Date of this Version
Singh, J., D. M. Heeren, Y. Ge, G. Bai, C. M. U. Neale, M. S. Maguire, and S. Bhatti. 2021. Sensor-based irrigation of maize and soybean in East-Central Nebraska under a sub-humid climate. ASABE Annual International Meeting (virtual), Paper No. 21001044. 12 pages.
The ever increasing pressure on the water resources in Nebraska and other irrigated agricultural areas require innovations and solutions for the governance of water allocation. This study proposes the use of sensor-based method for irrigation which has the potential to improve irrigation water use efficiency (IWUE). Practical methods and algorithms for creating irrigation prescriptions have become vital for the adoption of precision irrigation. A decision support system (DSS) for uniform irrigation was evaluated during 2020 growing season in a sub-humid region. The DSS was managed using soil water and plant feedback. In field practice, a sensor node station comprising of soil water content sensors and infrared thermometer (IRT) was installed in maize and soybean. Root zone water depletion (Drw), and crop water stress index (CWSI) served as the inputs for soil water, and plant feedback, respectively. The timing and depth of irrigation was determined using the DSS. The results of the sensor-based DSS treatment were compared to conventional treatment (managed by a crop consultant) and rainfed (no-irrigation) treatment. Test results for maize and soybean indicated that there was no significant difference in crop yield between sensor-based and conventional treatments. However, the sensor-based DSS treatment witnessed higher IWUE for both maize and soybean. The observed yield for rainfed treatment was significantly lower than the irrigated treatments in maize and soybean. There is a great potential for the use of this DSS system for uniform irrigation in humid and sub-humid regions and future studies are required for the adoption of this technology.