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서지정보
ㆍ발행기관 : 한국초지조사료학회
ㆍ수록지정보 : 한국초지조사료학회지 / 43권 / 1호
ㆍ저자명 : 김문주, 김지융, 조무환, 성경일
목차
ABSTRACT
Ⅰ. 서론
Ⅱ. 재료 및 방법
1. 자료 수집 및 변수생성
2. 통계분석 방법
Ⅲ. 결과 및 고찰
1. 오차드그라스에 대한 생산량, 기후 및 재배관리 변수
2. 오차드그라스의 생산량에 대한 기후 및 재배관리 변수의 중요도 평가
Ⅳ. 결론
Ⅴ. 요약
Ⅵ. 사사
Ⅶ. REFERENCES
영어 초록
This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982―2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0―6 years) and number of cutting (NC, 2nd―5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.
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