Optimization of Smart Irrigation Scheduling in Solanum lycopersicum Using IoT-Enabled Soil Moisture Sensors

Advances in Agriculture and Agricultural Sciences | Vol. 12, No. 2, February 2026 | pp. 17–22

DOI: 10.46882/2026.AAAS.120204

Research Article

Title: Optimization of Smart Irrigation Scheduling in Solanum lycopersicum Using IoT-Enabled Soil Moisture Sensors

Names of Authors: Dupont, L. M.¹, Rossi, G.², and Müller, H.³

Authors’ Affiliations: ¹Department of Agricultural Engineering, INRAE, Montpellier, France. ²Department of Agriculture and Food Systems, University of Bologna, Bologna, Italy. ³Institute of Agricultural Engineering, Hohenheim University, Stuttgart, Germany.

Abstract: Precision water distribution models are crucial for mitigating regional agricultural water allocation stresses. This investigation developed and evaluated an automated Internet of Things (IoT) sensor deployment network for irrigation scheduling in greenhouse Solanum lycopersicum crops. Continuous monitoring arrays utilized capacitive soil moisture probes calibrated across distinct substrate horizons alongside microclimate data integration. Automated valves actuated irrigation events when volumetric water content dropped below a target baseline of 22%. Compared to historical calendar-based drip cycles, the IoT responsive framework reduced water consumption metrics by 31.4% without inducing physiological wilting or leaf stomatal closure. Marketable tomato production remained statistically equivalent, yielding 14.2 kg/m², while Water Use Efficiency (WUE) grew from 42.6 kg/m³ to 61.8 kg/m³. Physicochemical evaluations of the fruits indicated a 15.6% increase in total soluble solids (Brix levels) and enhanced ascorbic acid content under precision regulated deficit setups. The operational deployment verified that smart automated frameworks reduce labor input requirements and prevent localized root-zone hypoxia.

Keywords: Precision agriculture; IoT telemetry; Water resource automation; Tomato cultivation; Deficit irrigation; Horticultural technology.

Manuscript Timeline: Received October 24, 2025; Revised December 18, 2025; Accepted January 16, 2026; Published February 21, 2026.

Citation: Dupont, L. M., Rossi, G., and Müller, H. (2026). Optimization of Smart Irrigation Scheduling in Solanum lycopersicum Using IoT-Enabled Soil Moisture Sensors. Advances in Agriculture and Agricultural Sciences, 12(2), pp. 17–22.

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