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    Remote sensing of nitrogen and water stress in wheat

    Access Status
    Fulltext not available
    Authors
    Tilling, A.
    O'Leary, G.
    Ferwerda, J.
    Jones, S.
    Fitzgerald, G.
    Rodriguez, D.
    Belford, Robert
    Date
    2007
    Type
    Journal Article
    
    Metadata
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    Citation
    Tilling, Adam K. and O'Leary, Garry J. and Ferwerda, Jelle G. and Jones, Simon D. and Fitzgerald, Glenn J. and Rodriguez, Daniel and Belford, Robert. 2007. Remote sensing of nitrogen and water stress in wheat. Field Crops Research. 104 (1-3): pp. 77-85.
    Source Title
    Field Crops Research
    DOI
    10.1016/j.fcr.2007.03.023
    ISSN
    03784290
    Faculty
    School of Agriculture and Environment
    Faculty of Science and Engineering
    Department of Agribusiness and Wine Science
    School
    Department of Agribusiness
    Remarks

    The link to the journal’s home page is: http://www.elsevier.com/wps/find/journaldescription.cws_home/503308/description#description. Copyright © 2007 Elsevier B.V. All rights reserved

    URI
    http://hdl.handle.net/20.500.11937/47238
    Collection
    • Curtin Research Publications
    Abstract

    Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24).The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 8C warmer than irrigated treatments (< 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and waterstress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers.

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