Irrigation scheduling using real-time soil moisture data in corn production

Abstract. Maximizing yields while using water and fertilizer efficiently has become one of the main challenges of irrigated agriculture. Groundwater depletion and nitrate leaching are major environmental issues in north-central Florida. Therefore, the use of real-time data monitoring technologies constitute alternatives to potentially increase the efficiency of water use. In response to this concern, a three-year research project is being performed to assess irrigation scheduling methods in corn production. For this study, two methods were compared: (i) GROW (calendar based): simulates corn grower‘s irrigation practices, where target irrigation rates varied based on growth stages and (ii) SMS (soil moisture sensor based): volumetric water content is monitored using soil moisture sensors which provide real-time data in order to refill the soil profile with irrigation. SMS were installed in both methods and also in non-irrigated plots for comparison. Initial results show no significant differences in corn yield among the irrigation scheduling methods. By contrast, 53 and 43% water savings were achieved when using the SMS irrigation scheduling method compared to the GROW method in 2015 and 2016, respectively. Real-time data technology can be potentially used as a water efficiency management tool for corn production in Florida.