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Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE

Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts

D. Rodriguez A E , G. J. Fitzgerald B , R. Belford C and L. K. Christensen D
+ Author Affiliations
- Author Affiliations

A Agricultural Production Systems Research Unit (APSRU), Department of Primary Industries and Fisheries, PO Box 102, Toowoomba, Qld 4350, Australia.

B USDA-ARS, U.S. Water Conservation Laboratory, 4331 E. Broadway Rd, Phoenix, AZ 85040, USA.

C Primary Industries Research Victoria, PO Box 260, Horsham, Vic. 3401, Australia.

D Nordic Gene Bank, PO Box 41, SE-23053 Alnarp, Sweden.

E Corresponding author. Email: daniel.rodriguez@dpi.qld.gov.au

Australian Journal of Agricultural Research 57(7) 781-789 https://doi.org/10.1071/AR05361
Submitted: 12 October 2005  Accepted: 17 February 2006   Published: 14 July 2006

Abstract

We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.

Additional keywords: water stress, plant density, remote sensing, nitrogen stress index.


Acknowledgments

This work was fully funded by the Department of Primary Industries of Victoria, Australia. We greatly appreciate the excellent field work done by Russel Argall. We appreciate the comments made by Dr Graeme Wright and Tom Clarke on early versions of this manuscript. We also thank the personnel at the USA Water Conservation Laboratory for their hard work and dedication.


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