Smart Control Models Used for Nutrient Management in Hydroponic Crops: A Systematic Review

In recent years, agriculture has significantly evolved with the integration of technology, enabling the development of new cultivation techniques that respond to the growing demand for food and the need to conserve natural resources. In this context, we conducted a comprehensive review of models of intelligent control for managing nutrients in hydroponic systems by analyzing studies from the last five years. The selection of articles was based on the guidelines of PRISMA and research questions, focusing on control techniques based on fuzzy Logic, Artificial Intelligence and artificial Vision. These models are essential to automatically adjust the concentrations of nutrients, adapting to the needs of the plants at each stage of their growth. The review results highlight essential advances but also identify significant challenges, such as the need for precise sensors, the management of large volumes of data, and adapting the models to different crops and conditions. Despite these challenges, the benefits include a more efficient use of nutrients, a reduction in the consumption of water, and increased crop yields. Continuous research in this field is essential to improve the sustainability and productivity of hydroponic systems, offering new opportunities for agriculture in the future. The findings of this review provide a solid basis for evaluating the effectiveness of the control models and their application in real agricultural scenarios.