DOI QR코드

DOI QR Code

Estimation of Heading Date for Rice Cultivars Using ORYZA (v3)

ORYZA (v3) 모델을 사용한 벼 품종별 출수기 예측

  • Hyun, Shinwoo (Department of Plant Science, Seoul National University) ;
  • Kim, Kwang Soo (Department of Plant Science, Seoul National University)
  • 현신우 (서울대학교 식물생산과학부) ;
  • 김광수 (서울대학교 식물생산과학부)
  • Received : 2017.06.29
  • Accepted : 2017.11.08
  • Published : 2017.12.30

Abstract

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

벼의 생육에 있어서 중요한 역할을 하는 출수기를 예측하기 위해 작물모델이 사용될 수 있다. 벼의 생육을 모의하는 모델 중 널리 사용되던 ORYZA2000 모델이 개선되어 ORYZA (v3)가 최근에 보고되었다. 그러나, 최근까지 ORYZA (v3)의 국내 적용 가능성에 대해서는 연구가 이루어지지 않았다. 본 연구에서는 ORYZA (v3)를 이용하여 예측된 출수기의 신뢰성을 검토하였다. 또한, 새로운 모델에 요구되는 입력자료를 생성하는데 있어서의 편의성을 평가하였다. 국립농업과학원의 실험포장에서 2015년과 2016년에 걸쳐 중만생종인 신동진벼를 이용하여 화학비료 표준시비 조건에서 실험을 수행하였다. 입력자료는 실험에 사용한 재배관리자료, 기상청으로부터 수집한 기상자료, 흙토람으로부터 수집한 토양자료 및 Lee et al.(2015)에서 사용한 품종모수 자료를 사용하였다. 또한, 벼우량계통 지역적응시험에서 얻어진 출수기 관측자료와 예측자료를 비교하였다. 예측된 출수기는 인근 기상관측소에서 얻어진 기상입력 자료가 사용되었을 경우, 실제 출수기와 비교적 유사한 결과를 보였다. 예를 들어, 전주, 대구, 영남, 논산, 계화에서 예측된 출수기는 1일 이내의 상당히 작은 오차는 가졌다. 그러나, 기상자료가 비교적 멀리 떨어져 있거나 해안가 인근지역에 위치하여 출수기 관측지의 국지적 기상조건을 충분히 반영하지 못할 경우 상당한 오차가 발생하였다. ORYZA (v3)의 입력자료 생성과 관련한 편의성 측면에서는 기존의 자료 처리도구를 활용할 수 있는 기상 자료 확보는 비교적 용이할 것으로 판단되나, 토양자료에 대해서는 ORYZA 2000 모델의 입력자료에 추가적인 자료가 요구되어 토양자료 처리도구의 개발이 필요할 것으로 보였다.

Keywords

References

  1. Ahn, S.B., 1968: Studies on response of rice plant to photoperiod. Korean Journal of Crop Science 5(1), 45-49.
  2. Bouman, B. A. M., M. J. Kropff, T. P. Tuong, M. Wopereis, H. F. M. Ten Berge, and H. H. Van Laar, 2001: ORYZA2000: modeling lowland rice, International Rice Research Institute, 235p.
  3. Hoogenboom, G., J. W. Jones, P. W. Wilkens, C. H. Porter, K. J. Boote, L. A. Hunt, U. Singh, J. I. Lizaso, J. W. White, O. Uryasev, R. Ogoshi, J. Koo, V. Shelia, and G. Y. Tsuji, 2015: Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.6 (http://dssat.net), DSSAT Foundation, Prosser, Washington.
  4. Kim, J., C. K. Lee, H. Kim, B. W. Lee, and K. S. Kim, 2015: Requirement analysis of a system to predict crop yield under climate change. Korean Journal of Agricultural and Forest Meteorology 17(1), 1-14. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2015.17.1.1
  5. Lee, C. K., J. Kim, and K. S. Kim, 2015: Development and application of a weather data service client for preparation of weather input files to a crop model. Computers and Electronics in Agriculture 114, 237-246. https://doi.org/10.1016/j.compag.2015.03.021
  6. Lee, C. K., J. Kim, J. Shon, W. H. Yang, Y. H. Yoon, K. J. Choi, and K. S. Kim, 2012: Impacts of climate change on rice production and adaptation method in Korea as evaluated by simulation study. Korean Journal of Agricultural and Forest Meteorology 14(4), 207-221. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2012.14.4.207
  7. Lee, C. K., K. S. Kwak, J. H. Kim, J. Y. Son, and W. H. Yang, 2011: Impacts of climate change and follow-up cropping season shift on growing period and temperature in different rice maturity types. Korean Journal of Crop Science 56(3), 233-243. (in Korean with English abstract) https://doi.org/10.7740/kjcs.2011.56.3.233
  8. Li, T., O. Angeles, M. Marcaida, E. Manalo, M. P. Manalili, A. Radanielson, and S. Mohanty, 2017: From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogendeficient environments. Agricultural and Forest Meteorology 237, 246-256.
  9. Yun, J. I., 2003: Predicting regional rice production in South Korea using spatial data and crop-growth modeling. Agricultural Systems 77(1), 23-38. https://doi.org/10.1016/S0308-521X(02)00084-7