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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #381276
Research Project: Precipitation and Irrigation Management to Optimize Profits from Crop Production

Location: Soil and Water Management Research

Title: Comparison of stationary and mobile canopy sensing systems for irrigation management of corn and soybean in Nebraska

Author
item BHATTI, SANDEEP - University Of Nebraska
item HEEREN, DEREK - University Of Nebraska
item Oshaughnessy, Susan
item NEALE, CHRISTOPHER - University Of Nebraska
item DORSEY, NATE - Valmont Industries, Inc
item GE, YUFENG - University Of Nebraska
item WOLDT, WAYNE - University Of Nebraska
item MAGUIRE, MITCHELL - University Of Nebraska

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 1/30/2021
Publication Date: 7/12/2021
Citation: Bhatti, S., Heeren, D.M., O'Shaughnessy, S.A., Neale, C.M., Dorsey, N., Ge, Y., Woldt, W.E., Maguire, M.S. 2021. Comparison of stationary and mobile canopy sensing systems for irrigation management of corn and soybean in Nebraska [abstract]. ASABE 2021 Annual International Meeting, Virtual and On Demand, July 12-16, 2021, Virtual. Paper No. 2100283.

Interpretive Summary:

Technical Abstract: Irrigation can potentially be better managed using data collected from various sensors installed on different platforms. The accuracy and repeatability of each data source is an important consideration when selecting a sensing system suitable for irrigation management. Four different irrigation scheduling methods were managed with four different water refill levels (0%, 50%, 100%, and 150% of full irrigation) to achieve 16 different method-level combinations during the 2020 growing season in a corn and soybean field in Eastern Nebraska. The four irrigation scheduling methods included common practice, Spatial Evapotranspiration Modeling Interface (SETMI) and two methods based on the Irrigation Scheduling Supervisory Control and Data Acquisition System (ISSCADA). Multispectral (MS) and infrared thermometer (IRT) sensors mounted on different platforms were compared to study the usability of each data source for irrigation management. The different sources included stationary posts on the ground, a center pivot irrigation system, and unmanned aerial systems (UAS). The stationary posts had one thermal infrared sensor each and were installed in two locations for each crop. These two locations were located in the 0% and 100% refill plots. The sensors installed on the center pivot included four pairs of IRTs and four MS sensors. The MS sensors reported the Normalized Difference Vegetation Index (NDVI). The UAS data was taken on multiple days during the season and included thermal infrared imagery and MS imagery capturing both visible and near infrared bands. This study will compare data from these sources and present conclusions on usability and accuracy of the data. Further, comparison of plant water stress and crop health in terms of NDVI will be made between different irrigation refill levels managed in the study. Secondary analysis will include comparison of data (from sensors mounted on the pivot lateral) collected during wet scans (during an irrigation event) and dry scans (pivot rotation without water application), and impact of travel speed during dry scans. Discussion will address both the timing and frequency of dry scans needed for optimal irrigation management.