A Monitoring Experiment of Melon Greenhouse’s Environment in Tropical Climate
DOI:
https://doi.org/10.56261/built.v22.255397Keywords:
Greenhouse, Melon Farm, Tropical Climate MonitoringAbstract
Greenhouses in tropical climates are designed to control passively the environment, protecting plants from pest and extreme climate condition, which is increasingly important due to climate change. This research aims to monitor a melon greenhouse's environment in a tropical climate to understand light intensity, pollutants, and climate conditions. Indoor and outdoor conditions of melon greenhouse were real-time monitored by Vantage VUE model, DAVIS weather station, PM2.5 meter and noise meter. The findings examined that peak light intensities were recorded at 135,600 lux outdoors and 32,050 lux indoors at noon, with an average light transmittance of 38%. Additionally, PM2.5 levels remained stable around 26-30 µg/m³, and sound levels decreased from 60 dB in the morning to 45 dB. These pollution levels did not disturb farmer and indoor melon in winter season. However, other seasoning period needs to be monitored for long term adaptation of application and climate change mitigation. These research findings will support greenhouse design for human comfort and plant growth, considering and optimizing temperature and humidity conditions. IoTs mechanisms and devices were proposed high costly potential for monitoring sensor, networking process, comparative and reliable data collection for further next step of greenhouse integration. Lastly, upcycled transparent roof from LDPE were suggested to be continually used with minor development or plug-in devices for increasing light shade during the mid-daytime.
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References
Abd Ali, F. S., Mahdi, K. H., & Jawad, E. A. (2019). Humidity effect on diffusion and length coefficient of radon in soil and building materials. Energy Procedia, 157, 384-392. https://doi.org/10.1016/j.egypro.2018.11.203
American Society of Heating Refrigerating and Air-Conditioning Engineers. (2017). 2017 Ashrae handbook. Fundamentals (Inch-pound).
Anagu, Emmanuel, John., Felicia, Cletus., Greg, Maksha, Wajiga. (2023). Smart Monitoring System for Vegetable Greenhouse. International Journal of Computer Applications, 10.5120/ijca2023923134
Ares, G., Ha, B., & Jaeger, S. R. (2021). Consumer attitudes to vertical farming (indoor plant factory with artificial lighting) in China, Singapore, UK, and USA: A multi-method study. Food Research International, 150, 110811. https://doi.org/10.1016/j.foodres.2021.110811
Asha Bharathi, S., Meghana, B., Meghana, S., Akshatha, M., & Hamsa, S. (2024). Monitoring of Smart Greenhouse Using Internet of Things (IoT), Singapore.
Avgoustaki, D. D., & Xydis, G. (2021). Energy cost reduction by shifting electricity demand in indoor vertical farms with artificial lighting. Biosystems Engineering, 211, 219-229. https://doi.org/10.1016/j.biosystemseng.2021.09.006
Baldocchi, D. D., Keeney, N., Rey-Sanchez, C., & Fisher, J. B. (2022). Atmospheric humidity deficits tell us how soil moisture deficits down-regulate ecosystem evaporation. Advances in Water Resources, 159, 104100. https://doi.org/10.1016/j.advwatres.2021.104100
Elio, R., Massimo, B., Pietro, T., & Carlo, B. (2019). A method to implement a monitoring system based on low-cost sensors for micro-environmental conditions monitoring in greenhouses. In A. Coppola, G. Carlo Di Renzo, G. Altieri & P. D'Antonio (Eds), Innovative biosystems engineering for sustainable agriculture, forestry and food production (pp. 775-782). Springer Cham. https://doi.org/10.1007/978-3-030-39299-4_83
Dash, R., Dash, D. K., & Biswal, G. C. (2021). Classification of crop based on macronutrients and weather data using machine learning techniques. Results in Engineering, 9, 100203. https://doi.org/10.1016/j.rineng.2021.100203
Delina, L. L., Ocon, J., & Esparcia, E. (2020). What makes energy systems in climate-vulnerable islands resilient? Insights from the Philippines and Thailand. Energy Research & Social Science, 69, 101703. https://doi.org/10.1016/j.erss.2020.101703
Dumas, G., Masson, V., Hidalgo, J., Edouart, V., Hanna, A., & Poujol, G. (2021). Co-construction of climate services based on a weather stations network: Application in Toulouse agglomeration local authority. Climate Services, 24, 100274. https://doi.org/10.1016/j.cliser.2021.100274
Enfan, Z., Jun, M., Lingfei, Z., & Bohang, C. (2021). Analysis of human body comfort based on variable precision fuzzy rough set of double universe. In S. Shi, L. Ye & Y. Zhang (Eds), Artificial intelligence for communications and networks (pp. 170-184). Springer Cham. https://doi.org/10.1007/978-3-030-90199-8_17
Ferreira Preston, H. A., Henrique de Sousa Nunes, G., Preston, W., Barbosa de Souza, E., de Lima Ramos Mariano, R., Datnoff, L. E., & Araújo do Nascimento, C. W. (2021). Slag-based silicon fertilizer improves the resistance to bacterial fruit blotch and fruit quality of melon grown under field conditions. Crop Protection, 147, 105460. https://doi.org/10.1016/j.cropro.2020.105460
Gibbons, J., Collins, K., Kazdan, D., & Frissell, N. (2022). Grape Version 1: First prototype of the low-cost personal space weather station receiver. HardwareX, 11, e00289. https://doi.org/10.1016/j.ohx.2022.e00289
Goldoni, E., Savazzi, P., Favalli, L., & Vizziello, A. (2022). Correlation between weather and signal strength in LoRaWAN networks: An extensive dataset. Computer Networks, 202, 108627. https://doi.org/10.1016/j.comnet.2021.108627
Huang, T., Niu, J., Xie, Y., Li, J., & Mak, C. M. (2020). Assessment of “lift-up” design’s impact on thermal perceptions in the transition process from indoor to outdoor. Sustainable Cities and Society, 56, 102081. https://doi.org/10.1016/j.scs.2020.102081
Jiuhong, Z., Kunjie, L., Xiaoqian, Z., Mingxiao, M., & Jiahui, Z. (2022). Study of human visual comfort based on sudden vertical illuminance changes. Buildings, 12(8), 1127-1127. https://doi.org/10.3390/buildings12081127
Ketjoy, N., Thanarak, P., & Yaowarat, P. (2022). Case studies on system availability of PVP plants in Thailand. Energy Reports, 8, 514-526. https://doi.org/10.1016/j.egyr.2021.11.266
Meng, X., Yan, L., & Liu, F. (2022). A new method to improve indoor environment: Combining the living wall with air-conditioning. Building and Environment, 216, 108981. https://doi.org/10.1016/j.buildenv.2022.108981
Naseer, M., Persson, T., Righini, I., Stanghellini, C., Maessen, H., & Verheul, M. J. (2021). Bio-economic evaluation of greenhouse designs for seasonal tomato production in Norway. Biosystems Engineering, 212, 413-430. https://doi.org/10.1016/j.biosystemseng.2021.11.005
Romanis, T., Lebedeva, M., Kolesnikov, A., Sapanov, M., & Sizemskaya, M. (2022). A dataset of soil microstructure features and the weather conditions affecting them from 2005 to 2021 in the Caspian Depression. Data in Brief, 41, 107957. https://doi.org/10.1016/j.dib.2022.107957
Prageeth, J., Matias, Q., Mahmoud, A., & Clayton, M. (2020). Humans-as-a-sensor for buildings: Intensive longitudinal indoor comfort models. Buildings, 10(10), 174. https://doi.org/10.3390/BUILDINGS10100174
Li, D., Park, S. E., Lee, M. R., Kim, J. C., Lee, S. J., & Kim, J. S. (2021). Soil application of Beauveria bassiana JEF-350 granules to control melon thrips, thrips palmi Karny (Thysanoptera: Thripidae). Journal of Asia-Pacific Entomology, 24(3), 636-644. https://doi.org/10.1016/j.aspen.2021.05.010
Li, H., Guo, Y., Zhao, H., Wang, Y., & Chow, D. (2021). Towards automated greenhouse: A state of the art review on greenhouse monitoring methods and technologies based on internet of things. Computers and Electronics in Agriculture, 191, 106558. https://doi.org/10.1016/j.compag.2021.106558
Likitswat, F. (2021). Urban farming: Opportunities and challenges of developing greenhouse business in Bangkok metropolitan region. Future Cities and Environment, 7(1), 8. https://doi.org/10.5334/fce.118
Lingkai, C., Joon-Ho, C., Xiaomeng, Y., Yolanda, G., Shrikanth, N., & Maryann, P. (2019). A personal visual comfort model: Predict individual’s visual comfort using occupant eye pupil size and machine learning. IOP Conference Series: Materials Science and Engineering, 609(4), 042097. https://doi.org/10.1088/1757-899X/609/4/042097
Loukatos, D., Fragkos, A., & Arvanitis, K. G. (2021). Exploiting voice recognition techniques to provide farm and greenhouse monitoring for elderly or disabled farmers, over Wi-Fi and LoRa interfaces. In D. Bochtis, C. Achillas, G. Banias & M. Lampridi (Eds.), Bio-Economy and Agri-production (pp. 247-263). Academic Press.
Makiel, M., Skiba, M., Kisiel, M., Maj-Szeliga, K., Błachowski, A., Szymański, W., & Salata, D. (2022). Formation of iron oxyhydroxides as a result of glauconite weathering in soils of temperate climate. Geoderma, 416, 115780. https://doi.org/10.1016/j.geoderma.2022.115780
Moreno-Carbonell, S., Sánchez-Úbeda, E. F., & Muñoz, A. (2020). Rethinking weather station selection for electric load forecasting using genetic algorithms. International Journal of Forecasting, 36(2), 695-712. https://doi.org/10.1016/j.ijforecast.2019.08.008
Office of Agricultural Economics. (2019). Agricultural Economic Report 2019 and Outlook for 2020.
Oliveira Filho, J. d. S., de Oliveira Lopes, R., de Oliveira Araújo, M., Silva Magalhães, M., Dayson de Sousa Vasconcelos, M., Rayssa Leite Lima, A., de Holanda Bastos, F., & Gervasio Pereira, M. (2022). How does increasing humidity in the environment affect soil carbon and nitrogen stocks and the C/N ratio in tropical drylands? Evidence from northeastern Brazil. CATENA, 213, 106208. https://doi.org/10.1016/j.catena.2022.106208
Sarabi, B., & Ghashghaie, J. (2022). Evaluating the physiological and biochemical responses of melon plants to NaCl salinity stress using supervised and unsupervised statistical analysis. Plant Stress, 4, 100067. https://doi.org/10.1016/j.stress.2022.100067
Song, B., & Park, K. (2021). Temperature trend analysis associated with land-cover changes using time-series data (1980–2019) from 38 weather stations in South Korea. Sustainable Cities and Society, 65, 102615. https://doi.org/10.1016/j.scs.2020.102615
Soto, F., Thompson, R. B., Granados, M. R., Martínez-Gaitán, C., & Gallardo, M. (2018). Simulation of agronomic and nitrate pollution related parameters in vegetable cropping sequences in Mediterranean greenhouses using the EU-Rotate_N model. Agricultural Water Management, 199, 175-189. https://doi.org/10.1016/j.agwat.2017.12.023
Sudprasert, S., & Jaroensen, P. (2021). Study of the thermal performance of water-soaked porous wall under a tropical climate. International Journal of Low-Carbon Technologies, 16(4), 1453-1463. https://doi.org/10.1093/ijlct/ctab072
Suman, L., Ramesh Kumar, S., Shashank, S., & Sonu, J. (2020). Greenhouse monitoring using WSN and SENSEnuts nodes. AIP Conference Proceedings, 2294(1), 030006. https://doi.org/10.1063/5.0031711
Tristán, A. I., Abreu, A. C., Aguilera-Sáez, L. M., Peña, A., Conesa-Bueno, A., & Fernández, I. (2022). Evaluation of ORAC, IR and NMR metabolomics for predicting ripening stage and variety in melon (Cucumis melo L.). Food Chemistry, 372, 131263. https://doi.org/10.1016/j.foodchem.2021.131263
Rustia, D. J. A., Lin, C. E., Chung, J.-Y., Zhuang, Y.-J., Hsu, J.-C., & Lin, T.-T. (2020). Application of an image and environmental sensor network for automated greenhouse insect pest monitoring. Journal of Asia-Pacific Entomology, 23(1), 17-28. https://doi.org/10.1016/j.aspen.2019.11.006
Qian, Y., Hibbert, L. E., Milner, S., Katz, E., Kliebenstein, D. J., & Taylor, G. (2022). Improved yield and health benefits of watercress grown in an indoor vertical farm. Scientia Horticulturae, 300, 111068. https://doi.org/10.1016/j.scienta.2022.111068
Saadon, T., Lazarovitch, N., Jerszurki, D., & Tas, E. (2021). Predicting net radiation in naturally ventilated greenhouses based on outside global solar radiation for reference evapotranspiration estimation. Agricultural Water Management, 257, 107102. https://doi.org/10.1016/j.agwat.2021.107102
Wang, J., Chen, M., Zhou, J., & Li, P. (2020). Data communication mechanism for greenhouse environment monitoring and control: An agent-based IoT system. Information Processing in Agriculture, 7(3), 444-455. https://doi.org/10.1016/j.inpa.2019.11.002
Wang, Q., Su, H., Yue, N., Li, M., Li, C., Wang, J., & Jin, F. (2021). Dissipation and risk assessment of forchlorfenuron and its major metabolites in oriental melon under greenhouse cultivation. Ecotoxicology and Environmental Safety, 225, 112700. https://doi.org/10.1016/j.ecoenv.2021.112700
Wang, W., Li, S., Guo, S., Ma, M., Feng, S., & Bao, L. (2021). Benchmarking urban local weather with long-term monitoring compared with weather datasets from climate station and EnergyPlus weather (EPW) data. Energy Reports, 7, 6501-6514. https://doi.org/10.1016/j.egyr.2021.09.108
Weiyu, W., Yuan, F., Weizhen, W., Qipeng, H., & Nianyu, Z. (2020). Study on factors correlation of personal lighting comfort model in cyber-physical human centric systems. In 2020 Fifth Junior Conference on Lighting (Lighting). https://doi.org/10.1109/LIGHTING47792.2020.9240565
Weldeslasie, D. T., Assres, G., Grønli, T.-M., & Ghinea, G. (2021). Automated climate monitoring system: The case of greenhouse industries in Ethiopia. Internet of Things, 15, 100426. https://doi.org/10.1016/j.iot.2021.100426
Wijewardane, M. A., Sudasinghe, S. A. N. C., Punchihewa, H. K. G., Wickramasinghe, W. K. D. L., Philip, S. A., & Kumara, M. R. S. U. (2018). Experimental investigation of visual comfort requirement in garment factories and identify the cost saving opportunities. International Journal of Architectural, Civil and Construction Sciences, 12(6), 671-676.
Wongwatcharapaiboon, J. (2022). An investigation of transparent materials affecting growing process of greenhouse plants in tropical climate [Paper presentation]. 19th International Conference on Sustainable Energy Technologies (SET2022), Istanbul.
Wongwatcharapaiboon, J., Chankasem, C., Lertwattanarak, P., & Riffat, S. (2023). A novel synthesis of light transmission from upcycled polyethylene terephthalate polymer and low-density polyethylene for greenhouse design in tropical climate. International Journal of Low-Carbon Technologies, 18, 1182-1191. 10.1093/ijlct/ctad100
Xia, S., Nan, X., Cai, X., & Lu, X. (2022). Data fusion based wireless temperature monitoring system applied to intelligent greenhouse. Computers and Electronics in Agriculture, 192, 106576. https://doi.org/10.1016/j.compag.2021.106576
Xu, W., Song, W., & Ma, C. (2020). Performance of a water-circulating solar heat collection and release system for greenhouse heating using an indoor collector constructed of hollow polycarbonate sheets. Journal of Cleaner Production, 253, 119918. https://doi.org/10.1016/j.jclepro.2019.119918
Xu, K., Guo, X., He, J., Yu, B., Tan, J., & Guo, Y. (2022). A study on temperature spatial distribution of a greenhouse under solar load with considering crop transpiration and optical effects. Energy Conversion and Management, 254, 115277. https://doi.org/10.1016/j.enconman.2022.115277
Yang, S., Wan, M. P., Ng, B. F., Dubey, S., Henze, G. P., Chen, W., & Baskaran, K. (2021). Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems. Applied Energy, 297, 117112. https://doi.org/10.1016/j.apenergy.2021.117112
Zarid, M., Bueso, M. C., & Fernández-Trujillo, J. P. (2020). Seasonal effects on flesh volatile concentrations and texture at harvest in a near-isogenic line of melon with introgression in LG X. Scientia Horticulturae, 266, 109244. https://doi.org/10.1016/j.scienta.2020.109244
Zhu, F. L., & Feng, Q. Q. (2021). Recent advances in textile materials for personal radiative thermal management in indoor and outdoor environments. International Journal of Thermal Sciences, 165, 106899. https://doi.org/10.1016/j.ijthermalsci.2021.106899
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