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DTS (Days Transformed to Standard temperature) 생육 모델을 활용한 군위 지역의 '후지' 사과 성숙기 예측

Predicting Harvest Maturity of the 'Fuji' Apple at the Gunwi Province of the South Korea using DTS Phenology Model

  • 최인태 (농촌진흥청 국립농업과학원 기후변화생태과) ;
  • 심교문 (농촌진흥청 국립농업과학원 기후변화생태과) ;
  • 김용석 (농촌진흥청 국립농업과학원 기후변화생태과) ;
  • 정명표 (농촌진흥청 국립농업과학원 기후변화생태과) ;
  • 윤경담 (미국 워싱턴대학교 환경산림과학부) ;
  • 김수형 (미국 워싱턴대학교 환경산림과학부)
  • Choi, In-Tae (Division of Climate Change & Agroecology, Department of Agricultural Environment, National Academy of Agricultural Science) ;
  • Shim, Kyo-Moon (Division of Climate Change & Agroecology, Department of Agricultural Environment, National Academy of Agricultural Science) ;
  • Kim, Yong-Seok (Division of Climate Change & Agroecology, Department of Agricultural Environment, National Academy of Agricultural Science) ;
  • Jung, Myung-Pyo (Division of Climate Change & Agroecology, Department of Agricultural Environment, National Academy of Agricultural Science) ;
  • Yun, Kyung-Dahm (School of Environmental and Forest Science, College of Environment University of Washington) ;
  • Kim, Soo-Hyung (School of Environmental and Forest Science, College of Environment University of Washington)
  • 투고 : 2015.10.13
  • 심사 : 2015.11.17
  • 발행 : 2015.11.30

초록

Fuji apple variety introduced in Japan has excellent storage quality and good taste so it is most commonly cultivated in the Korean Peninsula. Accurate prediction of harvest maturity allows farmers to more efficiently manage their farm, such as working time, fruit storage, market shipment and labor distribution so it is very important. This study was carried out to predict the harvest maturity of 'Fuji' apple using DTS (Days Transformed to Standard temperature) model based on the Arrhenius law in the Gunwi province of the South Korea. Input data are daily average temperature and apple harvest maturity. Predicted the harvest maturity of Fuji apple after estimating the optimal parameters by using the Nelder-Mead method. The differences of observed and predicted harvest maturity day are approximately 1 to 4 days and the RMSE is 2.9.

키워드

참고문헌

  1. Aono Y., 1998, Climatic change in march temperature deduced from phenological record for flowering of cherry tree in Tokyo since the late 18th century, Bulletin of Osaka Prefecture University, Series B50, 11-19.
  2. Aono Y., Kazui K., 2008, Phenological data series of cherry tree flowering in Kyoto, Japan, and its application to reconstruction of springtime temperatures since the 9thcentury, Int. J. Climatol., 28, 905-914. https://doi.org/10.1002/joc.1594
  3. Aono Y., Omoto Y., 1990, Estimation of blooming date for prunus yedoensis using DTS combined with chill-unit accumulations, J. Agr. Met., 45(4), 243-249. https://doi.org/10.2480/agrmet.45.243
  4. Aono Y., Saito S., 2010, Clarifying springtime temperature reconstructions of the medieval period by gapfilling the cherry blossom phenological data series at Kyoto, Japan, Int. J. Biometeorol, 54, 211-219. https://doi.org/10.1007/s00484-009-0272-x
  5. Honjo H., Fukui R., Aono Y., Sugiura T., 2006, The DTS accumulation model for prediction the flowering date of Japanese Pear Tree in Japan, Acta. Horticulture, 707, 151-158.
  6. Hur, J. N., Ahn, J. B., Shim, K. M., 2014, The change of cherry first-flowering date over South Korea projected from downscaled IPCC AR5 simulation, Int. J. Climatol, 34, 2308-2319. https://doi.org/10.1002/joc.3839
  7. Hur, J. N., Ahn, J. B., 2015, The change of first-flowering date over South Korea projected from downscaled IPCC AR5 simulation: peach and pear, Int. J. Climatol, 35, 1926-1937. https://doi.org/10.1002/joc.4098
  8. Ono S., Konno T., 1999, Estimation of flowering date and temperature characteristics of fruit trees by DTS method, Japan Agricultural Reserach Quarterly, 33, 105-108.
  9. RDA (Rural Development Administration), 2013, Apple, RDA, 18.
  10. Stastics Korea, 2015, Korean statistical information service, http://kosis.kr.
  11. Sugahara K., 2000, www application for pear fruit growth prediction, Proc. APAN2000, Beijing, 321-324.