidal matters whose composition and structure are yet to be known. The Yakto-fractions were subjected to analyze for search of its nature and coarse composition in terms of the distribution of nitrogen, contents of organic functional groups such as -COOH, phenolic-OH, alcholic-OH and methoxyl and hydrolysable sugars. Furthermore, absorption-spectra of each fraction were determined in visible and infrared region and compared the results each other.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.75-86
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• 2020

The purpose of this study is to develop a technology for estimating rice growth and damage effect according to bacterial leaf blight using UAV multi-spectral imagery. For this purpose, we analyzed the change of aerial images, rice growth factors (plant height, dry weight, LAI) and disease effects according to disease occurrence by using UAV images for 3 rice varieties (Milyang23, Sindongjin-byeo, Saenuri-byeo) from 2017 to 2018. The correlation between vegetation index and rice growth factor during vegetative growth period showed a high value of 0.9 or higher each year. As a result of applying the growth estimation model built in 2017 to 2018, the plant height of Milyang23 showed good error withing 10%. However, it is considered that studies to improve the accuracy of other items are needed. Fixed wing unmanned aerial photographs were also possible to estimate the damage area after 2 to 4 weeks from inoculation. Although sensing data in the multi-spectral (Blue, Green, Red, NIR) band have limitations in early diagnosis of rice disease, for rice varieties such as Milyang23 and Sindongjin-byeo, it was possible to construct the equation of infected leaf area ratio and rice yield estimation using UAV imagery in early and mid-September with high correlation coefficient of 0.8 to 0.9. The results of this study are expected to be useful for farming and policy support related to estimating rice growth, rice plant disease and yield change based on UAV images.

• Food Science and Preservation
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• v.9 no.4
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• pp.357-361
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• 2002

This study was carried out to understand the problems, and find out the solution of post - Harvest related procedures for barley in Korea. Consecutive post - harvest procedures in harvesting, drying, milling, packaging and marketing methods were collaborately surveyed at Bujeok (Chungchongnamdo) and Kunsuh (Cholanamdo) agricultural cooperative federation where Chalssalbori (waxy barley) and Ssalbori (non waxy barley) were collectively cultivated in a group farming area, respectively. An early harvesting and relatively short harvesting period within 15 to 20 days to transplanting rice plants as a succeeding crop lead to produce undergrade barley and 2 to 3％ harvesting loss were considered as the problem that should be improved. In drying of barley, wide moisture content range of harvested barley among the different farmers and cultivation land was made difficult barley drying unifomly when they were dried in same dryer and drying temperature was slightely higher with 50 to 70$\^{C}$ than that of optimum temperature (under 50$\^{C}$) fer barley drying for producing the high quality barley. Dried barley packaged in ton-bag or 3P bag and put into the rectangular grain bin were stored in ambient temperature warehouse and milled for marketing through whole you. The physico-chemical properties and taste of stored barley were fairly maintained until May next year.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.285-290
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• 2016

In rural area, our farmers confront decreasing benefits owing to imported crops and increased cost. Recently, the government encourage the 6th Industry that merges farming, rural resources, and information and communication technology. Therefor the government makes an investment in supplying 'smart greenhouse' in which a farmer monitor growing crops and environment information to control growing condition. The objective of this study is developing an Moving Monitor and Control System for crops in green House. This system includes a movable sensing unit, a controlling unit, and a server PC unit. The movable sensing unit contains high resolution IP camera, temperature and humidity sensor and WiFi repeater. It rolls on a rail hanging beneath the ceiling of a green house. The controlling unit contains embedded PC, PLC module, WiFi router, and BLDC motor to drive the movable sensing unit. And the server PC unit contains a integrated farm management software and home pages and databases in which the images of crops and environment informations. The movable sensing unit moves widely in a green house and gathers lots of information. The server saves these informations and provides them to customers with the direct commercing web page. This system will help farmers to control house environment and sales their crops in online market. Eventually It will be helpful for farmers to increase their benefits.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.1-13
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• 2021

The concept of integrated pest management (IPM) first developed in the 1950s, and the concept of economic control via pest management was established in the 1960s. Research on IPM began in the United States and Europe, and IPM studies in Korea started with citrus insects and paddy field pests following the distribution of high-yield varieties of rice. Apple IPM in Korea began with research on pest control using chemical pesticides and pesticides resistant to insect pests, studies on the ecology of insect pests and their natural enemies, and the exploitation of sex pheromones on insect pests. Since the 1990s, IPM research and field projects have been carried out simultaneously for farming households. In the 2000s, the development of pest monitoring and forecasting models centered on mating disturbances, database programs for pests, and networks for sharing information. IPM technology has expanded via the development of unmanned forecasting systems and automation technologies in the 2010s.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.71-85
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• 2022

The food self-sufficiency rate of agricultural products in Korea, excluding rice, is around 20%, and the government is promoting various policies including a Multiple-Purpose Utilization of Paddy Fields project, to increase the self-sufficiency rate of major grains. The project for Multiple-Purpose Utilization of Paddy Fields is being promoted as a part of a program to create farmland infrastructure to facilitate the cultivation of crops other than rice in rice paddies, and pilot projects were started in four regions in 2020. The purpose of this study is to analyze the economic effects of the pilot project for Multiple-Purpose Utilization of Paddy Fields, and to propose policies to increase the effectiveness of the project. In order to analyze the economic effect, we estimated the change in farm income generated by switching from rice to other crops, and measured the effect of welfare change using the Equilibrium Displacement Model (EDM). As a result of the analysis, social welfare is expected to increase when the pilot project for Multiple-Purpose Utilization of Paddy Fields is implemented, and the income of the beneficiary farmers is also expected to improve compared to that of single-cropping when double-cropping is implemented. However, it was found that the economic feasibility of the project differs depending on the crops converted. Juksan-myeon, Gimje-si, which is an area where soybean production was successful, was analyzed from the viewpoint of increasing the economic feasibility of the pilot project. Their success factors were analyzed into four major factors: infrastructure, farming methods, education, and collaboration with local agricultural organizations. If such a success story can be utilized in the future project implementation process, it can contribute to the improvement of farm household income and national economic welfare.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.