• The Journal of Information Systems
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• v.31 no.2
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• pp.45-62
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• 2022

Purpose Smart farms play a leading role in changing the safety food culture for the citizens. The purpose of this study is to investigate the factors that are important to covid 19-response in the case of ICT smart farm. To do so, we classified the factors as operating effect aspect and industrial wave effect aspect of the smart farm. Design/methodology/approach This study was conducted by visiting Geumsan County, which is attempting to perform a smart farm. Through interviewing farmers representatives based on their operational effect expectations on the smart farm, we derived the industrial crash effect factors and thereafter designed the research model. This study applied AHP, which is an expert decision-making method cans be used to measure relative importance for determining priorities. After interviewing the experts with smart farm, we obtained the factors which are important to smart farm development. Findings According to analysis, the productivity improvement factor was ranked as the most important among the operational effect items. This is consistent with the ultimate goal of smart farms with ICT convergence technology, which is increase the profitability of agriculture. The second place is the factor in the development of infrastructure and infrastructure, and the third and fifth positions were export expansion, environmentally friendly management, and job creation in terms of operational effectiveness.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.263-269
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• 1996

In indian agricultural , the energy use pattern has played dominant role in influencing the level of mechanization . Besides that the agro-climatic factors as well as the size of holdings do affect the degree of mechanization . Nearly 30 percent of total cultivated area is owned by l76 percent of the small and tiny land holders each owning even less than a hectare. On the other hand, about 2 percent of land owners cultivate land. These variabilitieshave greatly influenced the ownership of power sources on Indian farms. Small farmers, employ human and animal energies with the use of hand tools and animal drawn equipments. Whereases, the use of tractors, power tillers, electric motors, etc. on small farms is on a marginal scale. There are few pockets and also extensive wheat growing regions where mechanical and electrical power sources are extensively used in production agriculture leading to about 185% of cropping intensity . In that region, the animal energy is employed for on the farm transport of fertilizers, fodders and fuel to support milch animals and other household activities . Inspite of high degree of mechanization, the harvesting of crops is done by human labour with few exceptions of harvesting wheat crops by combines in few pockets. In overall assessment of mechanization, the following conclusions are drawn : ⅰ) Farm operation which show a growing trend of mechanization are (a) tillge, (b) seedling (c) Irrigation (d) Plant protection application (e) Threshing and (f) Transport . ⅱ) Crop cultivation system in respect of wheat, maize and sorghum have been greatly mechanized. ⅲ) The least mechanized cropping systems are (a) vegetable production and (b) cultivation of sugarcane, cotton, rice and pulses. ⅳ) Annual production of tractor has touched the figure of 280.000 by 1995 and the total number has crossed 1.5million on Indian farms.

• Journal of Bio-Environment Control
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• v.27 no.2
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• pp.166-172
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• 2018

This study set out to conduct a field survey with smart greenhouse-based farms in seven types to figure out the actual state of smart greenhouses distributed across the nation before selecting a system to implement an optimal greenhouse environment and doing a research on higher productivity based on data related to crop growth, development, and environment. The findings show that the farms were close to an intelligent or advanced smart farm, given the main purposes of leading cases across the smart farm types found in the field. As for the age of farmers, those who were in their forties and sixties accounted for the biggest percentage, but those who were in their fifties or younger ran 21 farms that accounted for approximately 70.0%. The biggest number of farmers had a cultivation career of ten years or less. As for the greenhouse type, the 1-2W type accounted for 50.0%, and the multispan type accounted for 80.0% at 24 farms. As for crops they cultivated, only three farms cultivated flowers with the remaining farms growing only fruit vegetables, of which the tomato and paprika accounted for approximately 63.6%. As for control systems, approximately 77.4% (24 farms) used a domestic control system. As for the control method of a control system, three farms regulated temperature and humidity only with a control panel with the remaining farms adopting a digital control method to combine a panel with a computer. There were total nine environmental factors to measure and control including temperature. While all the surveyed farms measured temperature, the number of farms installing a ventilation or air flow fan or measuring the concentration of carbon dioxide was relatively small. As for a heating system, 46.7% of the farms used an electric boiler. In addition, hot water boilers, heat pumps, and lamp oil boilers were used. As for investment into a control system, there was a difference in the investment scale among the farms from 10 million won to 100 million won. As for difficulties with greenhouse management, the farmers complained about difficulties with using a smart phone and digital control system due to their old age and the utter absence of education and materials about smart greenhouse management. Those difficulties were followed by high fees paid to a consultant and system malfunction in the order.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1023-1025
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• 2019

Coal and Natural gas are two biggest contributors to a generation of energy throughout the world. Most of these resources create environmental pollution while making energy affecting the natural habitat. Many approaches have been proposed as alternatives to these sources. One of the leading alternatives is Solar Energy which is usually harnessed using solar farms. In artificial intelligence, the most researched area in recent times is machine learning. With machine learning, many tasks which were previously thought to be only humanly doable are done by machine. Neural networks have two major subtypes i.e. Convolutional neural networks (CNN) which are used primarily for classification and Recurrent neural networks which are utilized for time-series predictions. In this paper, we predict energy generated by solar fields and optimal angles for solar panels in these farms for the upcoming seven days using environmental and historical data. We experiment with multiple configurations of RNN using Vanilla and LSTM (Long Short-Term Memory) RNN. We are able to achieve RSME of 0.20739 using LSTMs.

• Journal of Preventive Veterinary Medicine
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• v.42 no.4
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• pp.148-156
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• 2018

Clostridium perfringens (C. perfringens) may cause diarrhea and enterotoxemia in adult and young livestock, leading to problems in the production and management of farms. Four hundred fecal samples were collected from 25 goat farms located in Gyeongsangbuk-do Province in the Republic of Korea. Sixteen C. perfringens strains were isolates from fecal samples, and the isolates were identified as type A (n=11) and type D (n=5). Additionally, ${\alpha}$- and ${\varepsilon}$-toxin genes were detected in 16 and 5 strains by PCR, respectively, and the enterotoxin gene was presented in 2 strains. The antibiotic susceptibility test was performed using the disk diffusion method and E-test method. In the disk diffusion method, ampicillin (n=16) and chloramphenicol (n=15) were highly susceptible to 16 C. perfringens isolates. In the E-test method, ampicillin, amoxicillin, amoxicillin/clavulanic acid and meropenem were susceptible to more than 14 of 16 C. perfringens isolates. This study indicates that administration of antibiotics such as ampicillin, amoxicillin/clavulanic acid and meropenem can prevent and treat C. perfringens infections in goats.

• The Plant Pathology Journal
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• v.39 no.6
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• pp.614-624
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• 2023

Botrytis cinerea is a major fungal plant pathogen that causes gray mold disease in strawberries, leading to a decrease in strawberry yield. While benzimidazole is widely used as a fungicide for controlling this disease, the increasing prevalence of resistant populations to this fungicide undermines its effectiveness. To investigate benzimidazole resistant B. cinerea in South Korea, 78 strains were isolated from strawberries grown in 78 different farms in 2022, and their EC₅₀ values for benzimidazole were examined. As a result, 64 strains exhibited resistance to benzimidazole, and experimental tests using detached strawberry leaves and the plants in a greenhouse confirmed the reduced efficacy of benzimidazole to control these strains. The benzimidazole resistant strains identified in this study possessed two types of mutations, E198A or E198V, in the TUB2 gene. To detect these mutations, TaqMan probes were designed, enabling rapid identification of benzimidazole resistant B. cinerea in strawberry and tomato farms. This study utilizes TaqMan real-time polymerase chain reaction analysis to swiftly identify benzimidazole resistant B. cinerea, thereby offering the possibility of effective disease management by identifying optimum locations and time of application.

• Korean Journal of Veterinary Service
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• v.45 no.3
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• pp.211-219
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• 2022

Bovine viral diarrhea (BVD) is one of the problematic wasting diseases in cattle leading to huge economic losses. This study was conducted to investigate the prevalence of BVD including transient and persistent infection from cattle farms in Gyeongsangnam-do. A total of 2,667 blood samples from 24 farms were collected and the sera were subjected to ELISA to detect BVD virus (BVDV) antigen, E^rns. 5' untranslated region (5'-UTR) of BVDV-positive samples was sequenced to identify the genotype, and compared with isolates previously reported elsewhere. There were fourteen BVDV-positive calves from 2,667 samples (positive rate: 0.52%) from first ELISA testing followed by eight persistently infected out of eleven BVDV-positive samples (72.73%) in secondary ELISA that was conducted in at least four weeks suggesting the circulation of BVDV in the area. Sequencing analysis exhibited that thirteen BVDV-positive samples were identified as BVDV-1b and one sample was BVDV-2a. Phylogenetic analysis revealed that the BVDV-1b-positive samples showed the highest homology in nucleotide sequence to Korean isolates collected from Sancheong, Gyeongsangnam-do, while the BVDV-2a-positive sample (21GN7) was more similar to reference strains collected outside South Korea. This study will provide the recent fundamental data on BVD prevalence in Gyeongsangnam-do to be referred in developing strategies to prevent BVDV in South Korea.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.355-356
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• 2015

This paper proposes a control strategy of total output power ripple cancellation for both of Machine-Side Converter (MSC) and Grid-Side Converter (GSC) in a DFIG under unbalanced grid conditions. The proposed control strategy for the MSC is the zero torque ripple control algorithm with an enhanced LVRT capability. The control algorithm for the MSC exhibits reduced torque pulsation in steady-state unbalanced grid conditions. In addition, this control algorithm also minimizes a peak value of rotor current in transient unbalanced grid conditions. The total output power ripple cancellation control algorithm is adopted in the GSC. The total output power ripple cancellation is achieved by nullifying the oscillating component of the total output active and reactive power at the summing point of stator and rotor of DFIG. The proposed control strategy for the GSC reduces the output power oscillation leading to the improved quality of wind farms output.

• International Journal of Industrial Entomology and Biomaterials
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• v.3 no.2
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• pp.117-120
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• 2001

In India, mulberry (Morus spp.), the sole food plant of the silkworm, Bombyx mori (Linn.), is prone to infestation by the pink mealybug, Maconellicoccus hirsutus (Green). Infestation by this pest causes apical shoot malformation, popularly known as 'tukra'. Occurrence of tukra causes an appreciable reduction in leaf yield and quality, leading to low silkworm cocoon productivity. For management of M. hirsutus (Tukra), an IPM package comprising mechanical, chemical and biological measures was demonstrated in the mulberry gardens of five Government Silk Farms in Mysore District (Karnataka, India) during 1995-96. A suppression of 76.0% in tukra incidence and 90.19% in mealybug population was recorded by employ the IPM package which led to an estimated 4,000 kg recovery in leaf yield/ha/year. The impact of IPM package in the management of M. hirsutus, the role of biocontrol agent (Cryptolaemus montrouzieri Muls.) in pest suppression and the cost-benefit analysis of the IPM package are discussed.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.190-195
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• 2021

Currently, one of the fields leading the 4th industrial revolution is the image recognition field of artificial intelligence, which is showing good results in many fields. In this paper, using is a YOLO V2 model, which is one of the image recognition models, we intend to classify and select into three types according to the characteristics of fruits. To this end, it was designed to proceed the number of iterations of learning 9000 counts based on 640 mandarin image data of 3 classes. For model evaluation, normal, rotten, and unripe mandarin oranges were used based on images. We as a result of the experiment, the accuracy of the learning model was different depending on the number of learning. Normal mandarin oranges showed the highest at 60.5% in 9000 repetition learning, and unripe mandarin oranges also showed the highest at 61.8% in 9000 repetition learning. Lastly, rotten tangerines showed the highest accuracy at 86.0% in 7000 iterations. It will be very helpful if the results of this study are used for fruit farms in rural areas where labor is scarce.