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

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).

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Publication Details

Journal
Scientific Reports
Published
2024-10-08
DOI
https://doi.org/10.1038/s41598-024-74092-2
Citations
2
Primary Topic
Greenhouse Technology and Climate Control
Type
article
Field-Weighted Citation Impact
1.20

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article

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

Srinivasulu Ale, Curtis B. Adams, Qiong Su, Bala Ram Sapkota
2 citations
Scientific Reports
Greenhouse Technology and Climate Control
1.20
article

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

Srinivasulu Ale, Curtis B. Adams, Qiong Su, Bala Ram Sapkota
article en
2 citations

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).

Scientific ReportsVol. 14(1)
Natural Resources Conservation Service (US), Agricultural Research Service (US), Clemson University (US), Texas A&M University (US)
Cotton Incorporated
Clean water and sanitation
Openalex Percentile: Top 16%
Greenhouse Technology and Climate Control
1.20
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