Modeling and analysis of greenhouse environmental factors in north China based on path analysis and stepwise regression
DOI:
https://doi.org/10.5433/1679-0359.2020v41n6p2587Keywords:
Greenhouse, Environmental factors, Path analysis, Stepwise regression analysis.Abstract
To explore the relationship between environmental factors in a greenhouse on sunny/cloudy days, an environmental factor model was developed using path analysis and stepwise regression analysis. The environmental factors studied include greenhouse air temperature (GAT), greenhouse air humidity (GAH), soil temperature (ST), soil humidity (SH), greenhouse radiation (GR), and carbon dioxide concentration (CDC). The results showed that on a sunny day, the models can describe the GAT and GAH well (R2=0.957, 0.936), and the model’s tested determination coefficient was above 0.87. However, due to the delay and other main control factors of ST and SH, the models’ determination coefficient was poor (R2=0.587, 0.625). However, there was a fifth-order polynomial fitting relationship between ST and SH (R2=0.817). On a cloudy day, the coupling effect between dependent variables and environmental factors was well described (R2 ? 0.97). The model test results for GAT and ST were better (R2=0.997, 0.981), and the GAH and SH model test results were also good (R2=0.789,0.882). In summary, the established coupling model of greenhouse environmental factors was suitable for simple greenhouse environment prediction, allowing greenhouse managers to easily predict greenhouse environmental change trends and reduce the cost of testing, laying a foundation for the subsequent establishment of a simpler, more accurate greenhouse factor model.Downloads
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Chayangira, J. (2012). Effects of different ventilation strategies on the microclimate and transpiration of a rose crop in a greenhouse. Greener Journal of Science, Engineering and Technological Research, 3(5), 166-180. doi: 10.1029/2005TC001829
Chen, Q. Y., & Wang, Z. F. (1996). Dynamic simulation of the thermal environment in the energy-saving solar greenhouse. Journal of China Agricultural University,(1), 67-72. doi: CNKI:SUN:ZWZY.0.2019 96-05-013
Dimokas, G., Katsoulas, N, Tchamitchian, M., & Kittas, C. (2008). Validation of a climate simulator (Sim Gre C) inmediterranean greenhouses during winter period [J]. Proceedings of the 4th International Conference on Information and Communication Technologies in Bio and Earth Sciences, 9, 173-181. Recovered from www.researchgate.net/publication/251880917
Gong, X., Zhang, R. L., & Chao, H. X. (2011). Diurnal variation characteristics and influencing factors of photosynthesis and transpiration in 4 coconut cultivars. Journal of Tropical Crops, 32(2), 221-224. doi: CNKI:SUN: RDZX.0.2011-02-008
Jiang, Y. X., Qin, L. L., & Shi, C. (2013). Modeling of the modern greenhouse humidity system based on mechanism model. Journal of Jiangnan University (Natural Science Edition), 12(5), 535-540. doi: 10.3969/j.issn.1671-7147.2013.05.006
Li, Y. Z., Wu, D. R., & Yu, Z. (1994). Simulation and experimental study of solar greenhouse microclimate[J]，Journal of Agricultural Engineering, 1(19):130-136. doi: CNKI:SUN:NYGU.0.1994-01-019
Luo, Y. Z., & Cheng, Z. Y. (2011). Effects of water stress on water potential, transpiration rate, and stomatal conductance of alfalfa leaves. Journal of Grassland Science, 19(2), 215-221. doi: 10.11733/j.issn.1007-0435.2011.02.006
Mashonjowa, E., Ronsse, F., Mubvuma, M., Milford, J. R., & Pieters, J. G. (2013). Estimation of leaf wetness duration for greenhouse roses using a dynamic greenhouse climate model in Zimbabwe [J]. Computers and Electronics in Ag-Riculture, 95, 70-81.doi: 10.1016/j.compag.2013.04.007
Sai, Y. Z. G. T., Ma, W. J., & Ta, N. (2019). Effect of soil temperature on soil moisture content in a solar greenhouse, Journal of China Agricultural University, 24(3), 102-108. doi: 10.11841/j.issn.1007-4333. 2019.03.13
Singh, G., Singh, P. P., Lubana, P. P. S., & Singh, K. G. (2006). Formulation and validation of a mathematical model of the microclimate of a greenhouse[J]. Renewable Energy, 31(10): 1541-1560. doi: 10.1016/j. renene. 2005.07.011
Speetjens, B., Hemming, S., Wang, D., & Tsay, J. R.(2012). Design of a vegetable greenhouse system for subtropical conditions in Taiwan. 1-60. Recovered from http://edepot.wur.nl/238571
Ta, N., Wu, S. L., Ma, W. J., Chen, B., & Zhu, Y. K. (2015). The peak-fitting method for soil temperature variation in a solar greenhouse under different water content is proposed. Transactions of the Chinese Society of Agricultural Engineering, 30(20), 204-210. doi: 10.3969/j.issn.1002-6819.2014.20.025
Zhou, X. X., Ma, Y. Q., & Zhang, Z. Q. (2005). Effects of environmental factors on photosynthetic and transpiration characteristics of pepper. Journal of Plant Resources and Environment, 14(4), 15-20. doi: CNKI:SUN: ZWZY.0.2005-04-003
Zwart, H. F. D. (1996). Analyzing energy-saving options in greenhouse cultivation using a simulation model. Doctoral thesis, Wageningen University, Wageningen, Netherlands. Recovered from https://www.r esearchgate.net/publication/40189453
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Published
2020-09-19
How to Cite
Zhang, X., Gao, L., Zhao, Z., & Ren, B. (2020). Modeling and analysis of greenhouse environmental factors in north China based on path analysis and stepwise regression. Semina: Ciências Agrárias, 41(6), 2587–2596. https://doi.org/10.5433/1679-0359.2020v41n6p2587
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