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The application of remote sensing to estimate nitrogen levels across Field Pea genotypes

Burgos, F.A., O'Hara, G.W., Kobryn, H. and Howieson, J. (2009) The application of remote sensing to estimate nitrogen levels across Field Pea genotypes. In: 15th Australian Nitrogen Fixation Conference, 8 - 13 November, Margaret River, Western Australia.


Different forms of electromagnetic energy can be used by remote sensing instruments for target detection and characterisation. In vegetation studies the information about the canopy gathered by remote sensing sensors is the result of the interaction between electromagnetic energy and the vegetation. The vegetation spectral features are related by the interaction of the plant with its environment. In particular, legume plants are able to establish symbiosis with a root nodule inhabiting bacteria. This symbiosis can provide nitrogen available to the plants from atmospheric N,. The effects of the N supply on the pigments and the leaf structure are an increase of the number of chloroplasts, the number and size of cells per leaf resulting in an expansion of leaf area and volume. Thus levels of nitrogen can be detected using spectral analysis at wavelengths sensitive to light absorbing pigment or chlorophyll. Therefore, the purpose of this work is to investigate whether remote sensing is able to estimate rates of nitrogen and biomass across different field pea genotypes using digital multi-spectral imagery. The field trial was located in the wheatbelt of Western Australia. The field pea crop development was assessed by two methods: groundtruth or plant sample extraction for dry weight and nitrogen content, and remote sensing analysis using vegetation indices based on combinations of different bands. The results of the groundtruth showed a negative correlation between nitrogen levels and dry weight with time. However, there were significant differences across genotypes in nitrogen levels but there were no differences in dry weight. Spectral analysis of the remote sensing data identified some vegetation indices that allowed differentiation of genotypes and showed correlations with nitrogen contents and dry weight.

Publication Type: Conference Item
Murdoch Affiliation: School of Biological Sciences and Biotechnology
School of Environmental Science
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