Efficient Solar-Powered IoT Drip Irrigation for Tomato Yield and Quality: An Evaluation of the Effects of Irrigation and Fertilizer Frequency
DOI:
https://doi.org/10.18006/2023.11(5).845.853Keywords:
Drip irrigation system, Fertilization, Time based irrigation, IoT, Tomato yieldAbstract
The optimal management of irrigation and fertilization is crucial for maximizing the yield and quality of tomatoes grown in greenhouses. To address this challenge, this study aimed to develop and implement a solar-powered Internet of Things (IoT) based drip irrigation system for tomato cultivation in plastic roof net houses. Additionally, the study evaluated the effects of water and fertilizer frequency on tomato yield and quality. The experiment was designed with 2 irrigation frequencies (1 time in a day and 1 time in 2 days) and 3 fertilizer frequencies (1 time in 2, 4, and 6 days), with 4 replicates of the tomato variety CH154. The results showed that the solar-powered IoT-based drip irrigation system was efficient, precise in water and fertilizer control, and inexpensive to install and maintain. This allows for real-time monitoring of water flow rate, flow sensor status, treatment status, and electrical parameters on the Node-Red dashboard. Irrigation frequency had a significant impact (p < 0.05) on fruit number, weight, and length per plant, with 1-day irrigation resulting in a higher yield than 2-day irrigation. No significant interaction effect was found between irrigation and fertilizer frequency on tomato yield or quality. In conclusion, the solar-powered IoT-based drip irrigation system demonstrated precise control over water and fertilizer, proving its efficiency and cost-effectiveness. Real-time monitoring capabilities and the observed impact of irrigation frequency underscore its potential for enhancing tomato cultivation in greenhouses, offering a valuable contribution to sustainable and technology-driven agricultural practices.
References
Al-Ali, A.R., Al Nabulsi, A., Mukhopadhyay, S., Awal, M. S., Fernandes, S., &Ailabouni, K. (2019). IoT-solar energy powered smart farm irrigation system. Journal of Electronic Science and Technology, 17(4), 100017. DOI: https://doi.org/10.1016/ j.jnlest.2020.100017 DOI: https://doi.org/10.1016/j.jnlest.2020.100017
Bouzguenda, M., Rajamohamed, S., Shwehdi, M. H., & Aldalbahi, A. (2019). Solar powered smart irrigation system based on low cost wireless network: A senior design project experience. The International Journal of Electrical Engineering & Education, 002072091986041. https://doi.org/10.1177/0020720919860414 DOI: https://doi.org/10.1177/0020720919860414
Deveci, O., Onkol, M., Unver, H. O., & Ozturk, Z. (2015). Design and development of a low-cost solar powered drip irrigation system using Systems Modeling Language. Journal of Cleaner Production, 102, 529–544. https://doi.org/10.1016/ j.jclepro.2015.04.124 DOI: https://doi.org/10.1016/j.jclepro.2015.04.124
Elasbah, R., Selim, T., Mirdan, A., & Berndtsson, R. (2019). Modeling of Fertilizer Transport for Various Fertigation Scenarios under Drip Irrigation. Water, 11(5), 893. https://doi.org/10.3390/w11050893 DOI: https://doi.org/10.3390/w11050893
He, Z., Li, M., Cai, Z., Zhao, R., Hong, T., Yang, Z., & Zhang, Z. (2021). Optimal irrigation and fertilizer amounts based on multi-level fuzzy comprehensive evaluation of yield, growth and fruit quality on cherry tomato. Agricultural Water Management, 243, 106360. https://doi.org/10.1016/j.agwat.2020.106360 DOI: https://doi.org/10.1016/j.agwat.2020.106360
Jensen, M. H., & Malter, A. J. (1995). Protected agriculture: A global review. World Bank Publications, Washington DC.
Jones, J. B. (2008). Tomato plant culture: In the field, greenhouse, and home garden (2nd ed). CRC Press. DOI: https://doi.org/10.1201/9781420007398
Joy, A., & Manivannan, D. (2016). Smart Energy Management and Scheduling using Internet of Things. Indian Journal of Science and Technology, 9(48), 1-6. https://doi.org/10.17485/ijst/2016/v9i48/ 108001 DOI: https://doi.org/10.17485/ijst/2016/v9i48/108001
Juárez-Maldonado, A., Benavides-Mendoza, A., de-Alba-Romenus, K., & Morales-Diaz, A.B. (2014). Estimation of the water requirements of greenhouse tomato crop using multiple regression models. Emirates Journal of Food and Agriculture, 26(10):885-897. DOI:10.9755/ejfa.v26i10.18270 DOI: https://doi.org/10.9755/ejfa.v26i10.18270
Kabalci, Y., Kabalci, E., Canbaz, R., & Calpbinici, A. (2016). Design and implementation of a solar plant and irrigation system with remote monitoring and remote control infrastructures. Solar Energy, 139, 506–517. https://doi.org/10.1016/ j.solener.2016.10.026 DOI: https://doi.org/10.1016/j.solener.2016.10.026
Liwal, K. K., Vohra, M., Sheikh, H., Al-Khatib, O., Abdul Aziz, N., & Copiaco, C. (2020). Implementation of a sustainable and scalable vertical micro-farm. Journal of Applied Horticulture, 22(1), 3–7. https://doi.org/10.37855/jah.2020.v22i01.01 DOI: https://doi.org/10.37855/jah.2020.v22i01.01
Madeti, S. R., & Singh, S. N. (2017). Monitoring system for photovoltaic plants: A review. Renewable and Sustainable Energy Reviews, 67, 1180–1207. https://doi.org/10.1016/j.rser.2016.09.088 DOI: https://doi.org/10.1016/j.rser.2016.09.088
Mahfuz, N., & Al-Mayeed, S. Md. (2020). Smart Monitoring and Controlling System for Aquaculture of Bangladesh to Enhance Robust Operation. 2020 IEEE Region 10 Symposium (TENSYMP), 1128–1133. https://doi.org/10.1109/TENSYMP50017.2020.9230748 DOI: https://doi.org/10.1109/TENSYMP50017.2020.9230748
Mohammad, F. S., Al-Ghobari, H. M., & ElMarazky, M.S.A. (2013). Adoption of an intelligent irrigation scheduling technique and its effect on water use efficiency for tomato crops in arid regions. Australian Journal of Crop Science, 7(3):305-313
Nawandar, N. K., & Satpute, V. R. (2019). IoT based low cost and intelligent module for smart irrigation system. Computers and Electronics in Agriculture, 162, 979–990. https://doi.org/10.1016/j.compag.2019.05.027 DOI: https://doi.org/10.1016/j.compag.2019.05.027
Nițulescu, I.V., & Korodi, A. (2020). Supervisory Control and Data Acquisition Approach in Node-RED: Application and Discussions. IoT, 1(1), 76–91. https://doi.org/10.3390/iot1010005 DOI: https://doi.org/10.3390/iot1010005
Nut, N., Phou, K., Mihara, M., Nuth, S., & Sor, S. (2019). Erd Effects of Drip Irrigation Frequency on Growth and Yield of Melon (Cucumis melo L.) under Net-house's Conditions. International Journal of Environmental and Rural Development, 10 (1), 146-152.
Pawar, P., & Vittal K. P. (2019). Design and development of advanced smart energy management system integrated with IoT framework in smart grid environment. Journal of Energy Storage, 25, 100846. https://doi.org/10.1016/j.est.2019.100846 DOI: https://doi.org/10.1016/j.est.2019.100846
Rahman, M. M., Selvaraj, J., Rahim, N. A., & Hasanuzzaman, M. (2018). Global modern monitoring systems for PV based power generation: A review. Renewable and Sustainable Energy Reviews, 82, 4142–4158. https://doi.org/10.1016/j.rser.2017.10.111 DOI: https://doi.org/10.1016/j.rser.2017.10.111
Salokhe, V. M., Babel, M. S., &Tantau, H. J. (2005). Water requirement of drip irrigated tomatoes grown in greenhouse in tropical environment. Agricultural Water Management, 71 (3), 225-242. DOI: https://doi.org/10.1016/j.agwat.2004.09.003
Sensoy, S., Ertek, A., Gedik, I., & Kucukyumuk, C. (2007). Irrigation frequency and amount affect yield and quality of field-grown melon (Cucumis melo L.). Agricultural Water Management, 88(1–3), 269–274. https://doi.org/10.1016/j.agwat.2006.10.015 DOI: https://doi.org/10.1016/j.agwat.2006.10.015
Stark, E., Kučera, E., Haffner, O., Drahoš, P., &Leskovský, R. (2020). Using Augmented Reality and Internet of Things for Control and Monitoring of Mechatronic Devices. Electronics, 9(8), 1272. https://doi.org/10.3390/electronics9081272 DOI: https://doi.org/10.3390/electronics9081272
Wang, X., & Xing, Y. (2017). Evaluation of the effects of irrigation and fertilization on tomato fruit yield and quality: a principal component analysis. Scientific reports, 7(1), 350. https://doi.org/10.1038/s41598-017-00373-8. DOI: https://doi.org/10.1038/s41598-017-00373-8
Wu, C.K., & Lin, H.C. (2019). Development of Remote Sensing Data Collection and Management Platform via Internet. Sensors and Materials, 31(9), 2703. https://doi.org/10.18494/SAM.2019.2320 DOI: https://doi.org/10.18494/SAM.2019.2320
Zhang, M., Xiao, N., Li, Y., Li, Y., Zhang, D., Xu, Z., & Zhang, Z. (2022). Growth and Fruit Yields of Greenhouse Tomato under the Integrated Water and Fertilizer by Moistube Irrigation. Agronomy, 12(7), 1630. https://doi.org/10.3390/agronomy12071630 DOI: https://doi.org/10.3390/agronomy12071630
Zhu, K., Zhao, Y., Ma, Y., Zhang, Q., Kang, Z., & Hu, X. (2022). Drip irrigation strategy for tomatoes grown in greenhouse on the basis of fuzzy Borda and K-means analysis method. Agricultural Water Management, 267, 107598. https://doi.org/10.1016/ j.agwat.2022.107598 DOI: https://doi.org/10.1016/j.agwat.2022.107598
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