• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.5
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• pp.379-383
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• 2002

Allelic diversity of 44 microsatellite marker loci originated from the coding regions of specific genes or the non-coding regions of barley genome was analyzed for 19 barley genotypes. Multi-allelic variation was observed at the most of marker loci except for HVM13, HVM15, HVM22, and HVM64. The number of different alleles ranged from 2 to 12 with a mean of 4.0 alleles per micro-satellite. Twenty-one alleles derived from 10 marker loci are specific for certain genotypes. The level of polymorphism (Polymorphic Information Content, PIC) based on the band pattern frequencies among genotypes was relatively high at the several loci such as HVM3, HVM5, HVM14, HVM36, HVM62 and HVM67. In the cluster analysis using genetic similarity matrix calculated from microsatellite-derived DNA profiles, two major groups were classified and the spike-row type was a major factor for clustering. Correlation between genetic similarity matrices based on microsatellite markers and pedigree data was highly significant ($r=0.57^{**}$), but these two parameters were moderately associated each other. On the other hand, RAPD-based genetic similarity matrix was more highly associated with microsatellite-based genetic similarity ($r=0.63^{**}$) than coefficient of parentage.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.6
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• pp.552-562
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• 2004

KISTI(Korea Institute of Science and Technology Information) has developed the ${\ulcorner}$KITTI­ACOMS (KISTI-Article COntribution Management System)${\lrcorner}$ as part of the national project for automating the process of processing academic information by societies, in order to convert journals published by academic societies in Korea into an electronic form and make them accessible on the Internet. This system has been developed in the year 2001 and has since been distributed to societies free of charge. The number of societies requesting the service has risen recently, which prompted us to take more recommendations of the societies that adopt this system into account in expanding and standardizing the area of service being provided by the system. This paper will investigate the functions of KISTI-ACOMS constructed for use in the Korean Society of Crop Science and list the functions and requirements for the next system to enhance the on-line paper management system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.158-166
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• 2019

Implementing proper land management techniques, such as selecting the best crops and applying the best cultivation techniques at the farm level, is an effective way for farmers to adapt to climate change. Also it will be helpful if the farmer can get the information of agro-weather and the growth status of cultivating crops in real time and the simulated results of applying optional technologies. To test this, a system (web site) was developed to produce agro-weather data and crop growth information of farms by combining agricultural climate maps and crop growth modeling techniques to highland area for summer-season Chinese cabbage production. The system has been shown to be a viable tool for producing farm-level information and providing it directly to farmers. Further improvements will be required in the speed of information access, the microclimate models for some meteorological factors, and the crop growth models to test different options.

• The Plant Pathology Journal
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• v.36 no.4
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• pp.305-313
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• 2020

Host shifting and host expansion of fungal plant pathogens increases the rate of emergence of new pathogens and the incidence of disease in various crops, which threaten global food security. Magnaporthe species cause serious disease in rice, namely rice blast disease, as well as in many alternative hosts, including wheat, barley, and millet. A severe outbreak of wheat blast due to Magnaporthe oryzae occurred recently in Bangladesh, after the fungus was introduced from South America, causing great loss of yield. This outbreak of wheat blast is of growing concern, because it might spread to adjacent wheat-producing areas. Therefore, it is important to understand the host range and population structure of M. oryzae and related species for determining the evolutionary relationships among Magnaporthe species and for managing blast disease in the field. Here, we collected isolates of M. oryzae and related species from various Poaceae species, including crops and weeds surrounding rice fields, in Korea and determined their phylogenetic relationships and host species specificity. Internal transcribed spacer-mediated phylogenetic analysis revealed that M. oryzae and related species are classified into four groups primarily including isolates from rice, crabgrass, millet and tall fescue. Based on pathogenicity assays, M. oryzae and related species can infect different Poaceae hosts and move among hosts, suggesting the potential for host shifting and host expansion in nature. These results provide important information on the diversification of M. oryzae and related species with a broad range of Poaceae as hosts in crop fields.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.1
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• pp.61-67
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• 2017

This experiment was conducted to obtain information of feed value and fermentative quality of wheat cultivar, 'Taejoong' to confirm availability as a whole crop silage. As a result, the heading date of 'Teajoong' is April 27, and plant height is longer than whole crop barley, 'Youngyang' or whole crop wheat, 'Cheongwoo', spike length are also large, fresh and dry matter yield are also high. In case of feed value, 'Taejoong' had higher crude protein content than whole crop barley, 'Youngyang' or whole crop wheat, 'Cheongwoo', lower NDF and ADF contents, and significantly higher digestible nutrient contents(p<0.05). In case of fermentation qulity, pH of 'Taejoong' was 4.2, and lactic acid content was lower than 'Cheongwoo' silage and significantly higher than 'Youngyang' silage(p<0.05). Acetic acid content was significantly lower than 'Youngyang' and 'Cheongwoo' silage(p<0.01), butyric acid content was significantly lower than that of 'Youngyang' silage (p<0.05). The final Flieg's score showed that 'Taejoong' silage was the best. Also income of 'Taejoong' improved than 'Youngyang' or 'Cheongwoo'. Therefore, 'Taejoong' is considered sufficiently available as whole crop for forage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Proceedings of the Korean Society of Crop Science Conference
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• 2018.04a
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• pp.197-197
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• 2018

• The Korean Journal of Food And Nutrition
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• v.33 no.5
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• pp.588-597
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• 2020

This study was conducted to secure basic information for corn processing by comparing the quality characteristics according to maize cultivars and kernel types (dent, intermediate, flint-like). As a result of analyzing 15 cultivars, a range of measurements were observed: 100-kernel weight, 22.89~35.63 g; moisture, 7.57~8.42%; crude protein, 8.46~11.45%; crude lipids, 3.26~4.83%; Hunter's L-value, 83.70~86.79; a-value, 2.61~5.49; b-value, 22.01~28.15; and total carotenoids, 6.74~17.07 ㎍/g. Significance among the cultivars was shown in all quality characteristics (p<0.001), but the significance among the kernel types was found only in crude protein (p<0.005), crude fat (p<0.001), and Hunter's L-value (p<0.05). The hardness of maize was decreased proportionally to the soaking time for all maize cultivars (p<0.001). In particular, with the same soaking time for different kernel types, the hardness difference was shown in the order of flint-like > dent ≒ intermediate. It was confirmed that the decrease in the hardness of flint-like kernel of close to that of hard-type starch was slowed compare dent and intermediate kernels. So it is expected the some characteristic of kernel types will contribute to the appropriate customized use of the developed cultivars.