Remote detection of water stress in cotton using a center pivot irrigation system-mounted sensor package

Authors: SAPKOTA, BALA - Texas A&M University; Adams, Curtis; SU, QIONG - Clemson University; ALE, SRINIVASULU - Texas A&M Agrilife

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2024
Publication Date: 10/8/2024
Citation: Sapkota, B.R., Adams, C.B., Su, Q., Ale, S. 2024. Remote detection of water stress in cotton using a center pivot irrigation system-mounted sensor package. Scientific Reports. Sci Rep 14, 23436 (2024). https://doi.org/10.1038/s41598-024-74092-2.
DOI: https://doi.org/10.1038/s41598-024-74092-2

Interpretive Summary: PendingThere are several approaches that have been developed for measuring or estimating water stress in crops, which can be used for irrigation scheduling or for other applications. Many of these approaches use sensors installed in the field, including soil moisture sensors or infrared temperature (IRT) sensors focused on the crop canopy. However, adoption of these approaches is generally low, perhaps due to the logistical challenges of sensors installed in the field or other constraints. Alternatively, the Water Deficit Index (WDI) was developed to estimate crop water stress using data from remote IRT sensors not embedded in the canopy, plus ancillary data. The objective of this research was to evaluate the performance of WDI in estimating water stress in cotton, using data from a sensor package attached to the truss of a center pivot irrigation system. This design put the sensors out of the way of farming operations on the ground and allowed measurements to be made across the field as the pivot moved. Overall, the system was quite effective at estimating crop water stress in cotton. There was some indication that water stress was overestimated when water stress levels were relatively low and other ideas for improving accuracy of the system are discussed in the paper.

Technical Abstract: Much research has been invested in infrared temperature (IRT)-based methods for cotton (Gossypium hirsutism L.) water stress detection using in-field sensors, but adoption of these is low, perhaps due to logistical challenges. Alternatively, the Water Deficit Index (WDI) was developed for crop water stress assessment using remote sensors not embedded in the canopy. The objective of this research was to evaluate the performance of a sensor package—including modern IRT and normalized difference vegetation index (NDVI) sensors facing downward at 45°, and a mini weather station—attached unintrusively to a center pivot irrigation system for detecting cotton water stress using WDI. Sensor packages were evaluated in a two-year field study that included four irrigation treatments (0, 30, 60, and 90% ET replacement) and in two production cotton fields. Overall, the tested system was effective at distinguishing crop water stress among irrigation rates. Comparison of the results to a ground-based station and simulations indicated that WDI overestimated water stress at the highest irrigation rate, but performed well otherwise. Accuracy of the system could be improved by measuring canopy coverage (Fc) from the same vantage point as the IRT and NDVI sensors (from the pivot, downward at a 45° angle).