Towards Affordable Precision Irrigation: An Experimental Comparison of Weather-Based and Soil Water Potential-Based Irrigation Using Low-Cost IoT-Tensiometers on Drip Irrigated Lettuce

Abstract

Predictive weather-based models are widely used to schedule irrigation through the estimation of crop evapotranspiration. However, perceiving real-time crop water requirements remains a challenge. This research aims at field validating and exploiting a low-cost IoT soil moisture tensiometer prototype to consequently compare weather-based irrigation to soil water moisture-based irrigation in terms of yield and crop water productivity. The prototype is based on the ESP32 microcontroller and BMP180 barometric sensor. When compared to a mechanical tensiometer, the IoT prototype proved its accuracy, registering an average R2 equal to 0.8 and an RMSE range of 4.25–7.1 kPa. In a second step, the irrigation of a Romaine lettuce field (Lactuca sativa L.) cultivated under a drip system was managed according to two different scenarios: (1) using the data feed from the IoT tensiometers, irrigation was performed to keep the soil water potential between −15 and −25 kPa; (2) using the data provided by the in-situ weather station to estimate the crop water requirements. When comparing the yield, no significant difference was registered between the two scenarios. However, the water productivity was significantly higher, registering a 36.44% increment in scenario 1. The experiment highlights the water-saving potential achievable through real-time monitoring of soil moisture conditions. Since it is a low-cost device (82.20 USD), the introduced prototype facilitates deploying and managing a fleet of sensors for soil water potential live mapping.