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Modeling and analysis of greenhouse environmental factors in north China based on path analysis and stepwise regression

Modeling and analysis of greenhouse environmental factors in north China based on path analysis and stepwise regression

Authors :
Xu Zhang
Lijun Gao
Zhiyong Zhao
Biwu Ren
Source :
Semina: Ciências Agrárias, Vol 41, Iss 6 (2020)
Publication Year :
2020
Publisher :
Universidade Estadual de Londrina, 2020.

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.

Details

Language :
English, Portuguese
ISSN :
16790359 and 1676546X
Volume :
41
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Semina: Ciências Agrárias
Publication Type :
Academic Journal
Accession number :
edsdoj.fa917ecdd604ae5b71379b73e777acc
Document Type :
article
Full Text :
https://doi.org/10.5433/1679-0359.2020v41n6p2587