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Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI).

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Fitzgerald, G.J., Rodriguez, D. and O'Leary, G. (2010) Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI). Field Crops Research, 116 (3). pp. 318-324.

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Article Link: http://dx.doi.org/10.1016/j.fcr.2010.01.010

Publisher URL: http://www.elsevier.com


Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the "red edge" of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI-CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m-2) from Zadoks 14-37 with an r2 of 0.97 and RMSE of 0.65 g N m-2 when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.

Item Type:Article
Business groups:Crop and Food Science
Keywords:Canopy nitrogen; remote sensing; canopy chlorophyll content index (CCCI); canopy nitrogen index; spectral; nitrogen dilution; wheat; crop modelling.
Subjects:Agriculture > Agriculture (General) > Special aspects of agriculture as a whole > Remote sensing
Plant culture > Field crops > Wheat
Agriculture > Agriculture (General) > Fertilisers
Live Archive:23 Jun 2010 01:33
Last Modified:01 Feb 2022 01:24

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