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고랭지 배추의 생장모의

Growth Modeling of Chinese Cabbage in an Alpine Area

  • 투고 : 2014.09.25
  • 심사 : 2014.11.05
  • 발행 : 2014.12.30

초록

여름배추는 수요와 공급에 대한 가격반응이 매우 민감한 작목으로서 날씨에 따른 작황변동은 가격 등락폭과 밀접한 관련이 있다. 본 연구에서는 여름배추의 수급에 절대적으로 중요한 고랭지배추의 생장과 수량을 기상조건으로부터 예측할 수 있는 경험식을 개발하였다. 1997년부터 1998년까지 2년에 걸쳐 파종기를 달리하여 수행한 실험결과를 기반으로 기온으로부터 엽면적 추정식을 도출하였다. 배추 생체중의 변화를 엽면적에 의해 설명할 수 있는 예측식을 작성한 다음 엽면적 추정식과 결합하여 다음 식을 얻었다. $$Fresh\;weight=3500/(1+{\exp}(5.175-1.153{\times}(6/(1+{\exp}(6.367-0.0064{\times}PHU)))))$$ 이 경험식을 2003년부터 2006년까지 매일 기온자료에 의해 구동시켜 예상 생체중을 계산한 다음 검증용 포장에서 얻은 실제 생체중과 비교한 결과 연차별로 결정계수 0.89~0.94의 높은 상관을 보였다.

Summer cabbages in an alpine area are very sensitive to the fluctuations in supply and demand. Yield variability due to weather conditions dictates the market fluctuations of cabbage price. This study reports an empirical relationship based on weather conditions to estimate the growth and harvestable biomass of cabbages, factors that are critical for supply of summer cabbages. Based on experimental results testing sowing date effects over the two years from 1997 to 1998, a logistic equation was parameterized to predict leaf area expansion of summer cabbages. This logistic model for leaf area expansion was then combined with an empirical allometric relationship to predict total biomass. The final equation for estimating fresh weight accumulation of Chinese cabbage is given by: $$Fresh\;weight=3500/(1+{\exp}(5.175-1.153{\times}(6/(1+{\exp}(6.367-0.0064{\times}PHU)))))$$ Where PHU is potential heat units ($^{\circ}C$). The model performance was tested using weather data from 2003 to 2006 to predict fresh harvestable biomass. Overall the model performance was satisfactory with the correlation efficient ranging between 0.89 and 0.94 for each year.

키워드

참고문헌

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피인용 문헌

  1. Estimation of Chinese Cabbage Growth by RapidEye Imagery and Field Investigation Data vol.48, pp.5, 2015, https://doi.org/10.7745/KJSSF.2015.48.5.556
  2. Projecting the Spatio-Temporal Change in Yield Potential of Kimchi Cabbage (Brassica campestris L. ssp. pekinensis) under Intentional Shift of Planting Date vol.18, pp.4, 2016, https://doi.org/10.5532/KJAFM.2016.18.4.298
  3. Constructing Italian ryegrass yield prediction model based on climatic data by locations in South Korea vol.63, pp.3, 2017, https://doi.org/10.1111/grs.12163
  4. Application of Highland Kimchi Cabbage Status Map for Growth Monitoring based on Unmanned Aerial Vehicle vol.49, pp.5, 2016, https://doi.org/10.7745/KJSSF.2016.49.5.469
  5. 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