journal article·2023-08-30Open access

Spatial, Temporal, and Vertical Variability of Ambient Environmental Conditions in Chinese Solar Greenhouses during Winter

Md Nasim Reza, Md Nafiul Islam, Md Zafar Iqbal, Md Shaha Nur Kabir, Milon Chowdhury, Md Ashrafuzzaman Gulandaz, Mohammod Ali, Moon-Ki Jang, Sun-Ok Chung

Applied Sciences· Volume 13· Issue 17

Abstract

The monitoring and control of environmental conditions are crucial as they influence crop quality and yield in Chinese solar greenhouses (CSGs). The objectives of this study were to assess the spatial, temporal, and vertical variability of major environmental parameters in CSGs during winter and to provide greenhouse climate/microclimate characteristics in order to facilitate the monitoring and control of greenhouse environmental conditions. A wireless sensor network (WSN) was deployed in two CSGs: one with crops and one without. Sensors were placed at different locations inside and outside the greenhouses, and the air temperature, humidity, CO2 concentration, light intensity, solar radiation, and wind conditions were measured and analyzed. Significant variability in the spatial, temporal, and vertical distribution of environmental factors was observed in both greenhouses. The average minimum and maximum temperatures and humidity inside the CSG with crops were 9.96 °C (4:00 h) and 24.5 °C (12:00 h), and 32.6% (12:00 h) and 92.1% (5:00 h), respectively. The temperature difference was 2.2 °C between layers in the CSG without crops and 1.4 °C between layers in the CSG with crops. The CO2 concentration in the different layers inside the CSG with crops was highest at night. The average maximum light intensity inside the CSG with crops was 32,660.19 lx, 36,618.12 lx, and 40,660.48 lx (12:00 h to 13:00 h) in the bottom, middle, and top layers, respectively. Sensor positioning in the greenhouse was evaluated by considering the sensors’ data variability. The findings of this study could aid in the development of a better monitoring and control system for CSG’s microclimate during winter. More research is needed on greenhouse microclimate control systems based on this variability analysis, which could improve crop quality and yield in greenhouses.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Greenhouse Technology and Climate Control · Light effects on plants · Plant Water Relations and Carbon Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea

Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea

Department of Biosystems Engineering and Soil Science, College of Agricultural Sciences and Natural Resources, University of Tennessee, Knoxville, TN 37996, USA

Department of Biological and Agricultural Engineering, College of Agriculture and Life Sciences, Texas A&M University, College Station, TX 77843, USA

Department of Agricultural and Industrial Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh

Agricultural Technical Institute, Division of Horticultural Technologies, Ohio State University, Wooster, OH 44691, USA

College of Engineering, Shenyang Agricultural University, Shenyang 110866, China

Funding

Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) · Ministry of Agriculture, Food and Rural Affairs (MAFRA)

References (52)

Show source-provided references
1. Ray, D.K., Mueller, N.D., West, P.C., and Foley, J.A. (2018). Yield trends are insufficient to double global crop production by 2050. PLoS ONE, 13.
2. IPCC (2019). Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems.
3. Nexus approaches to global sustainable development10.1038/s41893-018-0135-8 ↗
4. Effects of environment control on tomato growth and fruit quality in greenhouses
5. Effects of environmental factors on tomato quality in greenhouses
6. Effects of greenhouse covering materials on the crop performance: A review
7. Greenhouse tomato fruit quality
8. Lettuce production in controlled environments
9. Development and test verification of air temperature model for Chinese solar and Spainish Almeria-type greenhouses
10. Solar greenhouse technology for food security: A case study from Humla District, NW Nepal10.1659/MRD-JOURNAL-D-12-00057.1 ↗
11. Assessing the SIMDualKc model for estimating evapotranspiration of hot pepper grown in a solar greenhouse in Northwest China10.1016/j.agsy.2015.05.001 ↗
12. Increase of soil pH in a solar greenhouse vegetable production system10.2136/sssaj2011.0445 ↗
13. Xu, Q., Hu, K., Zhang, H., Han, H., and Li, J. (2020). Organic vegetable cultivation reduces resource and environmental costs while increasing farmers’ income in the North China Plain. Agronomy, 10.10.3390/agronomy10030361 ↗
14. Sustainable greenhouse production during the winter season
15. Performance of a semi-transparent photovoltaic greenhouse for winter crop production
16. The low-temperature response of greenhouse crops: A review
17. New insights of designing thermal insulation and heat storage of Chinese solar greenhouse in high latitudes and cold regions10.1016/j.energy.2021.122953 ↗
18. Performance of a semi-underground solar greenhouse for vegetable production in Northwest China
19. Development of a microclimate model for prediction of temperatures inside a naturally ventilated greenhouse under cucumber crop in soilless media10.1016/j.compag.2018.08.044 ↗
20. Lee, C.K., Chung, M., Shin, K.Y., Im, Y.H., and Yoon, S.W. (2019). A study of the effects of enhanced uniformity control of greenhouse environment variables on crop growth. Energies, 12.10.3390/en12091749 ↗
21. The effect of dynamic solar heat load on the greenhouse microclimate using CFD simulation10.1016/j.renene.2019.01.108 ↗
22. Microclimate and Plant Transpiration of Tomato (Solanum lycopersicum L.) in a Sunken Solar Greenhouse in North China10.3390/agriculture12020260 ↗
23. Analysis of microclimate characteristics in solar greenhouses under natural ventilation10.1007/s12273-021-0771-1 ↗
24. Experimental study on indoor environmental factors of double film solar greenhouse and traditional Chinese greenhouse in cold region10.1177/01445987221098099 ↗
25. Dong, S., Ahamed, M.S., Ma, C., and Guo, H. (2021). A time-dependent model for predicting thermal environment of mono-slope solar greenhouses in cold regions. Energies, 14.10.3390/en14185956 ↗
26. Spatial, vertical, and temporal variability of ambient environments in strawberry and tomato greenhouses in winter10.5307/JBE.2014.39.1.047 ↗
27. Investigation and assessment on microclimate environment of solar greenhouse in North China
28. Sensitivity analysis of CSGHEAT model for estimation of heating consumption in a Chinese-style solar greenhouse10.1016/j.compag.2018.08.040 ↗
29. Influence of heating system on greenhouse microclimate distribution10.13031/2013.29498 ↗
30. CO2 environment in solar greenhouse in Northern China and effects of CO2 enrichment on photosynthetic rate and dry matter production of cucumber
31. An intelligent monitoring of greenhouse using wireless sensor networks
32. Greenhouse microclimate environment adaptive control based on a wireless sensor network
33. Nicolosi, G., Volpe, R., and Messineo, A. (2017). An innovative adaptive control system to regulate microclimatic conditions in a greenhouse. Energies, 10.10.3390/en10050722 ↗
34. Smart greenhouse fuzzy logic based control system enhanced with wireless data monitoring10.1016/j.isatra.2015.12.006 ↗
35. Wireless sensor networks for greenhouse climate and plant condition assessment10.1016/j.biosystemseng.2016.11.005 ↗
36. Monitoring spatial and temporal distribution of temperature and relative humidity in greenhouses based on wireless sensor technology
37. Research into key techniques of the agricultural greenhouse monitoring system based on internet of things
38. Monitoring the operating status of an automatic harmful fly collector for smart greenhouses10.1007/s42853-019-00036-8 ↗
39. Wang, Y., and Chi, Z. (2016, January 21–23). System of wireless temperature and humidity monitoring based on Arduino Uno platform. Proceedings of the 2016 Sixth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC), Harbin, China.10.1109/IMCCC.2016.89 ↗
40. Thermal performance of single span greenhouses with removable back walls10.1016/j.biosystemseng.2015.11.008 ↗
41. The effects of diurnal temperature rise on tomato fruit quality. Can the management of the greenhouse climate mitigate such effects?10.1016/j.scienta.2020.109836 ↗
42. The effect of temperature and light on strawberry production in a solar greenhouse10.1016/j.solener.2019.11.070 ↗
43. Energy management in horticultural applications through the closed greenhouse concept, state of the art10.1016/j.rser.2012.04.022 ↗
44. Spatial and temporal distribution test and analysis of tomato planting environment parameters in solar greenhouse
45. Zhang, C., Liu, H., Wang, C., Zong, Z., Wang, H., Zhao, X., Wang, S., and Li, Y. (2023). Testing and analysis on the spatial and temporal distribution of light intensity and co2 concentration in solar greenhouse. Sustainability, 15.10.3390/su15087001 ↗
46. Rangaswamy, T.C., Sridhara, S., Ramesh, N., Gopakkali, P., El-Ansary, D.O., Mahmoud, E.A., Abdelmohsen, S.A., Abdelbacki, A.M., Elansary, H.O., and Abdel-Hamid, A.M. (2021). Assessing the impact of higher levels of CO2 and temperature and their interactions on tomato (Solanum lycopersicum L.). Plants, 10.10.3390/plants10020256 ↗
47. Kellogg, W.W., and Schware, R. (2019). Climate Change and Society: Consequences of Increasing Atmospheric Carbon Dioxide, Routledge.10.4324/9780429048739 ↗
48. Optimization of greenhouse microclimate parameters considering the impact of CO2 and light
49. Zhang, X., Lv, J., Xie, J., Yu, J., Zhang, J., Tang, C., Li, J., He, Z., and Wang, C. (2020). Solar Radiation allocation and spatial distribution in Chinese solar greenhouses: Model development and application. Energies, 13.10.3390/en13051108 ↗
50. Ryu, M.J., Chung, S.O., Kim, K.D., Huh, Y.K., Hur, S.O., Ha, S.K., Han, K.H., and Kim, H.H. (2012, January 15–18). Determination of sensor locations for monitoring of greenhouse ambient environment. Proceedings of the 11th International Conference on Precision Agriculture, Indianapolis, IN, USA.
51. A tool for the optimal sensor placement to optimize temperature monitoring in large sports spaces10.1016/j.autcon.2016.05.012 ↗
52. Feng, L., Li, H., and Zhi, Y. (2013, January 12–16). Greenhouse CFD simulation for searching the sensors optimal placements. Proceedings of the 2013 Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Fairfax, VA, USA.10.1109/Argo-Geoinformatics.2013.6621972 ↗