Nutrient Sensing, Monitoring, and Control for Hydroponic Crop Production in Smart Greenhouses.

Authors

Arnab Majumder, Md Nasim Reza, Sakib Robin, Ji-Yeon Kang, Sanghwa Lee, Hyeunseok Choi, Dong Hee Noh, Sun-Ok Chung

Published in

Sensors (Basel, Switzerland). Volume 26. Issue 20. Oct 17, 2026. Epub Oct 17, 2026.

Abstract

Hydroponic crop production in smart greenhouses requires accurate nutrient monitoring and reliable control, especially in recirculating systems. This review critically examines sensing principles, data acquisition, control strategies, actuation, feedback, and system integration. Electrical conductivity (EC) and pH are widely used for dosing, but EC cannot quantify individual nutrient concentrations. Emerging technologies include ion-selective electrodes, solid contact and field effect sensors, optical spectroscopy, multi-sensor arrays, and Internet of Things platforms. Their deployment remains constrained by interference, drift, fouling, reference instability, calibration demands, and matrix effects. Control approaches range from threshold-based dosing and EC/pH feedback to proportional-integral-derivative, rule-based, ion-specific, and model-based strategies. Published ion-specific replenishment and hybrid EC-ion studies demonstrate feasibility under tested conditions. However, differences in nutrient formulations, study duration, and error definitions limit conclusions about commercial control accuracy. This review proposes an integrated framework linking sensing, decision making, actuation, and verification, with performance assessed at analytical, temporal, operational, and system/control levels. Future research should prioritize reliable multi-ion sensing, automated data quality checks, delivered dose verification, safe operation during faults, and communication between components. Validation should include complete crop cycles, maintenance, fault recovery, and independent sites. These requirements support evaluation of nutrient use efficiency, operational reliability, and scalability across crops and hydroponic systems under realistic production conditions.

PMID:
42944459
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.

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