• Ecology and Resilient Infrastructure
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• v.3 no.3
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• pp.207-211
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• 2016

This study focuses on the categorization of the phenomenon of vegetative recruitment on riparian channels, so called, the phenomenon from "white river" to "green river", and proposes for the corresponding research direction. According to the literature review and research outputs obtained from the authors' previous research performed in Korea within a limited scope, the necessary and sufficient conditions for the recruitment and retrogression of riparian vegetation may be the mechanical disturbance (riverbed tractive stress), soil moisture (groundwater level, topography, composition of riverbed material, precipitation etc.), period of submergence, extreme weather, and nutrient inflow. In this study, two categories, one for the reduction in spring flood due to the change in spring precipitation pattern in unregulated rivers and the other for the increase in nutrient inflow into streams, both of which were partially proved, have been added in the categorization of the vegetative recruitment and retrogression on the riparian channels. In order to scientifically investigate further the phenomenon of the riparian vegetative recruitment and retrogression and develop the working riparian vegetative models, it is necessary to conduct a systematic nationwide survey on the "white to green" rivers, establishment of the categorization of the vegetation recruitment and retrogression based on the proof of those hypotheses and detailed categorization, development of the working mathematical models for the dynamic riparian vegetative recruitment and retrogression, and adaptive management for the river changes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.294-297
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• 2015

Recently, big data analysis which is based on machine learning has been gained a lot of attentions in various fields. Especially, agriculture is considered as one promising field that machine learning algorithm can be efficiently utilized and accordingly, lots of works have been done so far. However, most of the researches are focusing on the forecast of weather or analysis of genome, and machine learning algorithm for livestock management, especially which uses individual data of livestocks, e.g., temperature and movement, are not properly investigated yet. In this work, we propose fast abnormal livestock detection algorithm based on machine learning, more specifically expectation maximization, such that livestock which has problem can be efficiently and promptly found. In our proposed scheme, livestocks are divided into two clusters using expectation maximization based on their bionic data and the abnormal livestock can be detected by comparing the size of two clusters. Especially, we divide the case in which single livestock has problem and the case in which livestocks have epidemic such that fast response is enabled when epidemic case. Moreover, our algorithm does not need statistical information.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.1
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• pp.26-30
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• 2015

A new tall fescue variety (Festuca arundinacea Schreb.) named 'Greenmaster2ho' was developed by the National Institute of Animal Science, Rural Development Administration, in Cheonan, Korea from 2010 to 2014. For the synthetic seed production of this new variety, 5 superior clones were selected and polycrossed: 09XFa02, 09XFa03, 09XFa11, 09XFa13, and 09XFa14. The agronomic growth characteristics and forage production capability of the seeds were studied at Cheonan from 2010 onward, and regional trials were conducted in Cheonan, Hoengseong, Jeju, and Jinju from 2012 to 2014. Greenmaster2ho showed resistance to disease, persistence, and regrowth ability that were all enhanced when compared with Fawn. At 15,119 kg/ha, the dry matter (DM) yield of Greenmaster2ho was 29% higher than that of Fawn, but the nutritive value of both varieties as forage was similar. This study aimed to make a contribution to the vitalization of the Korean grassland industry by developing a new tall fescue variety with excellent environmental adaptability.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Korean Journal of Breeding Science
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• v.43 no.6
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• pp.587-590
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• 2011

A new sesame variety 'Yunheuk' was developed from Yeongnam Agricultural Research Institute in 2007. A cross was made by 'Yoosung' with weak disease resistance and 'Kunheuk' with high yield capacity & quality, followed by pedigree selection, yield test and regional yield trial (RYT) by the sesame breeding team at the National Institute of Crop Science and Yeongnam Agricultural Research Institute up to 2007. The variety showed higher lodging resistance and more dark seed coloring rather than that of check variety 'Yangheuk'. Average stem length and the number of capsules per plant is 118 cm, 79 cm respectively. Its 1,000 grains weight is about 2.67 g indicating 0.10 g lower than that of 'Yangheuk', and its oil content is about 46.4%. 'Yunheuk' also contains total 2.59 mg/g of such lignans as sesamin and sesamolin. And its dark color density ($L^*$ Value) of seed coat is 22.43 which was about 10% lower than that of check variety. The average yield of 'Yunheuk' was 99.9 kg per 10a at the national-wide regional performance.

• Korean Journal of Plant Resources
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• v.32 no.1
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• pp.45-52
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• 2019

In the process of adapting climate change, the government needs to provide policy and technical support necessary for growing promising crops imported from abroad. Therefore, this study was conducted to survey and analyze the conditions of growth of imported foreign crops and to derive response tasks. As a result, tropical and subtropical vegetables were cultivated 18 crops in 920 farms in 321 ha area (in 2015 year). The cultivation scale decreased in the order of Curcuma aromatica, Momordica charantia, Asparagus aethiopicus, Allium hookeri and Herbs. Tropical and subtropical fruits were cultivated 9 crops in 264 farms in 106.5 ha area (in 2015 year). Special and medicinal crops introduced abroad cultivated 10 crops in 753 farms in 276.3 ha area (in 2015 year). The cultivation scale decreased in the order of Curcuma longa, Glycyrrhiza uralensis, Lepidium meyenii and Moringa oleifera. For the stable settlement of domestic growth of tropical and subtropical crops introduced abroad, there should be safety and economic feasibility in terms of the cultivation environment according to the domestic culture adaptation test. Consideration needs to be given to the use of locally grown products in Korea, the securing of distribution and sales markets, and the competitiveness of imported products.

• Journal of The Korean Society of Grassland and Forage Science
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• v.38 no.4
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• pp.280-285
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• 2018

A new variety of tall fescue (Festuca arundinacea Schreb.) named 'Greenmaster4ho' was developed during the cultivation year 2010-2017 at Grassland and Forages Division, National Institute of Animal Science, Rural Development Administration, Cheonan, Korea. In order to produce this new variety, 5 superior tall fescue lines including 12XFa07, 12XFa15, 12XFa24, 12XFa46, and 12XFa48 were polycrossed. The new variety Greenmaster4ho was evaluated in field test (Cheonan, Pyeongchang, Jeju, and Jinju) for determining the agronomic growth characteristics and forage production capability during 3 years (2015-2017). The dry matter yield (16,236 kg/ha) of Greenmaster4ho was 5 % higher than Fawn, but the nutritive value as forage crops was not significantly different with Fawn. Development of new tall fescue variety with excellent adaptability to changing unfavorable environment would be useful for forage cultivation and yield in Korean environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.224-236
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• 2002

A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Journal of the Korean Society of International Agriculture
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• v.31 no.1
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• pp.76-81
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• 2019

'Asemi' is a rice variety derived from a cross between 'Jinmibyeo' which has translucent milled rice and medium maturity and 'Cheolwon46', an elite line with high yield and early maturity by the rice breeding team at NICS, RDA in 2013. The heading date of 'Asemi' is August 1, six days earlier than the check variety 'Hwaseong'. It has 82 cm culm length and 109 spikelets per panicle. 'Asemi' is resistant to blast disease, stripe virus and tungro virus, but susceptible to other viruses and planthoppers. The milled rice of this variety exhibits translucent, clear non-glutinous endosperm and short grain shape. It has protein content (6.7%) higher than 'Hwaseong', and amylose content (19.5%) similar to 'Hwaseong'. The milled rice recovery rate of 'Asemi' is similar to that of 'Hwaseong'. However, the head rice rate of 'Asemi' is higher than that of 'Hwaseong'. Milled rice yield of 'Asemi' is 5.23 MT/ha in ordinary cultivation. ' Asemi' could be adaptable to the wide region of tropical Asia (Registration No. 5639).