• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.11a
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• pp.102-115
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• 2001

국내 분화류의 생산면적은 2000년 현재 1,036.2ha이며 생산량은 연간 282,656천분, 그리고 생산액은 연간 268,498,990천원으로 추산되고 있다(2000년 화훼재배현황, 농림부). 이와 같은 국내 분화재배면적이 증가함에 따라 다양한 화종의 분화가 재배되고 있으며 화종에 따른 관수방법, 이용상토, 양액농도, 시비방법 등에 대한 많은 연구가 이루어지고 있다(Lieth and Burger, 1989). (중략)

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 1998.05a
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• pp.83-88
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• 1998

양액재배는 세계적으로 각광을 받으며 그 면적이 급속히 증가하고 있고 이에 따라 우리나라의 양액재배 면적도 '94년 63㏊에서 '97년 413.9㏊로 급속히 증가하였다. 양액재배의 특징은 양분의 농도를 쉽게 변경하여 공급할 수 있는 장점이 있으나 토양이 갖는 완충능이 감소되는 조건하에서의 재배이므로 항상 작물의 생육에 합치되는 배양액의 관리가 필요하다. (중략)

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.5-15
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• 2001

For estimating paddy field area with Landsat TM images, two dates, May 31, 1991 (transplanting stage) and August 19, 1991 (heading stage) were selected by the data analysis of digital numbers considering rice cropping calendar. Four different estimating methods (1) rule-based classification method, (2) supervised classification(maximum likelihood), (3) unsupervised classification (ISODATA, No. of class:15), (4) unsupervised classification (ISODATA, No. of class:20) were examined. Paddy field area was estimated to 7291.19 ha by non-classification method. In comparison with topographical map (1:25,000), accuracy far paddy field area was 92%. A new image stacked by 10 layers, Landsat TM band 3,4,5, RVI, and wetness in May 31,1991 and August 19,1991 was made to estimate paddy field area by both supervised and unsupervised classification method. Paddy field was classified to 9100.98 ha by supervised classification. Error matrix showed 97.2% overall accuracy far training samples. Accuracy compared with topographical map was 95%. Unsupervised classifications by ISODATA using principal axis. Paddy field area by two different classification number of criteria were 6663.60 ha and 5704.56 ha and accuracy compared with topographical map was 87% and 82%. Irrespective of the estimating methods, paddy fields were discriminated very well by using two-date Landsat TM images in May 31,1991 (transplanting stage) and August 19,1991 (heading stage). Among estimation methods, rule-based classification method was the easiest to analyze and fast to process.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.93-100
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• 2011

본 연구에서는 자연광 이용 온실의 재배면적을 최대화 하기 위하여 작물생강 모델링, 태양의 위치 및 일사량을 이용하여 2단재배 시스템을 위한 한계일사량 산정 모델, 2단재배 광환경 분성 모델을 개발하였다. 그리고 광환경의 변화에 따른 작물 생장 지체시간을 이용하여 작물의 생산량이 최대가 될 수 있는 한계 일사량의 값을 산정하여 2단 재배 시스템을 최적 설계 하였다. 2단재배 시스템의 최적설계를 위한 분석결과 총 생산량이 약 3.669 kg (d.m.)${\cdot}m^{-2}{\cdot}yerar^{-1}$이며, 기존 재배방식보다 130.2 %의 생산 증대 효과를 잦는 것으로 계산 되었다. 이와 같은 다단재배 시스템은 온실 내부의 공간을 효율적으로 이용하여 제배면적 대비 에너지 투입 비용을 절감 할 것으로 기대 된다.

• The Hankook-Saengyark Bo
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• no.254
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• pp.4-4
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• 2003

• Life and Agrochemicals
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• s.267
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• pp.64-64
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• 2011

• Life and Agrochemicals
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• s.272
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• pp.56-56
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• 2011

• The Hankook-Saengyark Bo
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• no.192
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• pp.5-5
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• 1995

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.286-296
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• 2019

Land suitability assessments have been a crucial issue for enhancing productivity in agriculture and conserving agricultural lands. Based on soil and climate information, land suitability assessment for peaches (Prunus persica) and grapes (Vitis vinifera L.) were conducted using the maximum limiting characteristic method (MLCM) in South Korea. In peaches, S1 (highly suitable) exists on 2.21% of the land, S2 (moderately suitable) on 19.20%, N1 (currently not suitable) on 12.07%, and N2 (permanently not suitable) on the remaining 66.52%. In grapes, 3.65% of the land is classified as S1, 17.98% as S2, 11.85% as N1 and 66.52% as N2. In both fruit trees, the results acquired from soil and climatic information were similar to those from soil information alone. The data also suggest that the grades by soil information were relatively low over the land. With the assumption that the more suitable area a province has, the more will be cultivated for the fruit trees, we compared the percentages of area for peach and grape farming per province with the results by MLCM, and suggested that some provinces with a small percentage of farm can be encouraged to plant more in suitable areas as dictated by MLCM for the species. In the near future, we plan to use an advanced method such as analytic hierarchy process (AHP) to conduct similar tests, in which having reference data of yields or benefits per farm can efficiently increase the accuracy of the measurements.

• 농업기술회보
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• v.48 no.6
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• pp.31-33
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• 2011

최근에 논 소독 다양화 사업과 밭작물 자급률 향상 정책이 동시에 추진됨에 따라 논 콩의 재배면적이 늘어나고 있는 추세다. 따라서 논에서 콩을 안전하게 재배할 수 있는 핵심 기술을 소개한다.