Journal of The Korean Society of Grassland and Forage Science (한국초지조사료학회지)

The Korean Society of Grassland and Forage Science (한국초지조사료학회)
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Analysis of Contribution of Climate and Cultivation Management Variables Affecting Orchardgrass Production

오차드그라스의 생산량에 영향을 미치는 기후 및 재배관리의 기여도 분석

  • Moonju Kim (Institute of Animal Life Science, Kangwon National University) ;
  • Ji Yung Kim (Department of Animal Life Science, Kangwon National University) ;
  • Mu-Hwan Jo (Department of Animal Life Science, Kangwon National University) ;
  • Kyungil Sung (Department of Animal Life Science, Kangwon National University)
  • 김문주 (강원대학교 동물생명과학연구소) ;
  • 김지융 (강원대학교 동물생명과학대학) ;
  • 조무환 (강원대학교 동물생명과학대학) ;
  • 성경일 (강원대학교 동물생명과학대학)
  • Received : 2023.02.14
  • Accepted : 2023.03.13
  • Published : 2023.03.31
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Abstract

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.

본 연구는 우리나라(1982-2014년)의 오차드그라스 생산량에 대한 기후 및 재배관리 요인의 중요도를 확인하는 것을 목적으로 수행하였다. 기후는 1월 평균기온(MTJ, ℃), 1월 최저기온(LTJ, ℃), 생육일수 0-5일(GD 1, 일), 생육일수 5-25일(GD 2, 일), 하고일수(SSD, day), 강우일(RD, day), 누적강우량(AR, mm), 일조시간(SD, hr)을 고려하였다. 관리는 조성연차(EP, 0-6년)과 예취횟수(NC, 2-5년)를 측정하였다. 퍼셉트론 방법을 사용한 신경망 모델을 사용하여 오차드그라스의 생산량에 대한 중요도를 추정하였다. 그 결과 EP가 가장 중요한 변수(100%)였으며, RD(82.0%), AR(79.1%), NC(69.2%), LTJ(66.2%), GD 2(63.3%), GD 1 순이었다. (61.6%), SD(58.1%), SSD(50.8%) 및 MTJ(41.8%). 이는 EP, RD, AR, NC가 다른 것보다 중요하다는 것을 의미한다. 우리나라의 연간 강수량은 과수원의 생육에 필요한 양을 초과하므로 배수관리를 통해 적정량 이상의 호우로 인한 피해를 줄일 수 있다. 이는 과수원을 재배할 때 통제 가능한 요인이 상대적으로 중요하다는 것을 의미한다. 비록 본 연구가 신경망 모델에 의해 기후가 생산량에 미치는 구체적인 영향을 해석하는데 한계가 있지만, 주요 요인 선정을 통해 향후 수량 예측 및 기후변화에 의한 피해 추정 연구에 도움이 될 것으로 기대된다.

Keywords

Acknowledgement

본 논문은 과학기술정보통신부가 지원하는 한국연구재단을 통한 신진연구 프로그램의 지원에 의해 이루어졌습니다(NRF-2023R1C1C1004618).

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