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

  • 제36권3호
  • /
  • Pages.205-214
  • /
  • 2016
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  • 2287-5824(pISSN)
  • /
  • 2287-5832(eISSN)
한국초지조사료학회 (The Korean Society of Grassland and Forage Science)
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A Yield Estimation Model of Forage Rye Based on Climate Data by Locations in South Korea Using General Linear Model

  • Peng, Jing Lun (Department of Feed Science and Technology, College of Animal Life Sciences, Kangwon National University) ;
  • Kim, Moon Ju (Department of Feed Science and Technology, College of Animal Life Sciences, Kangwon National University) ;
  • Kim, Byong Wan (Department of Feed Science and Technology, College of Animal Life Sciences, Kangwon National University) ;
  • Sung, Kyung Il (Department of Feed Science and Technology, College of Animal Life Sciences, Kangwon National University)
  • 투고 : 2016.07.04
  • 심사 : 2016.08.04
  • 발행 : 2016.09.30
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초록

The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 - 4.693SRF + 45.106SRD - 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.

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피인용 문헌

  1. Accuracy evaluation of the crop-weather yield predictive models of Italian ryegrass and forage rye using cross-validation vol.20, pp.4, 2017, https://doi.org/10.1007/s12892-017-0090-0
  2. Climatic Suitability Mapping of Whole-Crop Rye Cultivation in the Republic of Korea vol.38, pp.4, 2018, https://doi.org/10.5333/KGFS.2018.38.4.337
  3. Yield modeling for prediction of regional whole-crop barley productivity pp.17446961, 2019, https://doi.org/10.1111/grs.12233