Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouses
Keywords:
air temperature model, Chinese solar greenhouse, Spanish Almería-type greenhouse, energy balance dynamics, microclimateAbstract
Growth can be defined as an increment in biomass or an increment in weight or height of the organs of the plant influenced by physiological processes. Many of these processes have their limits genetically determined, but climate and irrigation play an important role. Because of its importance, microclimate has been extensively studied in the modeling as a surrounding condition which is imposed by the exterior climate. The main objective of this work was to develop a temperature model based on the energy balance dynamics at two different greenhouse locations - South - eastern Spain and Northern China, and the traditional structures of Chinese solar greenhouse and Almería-type multi-span greenhouse were taken into account. The final model was developed by combining the external conditions, the actuator influence and the crop growth, where the temperature is influenced by soil, crop, cover, actuators, back wall and greenhouse geometry. The model took into account the energy lost by convective and conductive fluxes, as well as the energy supplied by solar radiation and heating systems. The soil and the back wall are the main media for energy storage. The temperature dynamic was determined by a physical model, which considered the energy balance from a holistic point of view - as a sub-model for a customizable interface among the external climate, the plant and the greenhouse system. The influences of different subsystems included in the temperature model were analyzed and evaluated. The results showed a high R2 value of 0.94 for Beijing and 0.95 for Almeria, and the average error was low, of which the MAE and RMSE were 0.71 and 1.365 for Almeria and 0.62 and 1.102 for Beijing, respectively. Thus, the model can be considered as a powerful tool for control design purposes in microclimate systems. Keywords: air temperature model, Chinese solar greenhouse, Spanish Almería-type greenhouse, energy balance dynamics, microclimate DOI: 10.25165/j.ijabe.20171004.2398 Citation: Sanchez-Molina J A, Li M, Rodriguez F, Guzman J L, Wang H, Yang X T. Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouses. Int J Agric & Biol Eng, 2017; 10(4): 66–76.References
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[16] Medrano E, Lorenzo P, Sachez-Guerrero M C, Montero J I. Evaluation and modelling of greenhouse cucumber-crop transpiration under high and low radiation conditions. SciHortic, 2005; 105: 163–175.
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[21] Bot G P A. Greenhouse climate: from physical process to a dynamic model. Universidad de Wageningen, Holanda, 1983.
[22] Boulard T, Baille A. Modelling of Air Exchange Rate in a Greenhouse Equipped with Continuous Roof Vents. J Agr Eng Res, 1995; 61(1): 37–48.
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[24] Rodriguez F, Guzman J L, Berenguel M, Arahal M R. Adaptive hierarchical control of greenhouse crop production. Int J Adapt Control, 2008; 22: 180–197.
[25] Sanchez-Molina J A, Rodriguez F, Guzman J L, Fernandez M D, Arahal M R. Modelling of tomato crop transpiration dynamics for designing new irrigation controllers. Acta Hortic, 2011; 893: 729–738.
[26] Ji Y H, Jiang Y Q, Li T, Zhang M, Sha S, Li M Z. An improved method for prediction of tomato photosynthetic rate based on WSN in greenhouse. Int J Agric & Biol Eng, 2016; 9(1): 146–152.
[27] Marcelis L F M, Buwalda F, Dieleman J A, Dueck T A, Elings A, de Gelder A, et al. Innovations in crop production: A matter of physiology and technology. Acta Hortic, 2014; 1037: 39–46.
[28] Sanchez-Molina J A, Rodriguez F, Guzman J L, Acien F G, Lopez J C. Strategies for control of temperature by increasing the concentration of CO2 by burning in cultivation under plastic. V Congreso Iberico de AgroIngenieria. Lugo, Spain, 2009.
[29] Kittas C, Boulard T, Papadakis G. Natural ventilation of a greenhouse with ridge and side openings: Sensitivity to temperature and wind effects. Transactions of ASAE, 1997; 40(2): 415–425.
[30] Sanchez-Molina J A, Rodriguez F, Guzman J L, Arahal M R. Virtual sensors for designing irrigation controllers in greenhouses. Sensors-Basel, 2012; 11: 15244–15266.
[31] Ha T, Lee I B, Kwon K S, Hong S W. Computation and field experiment validation of greenhouse energy load using Building Energy Simulation model. Int J Agric & Biol Eng, 2015; 8(6): 116–127.
[32] Wan-Liang W, Qi-Di W. Neural network modelling and intelligence control of the distributed parameter greenhouse climate. 14th IFAC World Congress Beijing, China, 1999; 1: 479–484.
[33] ASAE. Heating, ventilating, and cooling greenhouses (EP406.3). American Society of Agricultural Engineering Standards. Michigan. USA, 1998.
[34] Flores-Velazquez J, Montero J I, Baeza E J, Lopez J C. Mechanical and natural ventilation systems in a greenhouse designed using computational fluid dynamics. Int J Agric & Biol Eng, 2014; 1(7): 1–16.
[35] Seginer I. Some artificial neural network applications to greenhouse environmental control. Comput Electron Agr, 1997; 18: 167–186.
[2] Ramiez-Arias A, Rodriuez F, Guzman J L, Berenguel M. Multiobjective hierarchical control architecture for greenhouse crop growth. Automatica, 2012; 48(3): 490–498.
[3] Matysiak B, Nowak J. Carbon dioxide and light effects on photosynthesis, transpiration and ex vitro growth of Homalomena ‘Emerald Gem’ plantlets. SciHortic- Amsterdam, 1994; 57(4): 353–358.
[4] Seginer I, Boulard T, Bailey B J. Neural network models of the greenhouse climate. J Agr Eng Res, 1994; 59: 203–216.
[5] Ramiez-Arias J A. Hierarchical multiobjective control of greenhouse crop production. University of Almeria, 2005. (in Spanish)
[6] Van Straten G. Optimal Control of Greenhouse Cultivation. CRC Press, Boca Raton, FL, USA. 2011, 328.
[7] Vanthoor B H E, Stanghellini C, van Henten E J, de Visser P H B. A methodology for model-based greenhouse design: Part 1, a greenhouse climate model for a broad range of designs and climates. Biosyst Eng, 2011; 110(4): 363–377.
[8] Baille M, Baille L, Laury J C. A simplified model for predicting evapotranspiration rate of nine ornamental species vs. climate factors and leaf area. Sci Hort, 1994; 59: 217–232.
[9] Curry R B. Dynamic simulation of plant growth -Part I. Development of a model. Transation of ASAE, 1971; 14(5): 946–959.
[10] Tong G H, Christopher D M, Li T L, Wang T L. Temperature variations inside Chinese solar greenhouses with external climatic conditions and enclosure materials. 2008; Int J Agric & Biol Eng, 2012; 1(2): 21–26.
[11] Farquhar G D, Caemmerer S, Berry J A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 1980; 1: 78–90.
[12] Jolliet O, Bailey B. The effect of climate on tomato transpiration in greenhouses: measurements and models comparison. Agr Forest Meteorol, 1992; 58: 43–62.
[13] Farzaneh-Gord M, Arabkoohsar A, Bayaz M D D, Khoshnevis A B. New method for applying solar energy in greenhouses to reduce fuel consumption. Int J Agric & Biol Eng, 2013; 6(4): 64-75.
[14] Zhang X, Wang H L, Zou Z R, Wang S J. CFD and weighted entropy based simulation and optimisation of Chinese Solar Greenhouse temperature distribution. Biosystems Eng, 2016; 142: 12–26.
[15] Xu F, Li S, Ma C, Zhao S, Han J, Liu Y, et al. Thermal environment of Chinese solar greenhouses: analysis and simulation. Appl Eng Agr, 2013; 29(6): 991–997.
[16] Medrano E, Lorenzo P, Sachez-Guerrero M C, Montero J I. Evaluation and modelling of greenhouse cucumber-crop transpiration under high and low radiation conditions. SciHortic, 2005; 105: 163–175.
[17] Montero J, Anton A, Munoz P, Lorenzo P. Transpiration from geranium grown under high temperatures and low humidities in greenhouses. Agr Forest Meteorol, 2001: 323–332.
[18] Bakker J. Greenhouse climate control: an integrated approach. Wageningen Academic Pub, 1995.
[19] Jacobson B K, Jones P H, Jones J W, Paramore J A. Real-time greenhouse monitoring and control with an expert system. Comput Electron Agr, 1989; 3(4): 273–285.
[20] Kamp P G H, Timmerman G J. Computerized environmental control in greenhouses. A step by step approach. The Netherlands: IPC Plant, 1996.
[21] Bot G P A. Greenhouse climate: from physical process to a dynamic model. Universidad de Wageningen, Holanda, 1983.
[22] Boulard T, Baille A. Modelling of Air Exchange Rate in a Greenhouse Equipped with Continuous Roof Vents. J Agr Eng Res, 1995; 61(1): 37–48.
[23] Frace J, Thornley J M H. Mathematical models in agriculture. London Butterworths, 1984. 620.
[24] Rodriguez F, Guzman J L, Berenguel M, Arahal M R. Adaptive hierarchical control of greenhouse crop production. Int J Adapt Control, 2008; 22: 180–197.
[25] Sanchez-Molina J A, Rodriguez F, Guzman J L, Fernandez M D, Arahal M R. Modelling of tomato crop transpiration dynamics for designing new irrigation controllers. Acta Hortic, 2011; 893: 729–738.
[26] Ji Y H, Jiang Y Q, Li T, Zhang M, Sha S, Li M Z. An improved method for prediction of tomato photosynthetic rate based on WSN in greenhouse. Int J Agric & Biol Eng, 2016; 9(1): 146–152.
[27] Marcelis L F M, Buwalda F, Dieleman J A, Dueck T A, Elings A, de Gelder A, et al. Innovations in crop production: A matter of physiology and technology. Acta Hortic, 2014; 1037: 39–46.
[28] Sanchez-Molina J A, Rodriguez F, Guzman J L, Acien F G, Lopez J C. Strategies for control of temperature by increasing the concentration of CO2 by burning in cultivation under plastic. V Congreso Iberico de AgroIngenieria. Lugo, Spain, 2009.
[29] Kittas C, Boulard T, Papadakis G. Natural ventilation of a greenhouse with ridge and side openings: Sensitivity to temperature and wind effects. Transactions of ASAE, 1997; 40(2): 415–425.
[30] Sanchez-Molina J A, Rodriguez F, Guzman J L, Arahal M R. Virtual sensors for designing irrigation controllers in greenhouses. Sensors-Basel, 2012; 11: 15244–15266.
[31] Ha T, Lee I B, Kwon K S, Hong S W. Computation and field experiment validation of greenhouse energy load using Building Energy Simulation model. Int J Agric & Biol Eng, 2015; 8(6): 116–127.
[32] Wan-Liang W, Qi-Di W. Neural network modelling and intelligence control of the distributed parameter greenhouse climate. 14th IFAC World Congress Beijing, China, 1999; 1: 479–484.
[33] ASAE. Heating, ventilating, and cooling greenhouses (EP406.3). American Society of Agricultural Engineering Standards. Michigan. USA, 1998.
[34] Flores-Velazquez J, Montero J I, Baeza E J, Lopez J C. Mechanical and natural ventilation systems in a greenhouse designed using computational fluid dynamics. Int J Agric & Biol Eng, 2014; 1(7): 1–16.
[35] Seginer I. Some artificial neural network applications to greenhouse environmental control. Comput Electron Agr, 1997; 18: 167–186.
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Published
2017-07-31
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Sanchez-Molina, J. A., Ming, L., Rodriguez, F., Guzman, J. L., Hui, W., & Xinting, Y. (2017). Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouses. International Journal of Agricultural and Biological Engineering, 10(4), 66–76. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/2398
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Animal, Plant and Facility Systems
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