Spatial assessment of the physiological status of wheat crops as affected by water and nitrogen supply using infrared thermal imagery
D. Rodriguez A C , V. O. Sadras B , L. K. Christensen A and R. Belford AA Department of Primary Industries, Primary Industries Research Victoria, PB 260, Horsham, Vic. 3401, Australia.
B CSIRO–APSRU, PMB 2, Glen Osmond, SA 5064, Australia.
C Corresponding author; present address: Agricultural Production Systems Research Unit, Department of Primary Industries and Fisheries, PO Box 102, Toowoomba, Qld 4350, Australia. Email: daniel.rodriguez@dpi.qld.gov.au
Australian Journal of Agricultural Research 56(9) 983-993 https://doi.org/10.1071/AR05035
Submitted: 10 February 2005 Accepted: 23 June 2005 Published: 28 September 2005
Abstract
This work addresses the need for meaningful spatial indices of the physiological condition of field crops for site-specific management and variable rate application in precision agriculture. Precision agriculture is designed to target crop inputs according to within-field requirements to increase profitability while protecting the environment. The objectives of this work were to (a) develop a canopy physiological stress index with spatial resolution commensurate with the needs of site-specific management, and (b) test the physiological meaning of this index by exploring its association with key processes and variables at leaf and crop levels. We report results from a single-year field experiment where different levels of irrigation, wheat crop density, and nitrogen supply were applied to increase the expression of within-season variability. We defined a canopy stress index (CSI) as the difference between canopy (Tc), and air temperature (Ta), normalised by vapour pressure deficit (VPD): CSI = (Tc – Ta)/VPD. A novel method to extract canopy temperatures (Tc) from complex digital thermal images was developed, thus allowing for the spatial characterisation of CSI. CSI is expected to be positive and high if the capacity of the canopy to dissipate heat is reduced as when stomata close. CSI accounted for 80% of the variation in growth rate and yield, compared with 46–49% explained by the normalised difference vegetation index (NDVI). Most of the variation in crop response variables was related to water supply. The physiological meaning of this index was reinforced by its significant association with gas exchange variables measured at the leaf-level. The potential for the use of digital thermal imaging in precision agriculture is discussed.
Additional keywords: precision agriculture, thermal digital imaging, stomatal conductance, photosynthesis, NDVI.
Acknowledgments
This work was fully funded by the Department of Primary Industries of Victoria,
Australia. The collaboration with Victor Sadras was funded by GRDC (project CS0212). J. Angus provided valuable comments on this manuscript. We greatly appreciate and commend the excellent technical work provided by Russel Argall.
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