Compensation for nutrient deficit in NFT hydroponic systems
Abstract
The analysis of nutrient deficiencies in an NFT hydroponic system is essential for proper crop development. Since nutrient availability is crucial to ensuring that plants receive the necessary nutrients for their growth, it is important to implement strategies that allow efficient management and real-time control of nitrogen (N), phosphorus (P), and potassium (K) concentrations, as well as water supply, to compensate for nutrient deficiencies. To dose the deficit, an ON-OFF control system was implemented, which is activated based on the maximum deficit level set by the user. Sensors continuously monitor the pH levels of the circulating solution and the reservoir level to ensure that the system activates upon detecting the minimum threshold, compensating for the missing amounts of nutrients and water through flow sensors and solenoid valves that regulate the passage of solutions and water. The system includes a monitoring mechanism that allows users to check the crop’s status and take corrective actions in case of any system failure. Additionally, the data stored on a microSD card enabled a statistical analysis, which determined that the dosed amounts differed by 5% due to the limitations of the sensors used. However, compared to a system without automatic regulation, it was found that N, P, and K concentrations remained more stable, which favored lettuce growth and reduced resource waste.
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References
Domingues, D. S., Takahashi, H. W., Camara, C. A., & Nixdorf, S. L. (2012). Automated system developed to control pH and concentration of nutrient solution evaluated in hydroponic lettuce production. Computers and Electronics in Agriculture, 84, 53–61. doi:https://doi.org/10.1016/j.compag.2012.02.006
Manav, M., Sameer, S., Suresh, S., & Rijo, J. (2018). IoT based hydroponics system using Deep Neural Networks. Computers and Electronics in Agriculture, 155, 473–486. doi:https://doi.org/10.1016/j.compag.2018.10.015.
Rashid, M., Alioune, S., & Tahsin F, H. (2021). Automated Farming System Using Distributed Controller: A Feasibility Study. ASIAN JOURNAL OF ELECTRICAL AND ELECTRONIC ENGINEERING, 1(1), 21-29. doi:https://doi.org/10.69955/ajoeee.2021.v1i1.11
Suchitrarani , S., Dayanidhi, S., & Khirod, K. (2024). Optimization of an efficient hydroponic cultivation method for high yield of strawberry plants. South African Journal of Botany, 167, 429-440. doi:https://doi.org/10.1016/j.sajb.2024.02.033
Pandey, K., Singh, K., & Singh, A. (2023). Multi-Sensors based smart nutrient reuse management system for closed. Computers and Electronics in Agriculture, 204. doi:https://doi.org/10.1016/j.compag.2022.107495
Sanjuan-Delmás, D., Josa, A., Muñoz, P., Gassó, S., Rieradevall, J., & Gabarrell, X. (2020). Applying nutrient dynamics to adjust the nutrient-water balance in hydroponic crops. A case study with open hydroponic tomato crops from Barcelona. Scientia Horticulturae, 261. doi:https://doi.org/10.1016/j.scienta.2019.108908
Nicol, W., & van Rooyen, I. (2022). Inferential control of the phosphate concentration in hydroponic systems via measurement of the nutrient solution’s pH-buffering capacity. Scientia Horticulturae, 295, 1-8. doi:https://doi.org/10.1016/j.scienta.2021.110820
Yang, T., Samarakoon, U., & Altland, J. (2024). Growth, phytochemical concentration, nutrient uptake, and water consumption of butterhead lettuce in response to hydroponic system design and growing season. Scientia Horticulturae, 332(1), 1-16. doi:https://doi.org/10.1016/j.scienta.2024.113201
Silva, F., Queirós, C., Pinho, T., Boaventura, J., Santos, F., Barroso, T., . . . Martins, R. (2023). Reagent-less spectroscopy towards NPK sensing for hydroponics nutrient solutions. Sensors and Actuators B: Chemical, 395(15). doi:https://doi.org/10.1016/j.snb.2023.134442
Chang, C.-L., Chung, S.-C., Fu, W.-L., & Huang, C.-C. (2021). Artificial intelligence approaches to predict growth, harvest day, and quality of lettuce (Lactuca sativa L.) in a IoT-enabled greenhouse system. Biosystems Engineering, 212, 77-105. doi:https://doi.org/10.1016/j.biosystemseng.2021.09.015
Yang, T., & Kim, H.-J. (2020). Characterizing Nutrient Composition and Concentration in Tomato-, Basil-, and Lettuce-Based Aquaponic and Hydroponic Systems. Water, 12(5), 1-27. doi: https://doi.org/10.3390/w12051259
Casamayor, J., Muñoz, E., Franchino, M., Gallego-Schmid, A., & Shin, H. (2024). Human-powered hydroponic systems: An environmental and economic assessment. Sustainable Production and Consumption, 46, 268-281. doi:https://doi.org/10.1016/j.spc.2024.02.026
