Horticulture, Environment, and Biotechnology : HEB

Korean Society of Horticultural Science (한국원예학회)
권호 표지
DOI QR코드

DOI QR Code

Modeling of Transpiration of Paprika (Capsicum annuum L.) Plants Based on Radiation and Leaf Area Index in Soilless Culture

  • Ta, The Hung (Department of Plant Science, Seoul National University) ;
  • Shin, Jong-Hwa (Department of Plant Science, Seoul National University) ;
  • Ahn, Tae-In (Department of Plant Science, Seoul National University) ;
  • Son, Jung-Eek (Department of Plant Science, Seoul National University)
  • Received : 2010.11.01
  • Accepted : 2011.02.07
  • Published : 2011.06.30
⟨ Previous Next ⟩

Abstract

Modeling of crop transpiration is important to manage the irrigation strategy in soilless culture. In this study, the transpiration of paprika plants (Capsicum annuum L.) grown in rockwool was analyzed considering the relationship between incident radiation (RAD) and leaf area index (LAI). Coefficients of the simplified Penman-Monteith formula were calibrated in order to calculate the transpiration rate of the crop ($T_r$). Transpiration rate per floor area was measured by weighing plants with load cells. The following model was developed: $T_r=a[1-\exp(-k{\times}LAI)]{\times}RAD/{\lambda}+b$ for estimating transpiration of paprika. Determination coefficient for the linear regression between estimations and measurements of daily transpiration was 0.80 with a slope of 0.93. In validation, the model showed high agreement between estimated and measured values of daily transpiration. Radiation showed a great effect on transpiration of paprika plants. The results indicated the simplified Penman-Monteith formula could be used to predict water requirements and improve irrigation control in soilless culture. However the model coefficients require parameter adjustments for specific climate and crop conditions.

Keywords

References

  1. Antony, E. and R.B. Singadhupe. 2004. Impact of drip and surface on growth, yield and WUE of capsicum (Casicum annuum L.). Agr. Water Manage 65:121-132. https://doi.org/10.1016/j.agwat.2003.07.003
  2. Boulard, T. and R. Jemaa. 1993. Greenhouse tomato crop transpiration model application to irrigation control. Acta Hort. 355:381-387.
  3. Baille, M., A. Baill, and J.C. Laury. 1994. A simplified model for predicting evapotranspiration rate of nine ornamental species vs. climate factors and leaf area. Sci. Hort. 59:217-232. https://doi.org/10.1016/0304-4238(94)90015-9
  4. Boulard, T. and S. Wang. 2000. Greenhouse crop transpiration simulation from external climate conditions. Agr. For. Moteorol. 100:25-34. https://doi.org/10.1016/S0168-1923(99)00082-9
  5. Carmassi, G., L. Incrocci, R. Maggini, F. Malorgio, F. Tognoni, and A. Pardossi. 2007. An aggregated model for water requirements of greenhouse tomato grown in closed rockwool culture with saline water. Agr. Water Manage. 88:73-82. https://doi.org/10.1016/j.agwat.2006.10.002
  6. De Graaf, R. and J. Van den Ende. 1981. Transpiration of evapotranspiration of the glasshouse crops. Acta Hort. 119:147-158.
  7. Hamer, P.J.C. 1996. Validation of model used for irrigation control of a greenhouse crop. Acta Hort. 458:75-81.
  8. Jolliet, O. and B.J. Bailley. 1992. The effect of climate on tomato transpiration in greenhouse: measurements and models comparison. Agr. For. Meteorol. 58:43-63. https://doi.org/10.1016/0168-1923(92)90110-P
  9. Marcelis, L.F.M., E. Heuvelink, and J. Goudrian. 1998. Modeling biomass production and yield of horticultural crops: a review. Sci. Hort. 74:83-111. https://doi.org/10.1016/S0304-4238(98)00083-1
  10. Moreno, M.M., F. Ribas, A. Moreno, and M.J. Cabello. 2003. Physiological response of a pepper (Capsicum annuum L.) crop to different trickle irrigation rate. J. Spain Agri. Hort. 1:65-74.
  11. Motulsky, H. and A. Christopoulos. 2003. Fitting models to biological data using linear and nonlinear regression. A practical guide to curve fitting. GraphPad Sofware Inc. San Diego. CA., USA.
  12. Medrano, E., P. Lorenzo, M.C. Sanchez-Guerrero, and J.I. Montero. 2005. Evaluation and modeling of greenhouse cucumber-crop transpiration under high and low radiation conditions. Sci. Hort. 105:163-175. https://doi.org/10.1016/j.scienta.2005.01.024
  13. Nedefhoff, E.M. 1984. Light interception of a cucumber crop at different stages of growth. Acta Hort. 148:525-534.
  14. Nobel, P.S. and S.P. Long. 1985. Canopy structure and light interception, pp. 41-49. In: J. Coombs, D.O. Hal, S.P. Long, and J.M.O. Scurlock (eds.). Techniques in bioproductivity and photosynthesis. Pergamon Press. Oxford. UK.
  15. Stanghellini, C. 1987. Transpiration of greenhouse crops: an aid to climate management. PhD dissertation. Wageningen Agricultural University, Wageningen, Netherlands, p. 150.
  16. Smittle, D.A., W.L. Dickens, and J.R. Stansell. 1994. Irrigation regimes affect yield and water use by bell pepper. J. Amer. Soc. Hort. Sci. 119:396-939.
  17. Senzen, S.M., A. Yazar, and S. Eker. 2006. Effect of drip irrigation regimes on yield and quality of filed grown bell pepper. Agr. Water Manage. 81:115-131. https://doi.org/10.1016/j.agwat.2005.04.002

Cited by

  1. Penman-Monteith 모델에 의한 식물공장 내 상추(Lactuca sativa L.)의 증산량 예측 vol.22, pp.2, 2011, https://doi.org/10.12791/ksbec.2013.22.2.182
  2. Analyses of Transpiration and Growth of Paprika (Capsicum annuum L.) as Affected by Moisture Content of Growing Medium in Rockwool Culture vol.32, pp.3, 2014, https://doi.org/10.7235/hort.2014.13177
  3. Development of a real-time irrigation control system considering transpiration, substrate electrical conductivity, and drainage rate of nutrient solutions in soilless culture of paprika (Capsicum annu vol.80, pp.6, 2011, https://doi.org/10.17660/ejhs.2015/80.6.2
  4. 파프리카 재배에서 계절별 광환경 조건과 증산량 예측에 근거한 관수공급 기준 제시 vol.24, pp.1, 2011, https://doi.org/10.12791/ksbec.2015.24.1.001
  5. 무토양재배용 암면과 코이어 배지의 수분 이동 및 함수율 특성 비교 vol.24, pp.1, 2011, https://doi.org/10.12791/ksbec.2015.24.1.039
  6. Irrigation water consumption modelling of a soilless cucumber crop under specific greenhouse conditions in a humid tropical climate vol.47, pp.2, 2011, https://doi.org/10.1590/0103-8478cr20151538
  7. 온실의 환경요인을 이용한 인공신경망 기반 수경 재배 파프리카의 증산량 추정 vol.26, pp.4, 2017, https://doi.org/10.12791/ksbec.2017.26.4.411
  8. Theoretical and Experimental Analysis of Nutrient Variations in Electrical Conductivity-Based Closed-Loop Soilless Culture Systems by Nutrient Replenishment Method vol.9, pp.10, 2011, https://doi.org/10.3390/agronomy9100649
  9. 토마토 암면재배에서 정전용량 측정장치를 기반으로 한 급액방법 구명 vol.28, pp.4, 2011, https://doi.org/10.12791/ksbec.2019.28.4.366
  10. Estimating transpiration rates of hydroponically-grown paprika via an artificial neural network using aerial and root-zone environments and growth factors in greenhouses vol.60, pp.6, 2011, https://doi.org/10.1007/s13580-019-00183-z
  11. Estimating transpiration rates of hydroponically-grown paprika via an artificial neural network using aerial and root-zone environments and growth factors in greenhouses vol.60, pp.6, 2011, https://doi.org/10.1007/s13580-019-00183-z
  12. Examination of Yield Components and the Relationship Between Dry Matter Production and Fruit Yield in Greenhouse Sweet Pepper (Capsicum annuum) vol.90, pp.3, 2011, https://doi.org/10.2503/hortj.utd-263