Submitted to: Australian Journal of Agricultural Research
Publication Type: Peer reviewed journal
Publication Acceptance Date: 2/15/2006
Publication Date: 5/12/2006
Citation: Rodriguez, D., Fitzgerald, G.J., Belford, R. 2006. Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts. Australian Journal of Agricultural Research. 57(7):781-789. Interpretive Summary: Crop growth and yield are dependant on plant nitrogen (N). Application of the proper amount of nitrogen fertilizers will enhance yield while too much can lead to movement of N from the field into ground water and streams. Knowing when and where to apply nitrogen would allow farmers to maximize yields and reduce environmental effects. Additionally, it is important to identify where in a field applications of N could be most effectively used by the crop since under water-limiting conditions, the crop cannot take up N, potentially leading to off-farm contamination. Remote sensing can provided a view of entire fields potentially allowing maps of N needs to be produced. In this study, several remotely-sensed indices were tested to estimate plant N status in a rainfed winter wheat experiment in southeastern Australia. The experiment allowed the N and water inputs to vary, mimicking conditions in a farmer’s field. Two of these indices, the canopy chlorophyll content index (CCCI), and the modified spectral ratio planar index (mSRPI) were able to explain 68% and 69%, respectively of the observed variability in the aboveground shoot N of the crop as early as mid-season, irrespective of water status or ground cover. These indices provide the potential to map canopy N spatially across a field and could be used to aid in placement of N in areas of the field that can utilize N most efficiently.
Technical 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) were able to 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 three 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.