Analysis of Soil Nutrients based on Potential Productivity Tests with Balanced Minerals for Maize-Chickpea Crop
Volume-3 | Issue-1

A Review on Low Power VLSI Design Models in Various Circuits
Volume-4 | Issue-2

Simulation of Electromagnetic Waves Propagation Using Matlab
Volume-6 | Issue-2

Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2

Test Automation of Motor Over Temperature Protection Extension Module of Drive
Volume-5 | Issue-2

Evaluating Performance of Different Machine Learning Algorithms for the Acute EMG Hand Gesture Datasets
Volume-4 | Issue-3

Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2

Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
Volume-3 | Issue-2

Abstractive Summarization System
Volume-3 | Issue-4

Design of Adaptive Estimator for Nonlinear control system in Noisy Domain
Volume-3 | Issue-3

SMART STREET SYSTEM WITH IOT BASED STREET LIGHT OPERATION AND PARKING APPLICATION
Volume-1 | Issue-1

ENERGY AND POWER EFFICIENT SYSTEM ON CHIP WITH NANOSHEET FET
Volume-1 | Issue-1

Abstractive Summarization System
Volume-3 | Issue-4

A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4

MIMO BASED HIGH SPEED OPTICAL FIBER COMMUNICATION SYSTEM
Volume-1 | Issue-2

Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2

Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3

Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3

VIRTUAL REALITY SIMULATION AS THERAPY FOR POSTTRAUMATIC STRESS DISORDER (PTSD)
Volume-1 | Issue-1

Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2

Home / Archives / Volume-7 / Issue-3 / Article-4

Volume - 7 | Issue - 3 | september 2025

Bioinformatics-Driven Automation in Hydroponics: Nutrient Management System and Growth Prediction Model Open Access
Latha Mercy E.  , Anandhan R., Arun M., Karan S., Prasath D.  123
Pages: 233-246
Cite this article
E., Latha Mercy, Anandhan R., Arun M., Karan S., and Prasath D.. "Bioinformatics-Driven Automation in Hydroponics: Nutrient Management System and Growth Prediction Model." Journal of Electronics and Informatics 7, no. 3 (2025): 233-246
Published
12 August, 2025
Abstract

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.

Keywords

Hydroponics Automation Nutrient Management Data Synthesis Regression Model

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here