Journal of Bio-Environment Control (생물환경조절학회지)

The Korean Society for Bio-Environment Control (한국생물환경조절학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of Light Environments in Reclaimed Land and Estimation of Spatial Light Distributions in Greenhouse by 3-D Model

간척지 광환경 특성 분석 및 3-D 모델을 통한 온실 내 공간적 광분포 예측

  • Lee, June Woo (Department of Plant Science and Research Institute of Agriculture and Life Science, Seoul National University) ;
  • Shin, Jong Hwa (Department of Plant Science and Research Institute of Agriculture and Life Science, Seoul National University) ;
  • Kim, Jee Hoon (Department of Plant Science and Research Institute of Agriculture and Life Science, Seoul National University) ;
  • Park, Hyun Woo (Department of Plant Science and Research Institute of Agriculture and Life Science, Seoul National University) ;
  • Yu, In Ho (Protected Horticulture Research Station, National Institute of Horticultural and Herbal Science) ;
  • Son, Jung Eek (Department of Plant Science and Research Institute of Agriculture and Life Science, Seoul National University)
  • 이준우 (서울대학교 식물생산과학부 및 농업생명과학연구원) ;
  • 신종화 (서울대학교 식물생산과학부 및 농업생명과학연구원) ;
  • 김지훈 (서울대학교 식물생산과학부 및 농업생명과학연구원) ;
  • 박현우 (서울대학교 식물생산과학부 및 농업생명과학연구원) ;
  • 유인호 (국립원예특작과학원 시설원예시험장) ;
  • 손정익 (서울대학교 식물생산과학부 및 농업생명과학연구원)
  • Received : 2014.10.22
  • Accepted : 2014.11.05
  • Published : 2014.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Reclaimed lands, expected as high-tech export horticultural complex, have unusual light environments due to sea fog. For adequate greenhouse design at reclaimed land, spatial light distributions in greenhouse should be required considering diffusive and direct lights. The objectives of this study were to analyze light environments and estimate spatial light distributions in greenhouse at reclaimed land by 3D greenhouse models. Total and diffusive lights were compared between reclaimed land and inland. For verification of the 3D greenhouse models, spatial light distributions and measured light intensities in greenhouse were compared with the estimated ones. Light environments at reclaimed land showed a higher diffusive irradiation than at inland, especially near sunrise and sunset. The estimated spatial light distributions in greenhouse showed good agreements with the measured ones. By using this method, we could estimate the average light intensity with time and spatial light distributions in greenhouse at specific outside light conditions. This result will be useful for analysis of light environments but also estimation of crop light inception in greenhouse at reclaimed land.

수출용 온실 단지로 기대되는 간척지의 광환경은 해무 등에 의해 내륙과는 다른 광환경 특성을 나타낸다. 이러한 간척지에서 온실 설계 기준을 작성하기 위해서 산란광과 직달광을 고려한 온실 내 광분포 연구가 필요하다. 본 연구에서는 간척지의 고유의 광환경 특성을 분석하고 3-D 온실 모델에 적용하여 간척지의 온실 내 공간적인 광분포를 추정하고자 하였다. 먼저 간척지의 일사량을 산란광과 직달광으로 구분하여 측정하고 내륙의 일사량과 비교하였다. 또한 간척지 지역에 설치된 온실 내의 광분포를 측정하고 이를 시뮬레이션을 통해 계산된 값과 비교함으로써 3-D 온실 모델에 대한 검증을 실시하였다. 간척지는 내륙에 비하여 전체 일사량에 대비 높은 산란광의 비율을 나타내었으며, 특히 일출 및 일몰 부근에서 크게 나타났다. 3-D 온실 모델에 의한 온실 내 예측 광분포는 실제 간척지의 온실 내 광분포와 유사하게 나타났다. 검증된 3-D 온실 모델을 통하여 임의의 외부 광조건에 대하여 간척지 지역의 온실 내부의 시간적인 평균 광도의 변화와 광분포를 예측할 수 있었다. 이러한 결과는 간척지 지역의 온실 내 광환경 해석 이외에도 작물의 수광량 해석에도 유용하게 활용될 것으로 예상된다.

Keywords

References

  1. Baker, G.H., G. Brown, K. Butt, J.P. Curry, and Scullion, J. 2006. Introduced earthworms in agricultural and reclaimed land: their ecology and influences on soil properties, plant production and other soil biota. Biological Invasions 8: 1301-1316. https://doi.org/10.1007/s10530-006-9024-6
  2. Buck-Sorlin, G.H., R. Hemmerling, J. Vos, and P.H. de Visser. 2009. Modelling of spatial light distribution in the greenhouse: description of the model. In Plant Growth Modeling, Simulation, Visualization and Applications (PMA), 2009 Third International Symposium on (pp. 79-86). IEEE.
  3. Cavazzoni, J., T. Volk, F. Tubiello, and O. Monje 2006. Modelling the effect of diffuse light on canopy photosynthesis in controlled environments. Acta Horticulturae 593:39-45.
  4. Cieslak, M., C. Lemieux, J. Hanan, and P. Prusinkiewicz. 2008. Quasi-Monte Carlo simulation of the light environment of plants. Functional Plant Biology 35:837-849. https://doi.org/10.1071/FP08082
  5. de Visser, P.H., G. van der Heijden, and G. Buck-sorlin. 2014. Optimizing illumination in the greenhouse using a 3D model of tomato and a ray tracer. Frontiers in Plant Science 5:48.
  6. Elings, A., T. Dueck, E. Meinen, and F. Kempkes. 2012, Analysis of the effects of diffuse light on photosynthesis and crop production. Acta Horticulturae 957:45-52.
  7. Gao, S., H. Lin, B. Shen, G. and Fu. 2007. A heavy sea fog event over the Yellow Sea in March 2005: Analysis and numerical modeling. Advances in Atmospheric Sciences 24:65-81. https://doi.org/10.1007/s00376-007-0065-2
  8. Gupta, R., G.N. Tiwari, A. Kumar, and Y. Gupta. 2012. Calculation of total solar fraction for different orientation of greenhouse using 3D-shadow analysis in Auto-CAD. Energy and Buildings 47:27-34. https://doi.org/10.1016/j.enbuild.2011.11.010
  9. Hoffman, L., R.E. Ries, and J.E. Gilley. 1983. Relationship of runoff and soil loss to ground cover of native and reclaimed grazing land. Agronomy Journal 75:599-602. https://doi.org/10.2134/agronj1983.00021962007500040007x
  10. Jongschaap, R.E.E., T.A. Dueck, N. Marissen, S. Hemming, and L.F.M. Marcelis. 2006. Simulating seasonal patterns of increased greenhouse crop production by conversion of direct radiation into diffuse radiation. Acta Horticulturae 718:315-322.
  11. Kahlen, K. and H. Stutzel. 2011. Simplification of a lightbased model for estimating final internode length in greenhouse cucumber canopies. Annals of Botany 108:1055-1063. https://doi.org/10.1093/aob/mcr130
  12. Lamnatou, C. and D. Chemisana. 2013. Solar radiation manipulations and their role in greenhouse claddings: Fresnel lenses, NIR-and UV-blocking materials. Renewable and Sustainable Energy Reviews 18:271-287. https://doi.org/10.1016/j.rser.2012.09.041
  13. Lee, S.Y., D.H. Kang, J.G. Kim, Y.J. Kim, H.G. Choi, and J.W. Lee. 2014. Analysis of environmental characteristics for the greenhouse complex on reclaimed land. Agricultural Mechanization in Korea. 19:262-263 (in Korean).
  14. Maruyama, S., Y. Mori, and S. Sakai. 2004. Nongray radiative heat transfer analysis in the anisotropic scattering fog layer subjected to solar irradiation. Journal of Quantitative Spectroscopy and Radiative Transfer 83:361-375. https://doi.org/10.1016/S0022-4073(02)00378-3
  15. Ohde, T. and H. Siegel. 2013. Spectral effects of Saharan dust on photosynthetically available radiation in comparison to the influence of clouds. Journal of Atmospheric and Solar-Terrestrial Physics 102:269-280. https://doi.org/10.1016/j.jastp.2013.06.004
  16. Pinho, P., T. Hytonen, M. Rantanen, P. Elomaa, and L. Halonen. 2013. Dynamic control of supplemental lighting intensity in a greenhouse environment. Lighting Research and Technology 45:295-304. https://doi.org/10.1177/1477153512444064
  17. Sarlikioti, V., P.H.B. De Visser, and L.F.M. Marcelis. 2011. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional-structural plant model. Annals of Botany 107:875-883. https://doi.org/10.1093/aob/mcr006
  18. Shang, J.Q., M. Tang, and Z. Miao. 1998. Vacuum preloading consolidation of reclaimed land: a case study. Canadian Geotechnical Journal 35:740-749. https://doi.org/10.1139/t98-039
  19. Vos, J., J.B. Evers, G.H. Buck-Sorlin, B. Andrieu, M. Chelle, and P.H.B. De Visser. 2009. Functional-structural plant modelling: a new versatile tool in crop science. Journal of Experimental Botany 345:2101-2115.
  20. Vos, J., L.F.M. Marcelis, and J.B. Evers. 2007. Functionalstructural plant modelling in crop production: adding a dimension. Frontis 22:1-12.