DOI QR코드

DOI QR Code

Analysis of Meteorological Factors on Yield of Chinese Cabbage and Radish in Winter Cropping System

월동작형 배추와 무의 생산량에 영향을 미치는 기상요인 분석

  • Kim, In-Gyum (Policy Research Division, National Institute of Meteorological Research) ;
  • Park, Ki-Jun (Policy Research Division, National Institute of Meteorological Research) ;
  • Kim, Baek-Jo (Policy Research Division, National Institute of Meteorological Research)
  • 김인겸 (국립기상연구소 정책연구과) ;
  • 박기준 (국립기상연구소 정책연구과) ;
  • 김백조 (국립기상연구소 정책연구과)
  • Received : 2012.10.08
  • Accepted : 2013.06.07
  • Published : 2013.06.30

Abstract

Among many factors, especially meteorological conditions can impact agricultural productivities. This study was conducted to analyze the relationships between crop yield and meteorological factors. We collected meteorological data (i.e., temperature and precipitation) from the Automated Weather System (AWS) of Korea Meteorological Administration (KMA) and the yield data of Chinese cabbage and Radish from local Nonghyup (NCAF:National Agricultural Cooperative Federation) and Farmers' Corporate Association. The agricultural data were classified into two groups. These groups are comprised of the farmers who produced a crop under 30 kg per $3.3m^2$ and over 30k g per $3.3m^2$ respectively. The daily meteorological data were calculated from the average value for ten days. Based on the regression analysis, we concluded that the yield of Chinese cabbage (Haenam) was related to average temperature, minimum temperature, precipitation, and number of days with precipitation, whereas that of Radish (Jeju) was related to average temperature, maximum temperature, and minimum temperature. The result suggests that these meteorological data can be used more effectively for the prediction of crop yield.

본 연구는 급격한 가격변동으로 소비자 물가에 직접적인 영향을 미치고 있는 배추와 무를 선정하여 단위면적당 수확량과 기상요소의 관계를 밝히고자 하였다. 기존에 농작물과 기상요소의 관계를 분석한 연구들은 넓은 지역을 대표하는 특정 지점의 기상자료를 사용하였으나 본 연구에서는 개별 농경지에서 가장 가까운 지점의 기상자료를 사용하였다. 특히 지역의 계약재배 담당자들과의 인터뷰에 기반하여 수집된 농업자료를 그대로 사용하지 않고, 농업과 기상자료의 가공을 통해 좀 더 세부적인 분석을 시도하였으며, 도출된 유의한 기상요소들은 기존의 연구들에서 제시한 상관계수들보다 높게 나타나 농산물의 단수추정에 기상요소가 중요하게 활용될 수 있음을 보였다. 분석 결과 월동배추 무의 생육기간 동안 각각 최저기온과 최고기온이 단수와 관련이 많은 것으로 드러났는데, 향후 기상청과 같은 기상정보 제공자들은 재배 지역에 농업기상정보를 제공하고자 할 때, 농산물과 지역의 특성을 고려한 세부기상요소를 중점적으로 제공하면 효과를 거둘 수 있을 것으로 기대된다.

Keywords

References

  1. Jeju Special Self-Governing Province Agricultural Research & Extension Services, 2012: Cultivation Techniques of Economic Crops. Jeju Special Self-Governing Province. (in Korean)
  2. Lee, J. W., 1996: A Study on the Analysis of Determinant Factors of Production for Radish and Chinese Cabbage, Korea Rural Economic Institute, 77pp. (in Korean)
  3. Lee, K. K., K. K. Ko, and J. W. Lee, 2012: Correlation Analysis between Meteorological Factors and Crop Products. Journal of the Environmental Sciences 21, 461-470. (In Korean with English abstract) doi:10.5322/JES.2012.21.4.461
  4. Lee, Y. S., H. K. Jeong, W. T. Kim and Y. C. Choi, 2004: An Estimation of Yield Functions of Korean Fruit-Vegetables. Korea Rural Economic Institute. 61pp. (In Korean with English abstract)
  5. Lee, Y. S., H. K. Jeong, and S. B. Shim, 2005: A Study on determinants of Seasonal Supply and Price of Produce in Korea: With Special Emphasis on Weather. Korea Rural Economic Institute. 131pp. (In Korean with English abstract)
  6. Seoul Agro-Fisheries & Food Corporation, 2012: Analysis on the Place of Shipment. Seoul Metropolitan Government. (in Korean)
  7. Statistics Korea, 2010: 2010 Annual Average Customer Price Trend. Statistics Korea (in Korean)
  8. Korea Rural Economic Institute, http://aglook.krei.re.kr/ (2013.06.30)

Cited by

  1. Panel analysis of radish yield using air temperature vol.41, pp.4, 2014, https://doi.org/10.7744/cnujas.2014.41.4.481
  2. Evaluation of Factors Related to Productivity and Yield Estimation Based on Growth Characteristics and Growing Degree Days in Highland Kimchi Cabbage vol.33, pp.6, 2015, https://doi.org/10.7235/hort.2015.15074
  3. Production of Agrometeorological Information in Onion Fields using Geostatistical Models vol.27, pp.7, 2018, https://doi.org/10.5322/JESI.2018.27.7.509