• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.21-29
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• 2017

The purpose of this study is to analyze the accuracy of cultivated crop database in agricultural farm business using UAV(Unmanned Aerial Vehicle) and field survey over Daesso-myeon, Umsung-gun, Chungbuk. When comparing with agricultural farm business and cadastral maps, Daeso-myeon crop field shows 29.8%(2,030 parcels out of 6,822 parcels) is either mismatched or missing. It covers almost 19.3%($3.4km^2$ of $17.6km^2$) of total farmland. In order to solve these problems, it is necessary to prepare a multifaceted plan including cadastral map. Comparative analysis of the cultivated crop registered in the agricultural farm business and the field survey agreed only in 3,622 parcels in total 6,822 parcels whereas 3200 parcels disagree. Among these disagreed parcels 2,030(29.8%) have been confirmed as unregistered farm business entity. Accuracy of cultivated crop registered in agricultural farm business agreed in 75.6% cases. Especially the paddy field registration is more accurate that other crops. These discrepancies can lead to false payment in agricultural farm business. For exploration and analysis of regional resources, UAV images can be used together with farm business management database and cadastral map to get a clearer grasp over on-site resources and conditions.

• Korean Journal of Agricultural Science
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• v.31 no.2
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• pp.149-160
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• 2004

This study had carried out an analysis of leaf tobacco production cost by cost items, growing stages, and farm sizes per 10a to provide the basic data for determination of the purchasing price of leaf tobacco by KT&G. Considering the survey results of 12 tobacco farm households, the composition rates of production cost by items revealed as 7-10% for land service, 5-22% for depreciation, 13-25% for material costs, 50-65% for labour cost respectively. The production cost of leaf tobacco by growing stages were shown as 15.3% in nursery bed period, 32.3% in main growing period in field, 30.8% in harvesting period and 21.6% in packing period. The magnitude of wage expenditure was appeared as harvesting stage, packing stage, growing stage on main field and nursery bed stage in order. The amount of material costs were revealed as the growing stage in main field, harvesting stage, nursery bed stage and packing stage respectively. The production costs of leaf tobacco per 10a by farm sizes were shown as 1,615,879won for small farm, 1,446,896won for medium farm and 1,454,408won for large farm respectively. The production cost of leaf tobacco had shown decreasing tendency according to increasing farm sizes. To promote the international market competitiveness of leaf tobacco producing farms, labour saving production technologies and cost effective farm size to decrease tobacco production cost should be developed.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.591-597
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• 1996

To straighten the path that farm machinery follows in paddy fields, it is necessary to measure and evaluate the tracks that these machines leave behind. However, there are no known methods for making such measurements and evaluations since it is difficult to accurately trace the paths that the machine make in paddy fields. Therefore, a measuring system has been developed which can accurately recored the path of a farm machinery in a field by measuring the horizontal straight-line distance from the side of the field to the machine. This system consists of a track subsystem on the machine and a range finder system. A measuring appraratus is installed on a flatcar which runs on rails over 50 m long at the side of the filed. The track subsystem uses a CCD camera to track the movement of the machine in the field which is following a lengthwise path. The range finder subsystem measures the distance that the measuring apparatus has traveled on the rails and the distance from the app ratus to the machine in the field. This system makes it possible to record the path that the machine travels. Even though differences in traveling distance arise between the measuring apparatus and the farm machine, these differences are detected by image processing , which allows the machine in the field to be located accurately. The short(0.05 second) time required for image processing is enough to follow an object . In the present study, this system was able to measure the path that a moving tractor makes. Even though a lag of up to 0.4 meters occurred, this system did not miss its target during operation of the track subsystem. Thus the path measuring system developed here is able to record vehicle paths automatically by following the movement of vehicles in the field and measuring the distance to them. It is expected to come into use in such applications as unmanned moving vehicle tests.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Journal of Microbiology and Biotechnology
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• v.25 no.5
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• pp.709-717
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• 2015

Airborne bacteria from hog farms may have detrimental impacts on human health, particularly in terms of antibiotic resistance and pathogen zoonosis. Despite human health risks, very little is known about the composition and diversity of airborne bacteria from hog farms and hog-related spray fields. We used pyrosequencing analysis of 16S rRNA genes to compare airborne bacterial communities in a North Carolina hog farm and lagoon spray field. In addition, we isolated and identified antibiotic-resistant bacteria from both air samples. Based on 16S rRNA gene pyrosequence analysis, Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria were the dominant phyla in airborne bacterial communities from both hog farm and spray field sites. Within the Firmicutes genera, Clostridium spp. were more abundant in the hog farm, whereas Staphylococcus spp. were higher in the spray field. The presence of opportunitic pathogens, including several Staphylococcus species and Propionibacterium acnes, was detected in both bioaerosol communities based on phylogenetic analysis. The isolation and identification of antibiotic-resistant bacteria from air samples also showed similar results with dominance of Actinobacteria and Proteobacteria in both hog farm and spray field air. Thus, the existence of opportunistic pathogens and antibiotic resistant bacteria in airborne communities evidences potential health risks to farmers and other residents from swine bioaerosol exposure.

• Journal of Biosystems Engineering
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• v.24 no.6
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• pp.493-500
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• 1999

In 1990's, two types of land consolidation has been widely carried out to enforce competativeness of rice production in Korea. One is so called large-scale land consolidation for resizing paddy field and farm road, the other is general land consolidation for changing both size and shape of field, water channel and farm road. This study was conducted to evaluate how much effect on fm mechanization the land consolidation had. To evaluate the influence of the land consolidation, theoretical analysis and surveys were accomplished. Land consolidation was analyzed to increase field efficiency by 180 to 670% depending on the type of land consolidation and machine selection. Also, land consolidation brought increment of real working time ratio by reducing traveling time on farm road. Trends of large scale mechanization and increment of custom work were observed to be accelerated by land consolidation. It also gave effect on the pattern of machine troubles. Farmers were conscious of the influence of land consolidation on machine utilization, however, in plains level of satisfaction was shown to be low.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.254-261
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• 2000

Soil chemical properties, relief of field surface, SPAD values and grain yield were investigated in a 0.5ha paddy field in 1999 to obtain basic field information for precision agriculture. Descriptive statistics of field information showed that the coefficient of variation ranged from 1.63% to 38.7%. Field information showed a high spatial dependence for within paddy field. The ranges of spatial dependence were from 15m to 60m, respectively. Kriged maps enable the visualization and comparison the spatial variability of field information. The causes of spatial variability of the field information could be explained rationally by a field management map. Grain yield was negatively correlated with pH, relief values, whereas, was positively correlated with total C, total N, C/N ratio, mineralizable N, available P and exchangeable K, Ca at the significant level of 1 %.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.203-215
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• 2022

The study is to investigate research trends and knowledge structures in the Smart Farm field. To achieve the research purpose, keywords and the relationship among keywords were analyzed targeting 104 Korean academic journals related to the Smart Farm in KCI(Korea Citation Index), and topics were analyzed using the LDA Topic Modeling technique. As a result of the analysis, the main keywords in the Korean Smart Farm-related research field were 'environment', 'system', 'use', 'technology', 'cultivation', etc. The results of Degree, Betweenness, and Eigenvector Centrality were presented. There were 7 topics, such as 'Introduction analysis of Smart Farm', 'Eco-friendly Smart Farm and economic efficiency of Smart Farm', 'Smart Farm platform design', 'Smart Farm production optimization', 'Smart Farm ecosystem', 'Smart Farm system implementation', and 'Government policy for Smart Farm' in the results of Topic Modeling. This study will be expected to serve as basic data for policy development necessary to advance Korean Smart Farm research in the future by examining research trends related to Korean Smart Farm.

• Korean Journal of Agricultural Science
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• v.28 no.1
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• pp.41-47
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• 2001

Farm management consulting is recently widely recognized as farm business becomes more commercial. For better consulting practice, this paper analyzes current status of consulting practice and then suggests few strategies for consulting practice. Firstly, basic farm managements consulting should be strengthen, which have been done by technological center in local governments. Secondly, farm management consulting institutions must be specialized, in terms of role for each institution. Thirdly, we should train and produce more consultants specialized in field needs. Finally, aftermath program have to be developed for estimating consulting benefits.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1145-1156
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• 2015

There is a shortage of mobile application systems readily applicable to the field of crop cultivation in relation to diseases and insect pests directly connected to the quality of crops. Most of system have been devoted to diseases and insect pests that would offer full predictions and basic information about diseases and insect pests currently. But for lack of the instant diagnostic functions seriously and the field of crop cultivation, we design and implement a crop cultivation field-oriented smart diseases and insect pests information retrieval system based on mobile for u-Farm. The proposed system had such advantages as providing information about diseases and insect pests in the field of crop cultivation and allowing the users to check the information with their smart-phones real-time based on the Lucene, a search library useful for the specialized analysis of images, and JSON data structure. And it was designed based on object-oriented modeling to increase its expandability and reusability. It was capable of search based on such image characteristic information as colors as well as the meta-information of crops and meta-information-based texts. The system was full of great merits including the implementation of u-Farm, the real-time check, and management of crop yields and diseases and insect pests by both the farmers and cultivation field managers.