Pivot-Mounted Sensors

The next step forward for advancing irrigation management in the Great Plains is increasing adoption rates of scientific irrigation scheduling, with a primary benefit of improving crop water productivity and reducing nitrate leaching. Taking advantage of a center pivot as a mobile sensing platform, this research focused on thermal and multispectral sensors mounted on the center pivot lateral as a data stream for irrigation automation. The center pivot at the research field site was equipped with a high-speed drive and could complete an entire revolution in only four hours. This made it feasible to pause irrigation and collect data during a dry revolution (to avoid cooling the canopy with irrigation water) in the early afternoon when crop stress was most likely to occur.

Data from pivot-mounted sensors were found to be consistent with data from sensors on other platforms (stationary post, drone, satellite). Thermal stress was detected using the sensing system without incurring yield loss, indicating that thermal data may be used to trigger irrigation without a yield penalty in a subhumid location. Irrigation scheduling using pivot-mounted sensors was found to reduce irrigation applications as compared to common practice while maintaining crop yield. Compared to using unmanned aircraft to determine canopy temperature, thermal sensors mounted on the pivot required minimal data processing, could collect data in windy conditions, and had a low cost of operation (electrical energy consumed was about $3.60 per dry revolution).

The current initial cost of pivot-mounted thermal and multispectral sensors is high when compared to the increase in profits from reduction of irrigation application. However, the use of pivot-mounted sensors for other aspects of crop production (e.g., nutrient management, weed/disease/pest identification) could also increase the value of the system. Future work should utilize artificial intelligence (e.g., machine learning) to combine data from pivot-mounted sensors with other data streams to create easy-to-use software for irrigation automation.

Toward Automated Irrigation with Sensors on the Pivot

Funding and Partners

  • Irrigation Innovation Consortium (with funding from FFAR)
  • Valmont Industries (Omaha, NE)
  • Daugherty Water for Food Global Institute at the University of Nebraska
  • UNL Department of Biological Systems Engineering
  • Eastern Nebraska Research, Extension and Education Center (Mead, NE)
  • USDA ARS Conservation and Production Research Laboratory (Bushland, TX)

Popular Press

Journal Articles

  • Bhatti, S., Heeren, D. M., O’Shaughnessy, S. A., Neale, C. M. U., LaRue, J. L., Melvin, S. R., Wilkening, E. J., & Bai, G. 2023. Toward automated irrigation management with integrated crop water stress index and spatial soil water balance. Precision Agriculture. https://doi.org/10.1007/s11119-023-10038-4
  • Bhatti, S., Heeren, D. M., Evett, S. R., O’Shaughnessy, S. A., Neale, C. M. U., Rudnick, D. R., Franz, T. E., & Ge, Y. 2022. Crop response to thermal stress without yield loss in irrigated maize and soybean in Nebraska. Agricultural Water Management 274. https://doi.org/10.1016/j.agwat.2022.107946
  • Bhatti, S., D. M. Heeren, S. A. O’Shaughnessy, S. R. Evett, M. S. Maguire, S. P. Kashyap, and C. M. U. Neale. 2022. Comparison of stationary and mobile canopy sensing systems for irrigation management of maize and soybean in Nebraska. Applied Engineering in Agriculture 38(2): 331-342. https://doi.org/10.13031/aea.14945