Bioinformatics-Driven Automation in Hydroponics: Nutrient Management System and Growth Prediction Model

Effective nutrient management is needed for hydroponic farming. Herein, a bioinformatics-driven automation system that incorporates growth prediction models, automated dosing of nutrients, and real-time analysis of sensor data for optimal plant growth is introduced. For control and monitoring in real-time, a microcontroller is coupled with calibrated TDS, pH, and EC sensors. TDS differentials are used to predict nutrient uptake, and a pH- and EC-based regression model is employed to predict plant height. The technique was validated using a range of plants like tomatoes, lettuce, and beans. Without relying on IoT infrastructure, the outcome is higher nutrient efficiency and accurate height prediction, offering a scalable and cost-effective alternative to existing systems.