Development of an IoT-Based Monitoring System for a Smart Greenhouse to Study the Effects of Salt Stress and Nitrogen Nutrition on Tomato (Solanum Lycopersicum) Growth)

Abstract

Smart farming management, supported by advances in measurement technologies and intelligent communication systems, plays a crucial role in improving agricultural efficiency. It enables precise control of key environmental factors to sustainably enhance productivity while optimizing the use of essential resources, particularly water and nutrients. This study presents the development of an innovative Internet of Things (IoT)-based system for real-time monitoring and control of a smart greenhouse. The experimental platform, entirely powered by solar energy, was designed and installed at the Maâmora Nuclear Research Center (CENM-CNESTEN) as part of the national Green InnoPROJECT initiative funded by IRESEN. The system enables the simulation of arid and semi-arid conditions to study the physiological impact of salt stress on tomato (Solanum lycopersicum) growth under different nitrogen levels. Two concentrations of ammonium sulfate (100% and 75% of the prescribed dose, corresponding to 0.238 g and 0.178 g of nitrogen per kilogram of soil, respectively) were combined with two irrigation salinity levels (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 \mathrm{g} / \mathrm{L}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4 \mathrm{g} / \mathrm{L}$</tex> of NaCl). Water and nutrient supply were managed through a controlled fertigation system that ensured uniform and continuous distribution of the nutrient solution. Sensors installed on each cultivation table continuously measured temperature, humidity, and electrical conductivity for real-time monitoring of salinity dynamics. Agronomic and biochemical analyses conducted at the flowering and fruiting stages revealed that nitrogen fertilization significantly influences plant tolerance to salinity. Moderate nitrogen input (75%) was beneficial under moderate stress (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$2 \mathrm{g} / \mathrm{L}$</tex> NaCl), while full nitrogen application (100%) provided better performance under severe salinity (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4 \mathrm{g} / \mathrm{L} \text{NaCl}$</tex>).