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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 #197450


item Evett, Steven - Steve

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/1/2007
Publication Date: 7/1/2007
Citation: Peters, R.T., Evett, S.R. 2007. Spatial and temporal analysis of crop conditions using multiple canopy temperature maps created with center-pivot-mounted infrared thermometers. Transactions of the ASABE. 50(3):919-927.

Interpretive Summary: In separate research we have developed a center pivot irrigation system that automatically responds to crop water stress by measuring the leaf temperatures as the system moves over the field. In the system, the sensors are mounted on the pivot main line; and data are fed into a computer that controls the irrigation. Results indicate crop yields and water use efficiencies that are as large as those obtained with the here-to-fore best scientific irrigation scheduling method, but with much less labor and management time. In the present research, we extended the use of the sensing system to provide maps of crop stress across the field. Using a statistical method borrowed from the manufacturing industry, we developed a method of mapping and high lighting 'out-of-control' parts of the field, that is, parts that were stressed. These maps were combined over time to show parts of the field that were stressed (deliberately), and to allow the irrigation manager to see how stressed areas of the field changed over time. This new technology will allow managers to quickly see what parts of a field need attention, without the cost of satellite imagery or aerial photography. The technology is being combined with the center pivot irrigation system control panel, so that a graphical screen will be always available to the irrigation manager.

Technical Abstract: Infrared thermometers were mounted on a research center pivot irrigating a field with varying degrees of induced water stress in 2004 and 2005. The thermometers were used to create canopy temperature maps of the field every time the pivot moved over the field. Individual canopy temperature measurements were scaled to a common time of day to account for temperature differences due to time lag. Twenty-two maps were created during the 2004 irrigation season, and 24 maps were created in 2005. These maps were standardized and combined into a single map for each year using an algorithm modeled after that used to combine multiple years of yield maps. The combined maps for each year were able to show the water-stressed areas of the field. The combined, average, standardized temperatures (Tsd) from the different irrigation treatments were correlated with end-of-year yield, biomass, and total water use in both years (r**2 of ~0.8). The Tsd values were also significantly different across irrigation treatments in 2004. These data demonstrate the ability of this method to help identify stressed areas of a field and therefore management zones for precision agriculture under self-propelled irrigation systems. Statistical process control (SPC) charts were used to evaluate each point on the maps to capture temporal variation and to highlight when temperature differences were due to more than natural variation. Stress deliberately introduced to a particular area of the field late in the 2005 season was not visible to the eye, but was clearly apparent in the SPC charts. These methods utilize the center pivot platform for mounting sensors and can provide producers real-time feedback on both the spatial and temporal variability of a field during a growing season.