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Setting Criteria of Suitable Site for Southern-type Garlic Using Non-linear Regression Model

비선형회귀 분석을 통한 난지형 마늘의 적지기준 설정연구

  • Choi, Won Jun (Climate change Assessment Division, National Institute of Agricultural Sciences) ;
  • Kim, Yong Seok (Climate change Assessment Division, National Institute of Agricultural Sciences) ;
  • Shim, Kyo Moon (Climate change Assessment Division, National Institute of Agricultural Sciences) ;
  • Hur, Jina (Climate change Assessment Division, National Institute of Agricultural Sciences) ;
  • Jo, Sera (Climate change Assessment Division, National Institute of Agricultural Sciences) ;
  • Kang, Mingu (Climate change Assessment Division, National Institute of Agricultural Sciences)
  • 최원준 (국립농업과학원 기후변화평가과) ;
  • 김용석 (국립농업과학원 기후변화평가과) ;
  • 심교문 (국립농업과학원 기후변화평가과) ;
  • 허지나 (국립농업과학원 기후변화평가과) ;
  • 조세라 (국립농업과학원 기후변화평가과) ;
  • 강민구 (국립농업과학원 기후변화평가과)
  • Received : 2021.10.19
  • Accepted : 2021.12.22
  • Published : 2021.12.30

Abstract

This study attempted to establish a field data-based write analysis standard by analyzing field observation data, which is non-linear data of southern garlic. Five regions, including Goheung, Namhae, Sinan, Changnyeong, and Haenam, were selected for analysis. Observation values for each observation station were extracted from the temperature data of farmland in the region through inverse distance weighted. Southern-type garlic production and temperature data were collected for 10 years, from 2010 to 2019. Local regression analysis (Kernel) of the obtained data was performed, and growth temperatures were analyzed, such as 0.8 (18.781℃), 0.9 (18.930℃), 1.0 (19.542℃), 1.1 (20.165℃), and 1.2 (21.042℃) depending on the bandwidth. The analyzed optimum temperature and the grown temperature (4℃/25℃) were applied to extract the growth temperature for each temperature by using the temperature response model analysis. Regression analysis and correlation analysis were performed between the analyzed growth temperature and production data. The coefficient of determination(R2) was analyzed as 0.325 to 0.438, and in the correlation analysis, the correlation coefficient of 0.57 to 0.66 was analyzed at the significance probability 0.001 level. Overall, as the bandwidth increased, the coefficient of determination was higher. However, in all analyses except bandwidth 1.0, it was analyzed that all variables were not used due to bias. The purpose of this study is to accommodate all data through non-linear data. It was analyzed that bandwidth 1.0 with a high coefficient of determination while accepting modeling as a whole is the most suitable.

본 연구는 현장관측자료의 분석을 통해 현장데이터 기반 생육적온 분석 및 재배적지 분석 기준을 제시하고자 하였다. 연구에 활용된 현장 데이터는 고흥, 남해, 신안, 창녕, 해남 등 5개 지역의 난지형 마늘 생산량데이터를 구득하였으며, 관측소별 관측값을 역거리 가중법(Inverse Distance Weighted)를 통해 지역내 농경지 기온데이터를 추출하였다. 데이터 분석에 활용된 기간은 2010년부터 2019년까지 10년간 데이터를 활용하였다. 조사된 생산량과 기온의 국소(Kernel)회귀분석을 통해 생육적온을 분석하였으며, 대역폭에 따라 0.8(18.781℃), 0.9(18.930℃), 1.0(19.542℃), 1.1(20.165℃), 1.2(21.042℃)이었다. 생육적온의 검증 및 재배적지 기준 적용을 위해 온도반응모델을 진행하였다. 분석된 생육적온과 생산량데이터 간의 회귀 분석 및 상관 분석을 수행결과 결정계수(R2)는 0.325~0.438로 분석되었으며, 상관관계 분석에서는 유의 확률 0.001 수준에서 상관계수 0.57~0.66로 분석되었다. 전체적으로 대역폭이 증가함에 따라 결정 계수가 더 높아졌으나 대역폭 1.0을 제외한 모든 대역폭에서는 편향된 결과로 일부 데이터가 모델에 크게 영향을 주는 것으로 나타났다. 이에 비선형분석을 통해 모든 데이터가 평이하게 반영된 모델인 대역폭 1.0이 본 연구 목적에 적합한 것으로 분석되었다.

Keywords

Acknowledgement

이 연구는 농촌진흥청 국립농업과학원 농업과학기술 연구개발사업(과제번호: PJ01354801)의 지원으로 수행되었습니다.

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