• Title/Summary/Keyword: 북한의 농업

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Yangshao Culture and Rice Culture - In Relations to Dissemination of Rice Culture Towards to the North - East of China - (중국 앙소시대 문화와 도작농업 -재배도의 동북방향 전파노선과 관계하여-)

  • Chang, Juzhong;Wang, Xiangkun;Cui, Zong Jun;Heu, Mun Hue
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.41 no.3
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    • pp.376-383
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    • 1996

  • Distribution of archaeological sites where the rice and Itallian millets were excavated was discussed in relation to the rice culture of Yangshao era. According to the distribution of the sites where the rice and Italian millet remains were excavated, the putative border of rice growing area, Italian millet growing area and mixed-cropping area were drawn. Discussions were made about the drifting of the area of mixed-cropping, north and south, depending on the climates of archaeological eras, The climates of the eras were discussed with the various remains of animals and plants excavated from each era's sites. Examining the chronology of mixed-cropping area the extension of rice culture were traced chronologically. And the extension of rice culture towards north-east during the last period of Yangshao era, and the feasibilities of transfer to the Han-river mouth area in Korea, 5,000 aBP(about Before Present), were discussed.

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Statistical Analysis of Amylose and Protein Content in Landrace Rice Germplasm Collected from East Asian Countries Based on Near-Infrared Reflectance Spectroscopy (NIRS) (근적외선분광분석에 의한 동아시아 지역 재래종 벼 유전자원의 아밀로스 및 단백질 함량 변이분석)

  • Oh, Sejong;Choi, Yu Mi;Yoon, Hyemyeong;Lee, Sukyeung;Yoo, Eunae;Lee, Myung Chul;Rauf, Muhammad;Chae, Byungsoo
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.64 no.2
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    • pp.70-88
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    • 2019

  • A statistical analysis of 4,380 non-glutinous landrace rice germplasm collected from four East Asian countries namely South Korea (1,032), North Korea (994), Japan (800), and China (528) was conducted using normal distribution, variability index value (VIV), analysis of variation (ANOVA), and Duncan's multiple range test (DMRT) based on a data obtained from Near-Infrared Reflectance Spectroscopy (NIRS) analysis. In normal distribution, the average protein content was 8.2%, and the non-glutinous rice amylose, ranging over 10%, was found to be 22.0%. Protein content in most gremplasm was between 5.4 and 10.9%, and amylose content was between 15.0 and 28.9%. The VIV was 0.50 for protein, and 0.81 for non-glutinous rice amylose content. The average amylose content was 23.34% in Chinese, 21.55% in South Korean, 21.45% in Japanese, and 20.48% in North Korean resources, while the average protein content was found to be 9.02% in Chinese, 8.06% in Japanese, 8.04% in North Korean, and 7.99% in South Korean resources. ANOVA of amylose and protein content showed significant differences at p=0.01. The F-test value for amylose content was 94.92, and for protein content was 81.82 compared to the critical value of 3.79. DMRT of amylose and protein content revealed significant differences (p<0.01). Among the various germplasm obtained from different countries, that from North Korean had the lowest level of amylose content, whereas that from South Korea had the lowest level of protein content than all other resources. Chinese resources had the highest level of amylose and protein content. It is recommended to use these results in breeding fields.

  • https://doi.org/10.7740/kjcs.2019.64.2.070 인용 PDF KSCI HTML

Extraction of paddy rice field in North Korea using time-series satellite images (시계열 위성영상을 이용한 북한 지역의 논벼 재배 지역 추출 기법 연구)

  • Lee, Sang-Hyun;Choi, Jin-Yong;Oh, Yun-Gyeong;Yoo, Seung-Hwan;Lee, Sung-Hack;Park, Na-Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.441-441
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    • 2012

  • 본 연구의 목적은 북한지역에 적용할 수 있는 논벼 재배지역 추출 기법을 개발 및 적용하여 논 분포도를 작성하고, 정확도를 평가하는 것이다. 이를 위하여 북한에 적용 가능한 시계열 위성자료를 수집하고, 논벼 재배지역 추출을 위한 토지피복 분류 기법을 개발하여 북한의 논벼 재배지역 분포도를 작성하고자 한다. 최종적으로 작성된 논 분포도를 북한의 농경지 모니터링을 위한 기초 자료로 제공토록 한다. 본 연구에서는 시계열 NDVI를 적용한 객체기반 무감독 토지피복 분류 방법을 활용하여 북한의 황해남도 재령군을 대상으로 토지피복 분류와 논 지역을 추출을 수행하고자 하였다. 본 연구에서 활용한 영상은 RapieEye로서 5개의 위성이 지구를 관측하고 있기 때문에 매일 동일한 지역의 영상을 폭넓게 획득할 수 있다는 장점이 있으며, Red, Green, Blue, Near Infra Red 밴드 외에 Red Edge 밴드에서 데이터를 획득하여 산림 모니터링, 농작물 모니터링 등에 효과적으로 활용할 수 있다는 특징이 있다. 먼저 2010년 4월, 6월, 9월 영상으로 각 영상의 NDVI를 산정하고 이를 활용하여 객체를 생성하였다. 다음으로 생성된 객체를 바탕으로 무감독 토지피복 분류를 수행하였고, 논 적합지역에 대한 지형 정보를 분류결과에 반영하여 최종적인 토지피복지도 및 논 지역 지도를 구축하였다. 본 연구결과는 원격탐사분야의 응용 기술을 확장하고, 향후 북한지역의 농산물 생산량 파악과 농업수자원 평가 분야에서도 폭 넓게 활용될 것으로 판단된다.

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