• Korean Journal of Agricultural Science
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• v.50 no.2
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• pp.235-248
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• 2023

Orchidaceae species account for one-tenth of all angiosperms including more than 30,000 species having significant ecological, evolutionary, and economic importance. Despite Orchidaceae being one of the largest families among flowering plants, crucial cytogenetic information for studying species diversification, inferring phylogenetic relationships, and designing efficient breeding strategies is lacking, except for 10% or less of orchid species cases involving mostly chromosome number or karyotype analysis. Also, only approximately 1.5% of the identified orchid species from less than a hundred genera have genome size data that provide crucial information for breeders and molecular geneticists. Various molecular cytogenetic techniques, such as fluorescence in situ hybridization (FISH) and genomic in situ hybridization (GISH), have been developed for determining ploidy levels, analyzing karyotypes, and evaluating hybridity, in several ornamental crops including orchids. The estimation of genome size and the determination of nuclear DNA content using flow cytometry have also been employed in some Orchidaceae subfamilies. These different techniques have played an important role in supplementing beneficial knowledge for effective plant breeding programs and other related plant research. This review focused on orchid breeding summarizes the status of current cytogenetic tools in terms of background, advancements, different techniques, significant findings, and research challenges. Principal roles and applications of cytogenetics in orchid breeding as well as different ploidy level determination methods crucial for breeding are also discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.108-118
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• 2018

Recently, agricultural sector apply ICT technology such as Smart Farm to pursue innovation in the changing situation that is emerging as the fourth industrial revolution. However, this innovation requires techniques for forecasting and analyzing in various data bases and spatial information provides such infrastructure data. In this study, the cultivation area of Chinese cabbage, radish, garlic, onion, and red pepper were calculated and analyzed by year. The purpose of this analysis is to cope with sudden changes in vegetable crops and changes in cultivated area caused by weather changes to supply and demand of major vegetables and price instability. As a result of this study, spatial information based on time series information of vegetable complex will be used as efficient agricultural environment observation data, as well as interpretation of various spatial ranges such as the estimation of cultivation area using remote sensing.

• Research in Plant Disease
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• v.8 no.2
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• pp.84-91
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• 2002

Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.

• Journal of Life Science
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• v.25 no.9
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• pp.1059-1071
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• 2015

Watermelon and melon are economically important Cucurbitaceae crops. Recently, the development of molecular markers based on the construction of genetic linkage maps and detection of DNA sequence variants through next generation sequencing are essential as molecular breeding strategies for crop improvement that uses marker-assisted selection and backcrossing. In this paper, we intended to provide useful information for molecular breeding of watermelon and melon by analyzing the current status of international and domestic research efforts on genomics and molecular markers. Due to diverse genetic maps constructed and the reference genome sequencing completed in the past, DNA markers that are useful for selecting important traits including yield, fruit quality, and disease resistances have been reported and publicly available. To date, more than 16 genetic maps and loci and linked markers for more than 40 traits have reported for each watermelon and melon. Furthermore, the functional genes that are responsible for those traits are being continuously discovered by high-density genetic map and map-based cloning. In addition, whole genome resequencing of various germplasm is under progress based on the reference genome. Not only by the efforts for developing novel molecular markers, but application of public marker information currently available will greatly facilitate breeding process through genomics-assisted breeding.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Spatial Information Research
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• v.17 no.4
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• pp.431-443
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• 2009

Recently, turbidity problem is one of the hot issues in dam and reservoir management works. Main reason to bring about high density turbid water is sediment yield by rainfall intensity energy. Because existing researches didn't consider diverse types of crops, it was difficult to calculate more accurate soil erosion and sediment yield. This study was evaluated the reduction efficiency of soil erosion and sediment yield using ginseng layer extracted from IKONOS satellite image, and the area and the ratio of ginseng area represented $0.290km^2$ and 0.94%. The reduction efficiency of soil erosion considering ginseng area represented low value in 0.9% using GIS-based RUSLE model, because the area of ginseng was small compared to areas of other agricultural lands. To reflect future land use change, this study was calculated the reduction efficiency of soil erosion and sediment yield by considering many scenarios as kinds of crops of paddy, dry field, orchard, and other agricultural areas convert to the ginseng district. As result of analysis of them according to scenarios, scenario (1) in which dry field was converted to ginseng area and scenario (2) in which fully agricultural lands were converted to ginseng area showed high reduction efficiency as 31.3% and 34.8% respectively, compared to existing research which didn't consider ginseng area. Methodology suggested in this study will be very efficient tools to help reservoir management related to high density turbid water.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.290-298
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• 2019

The proportion of farm households in the total population is decreasing every year. The aging of rural areas is expected to deepen. The aging of agriculture is continuing due to the aging of the aged population and the decline of the young population, and agricultural manpower shortage is emerging as a threat to agriculture and rural areas. The existing facility cultivation was concentrated on the production / yield per unit area. However, nowadays, not only production but also crop quality should be good so that the quality of crops must be improved because they can secure competitiveness in the market. Therefore, the government plans to increase the productivity by hi-techization of ICT infrastructure horticulture and to plan the dissemination of energy saving smart greenhouse. Therefore, it is necessary to develop a Smart Farm convergence service system based on a hybrid algorithm to enhance diversity and connectivity. Therefore, this study aims to develop smart farm convergence service system which collects data of growth environment of the rhizosphere environment of crops by wireless and monitor smartphone.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.53-61
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• 2022

Growing agricultural products in greenhouses controlled by creating suitable climatic conditions and root zone of crop has been an important research and application subject. Appropriate environmental conditions in greenhouse are necessary for optimum plant growth improved crop yields. This study aimed to establish web-based remote monitoring system which monitors crops growth environment and status of crop on a real-time basis by applying to greenhouses IT technology connecting greenhouse equipment such as temperature sensors, soil sensors, crop sensors and camera. The measuring items were air temperature, relative humidity, solar radiation, CO₂ concentration, EC and pH of nutrient solution, medium temperature, EC of medium, water content of medium, leaf temperature, sap flow, stem diameter, fruit diameter, etc. The developed greenhouse monitoring system was composed of the network system, the data collecting device with sensors, and cameras. Remote monitoring system was implemented in a server/client environment. Information on greenhouse environment and crops is stored in a database. Items on growth and environment is extracted from stored information, could be compared and analyzed. So, A integrated monitoring system for smart greenhouse would be use in application practice and understanding the environment and crop growth for smart greenhouse management. sap flow, stem diameter and pant-water relations