Research conducted in South Australia has provided strong evidence that field-based near infrared (NIR) devices can be used to provide accurate and consistent predictions of nitrogen content in wheat and barley crops grown across different environments.
Using a hand-held FieldSpec Spectrometer, Landmark Pfitzner and Kleinig agronomist, Michael Zerner, who is based at Eudunda, was able to provide non-destructive predictions of nitrogen content in cereal crops.
The University of Adelaide set up trials at Mintaro, Roseworthy and Loxton in 2016 and 2017 with funding from the South Australian Grain Industry Trust (SAGIT).
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More than 1500 plant samples were taken at different growth stages and analysed for nitrogen content and water-soluble carbohydrates in conjunction with non-destructive field-based NIR spectroscopy using the FieldSpec unit.
Trials were sown using a range of commercial wheat and barley cultivars across a variety of:
- Times of sowing
- Nitrogen management strategies
- Soil types
- Row spacings.
Mr Zerner says the robust data set ensured there was a sufficient range in nitrogen content and water-soluble carbohydrate data to develop an accurate and predictive model suitable to all end-users.
"Data analysis and interpretation was a crucial part of this research to link near-infrared spectral data to actual nitrogen content and water-soluble carbohydrate values," he says.
"Spectral data was analysed using extremely powerful software, the Unscrambler X (CAMO), which was used for partial least squares regression analysis in creating the near-infrared spectral predictive models."
A residual predictive deviation (RPD) value the standard deviation of the population and standard error in cross-validation for the NIR predictions was used to evaluate the predictive ability of the calibration models developed.
Data analysis and interpretation was a crucial part of this research to link near-infrared spectral data to actual nitrogen content and water-soluble carbohydrate values.
An RPD value between three and five is considered good for screening applications, Mr Zerner says.
"Consequently, an RPD value of 2.41 indicates the model is potentially suitable for screening applications of nitrogen content and robust enough to be used to make management decisions," he says.
"The ability to predict nitrogen content using the whole spectra of data with devices such as the FieldSpec hand-held unit is a significant improvement on the current NDVI (normalised difference vegetation index) sensors available.
"Instead of using two or three specific wavelengths, as is used in calculating NDVI, the method used in this study uses every wavelength from 350 nanometres to 1100nm.
"This provides much more information relating to the chemical composition of the crop canopy compared to just how green it is in the visible spectra, as per NDVI sensors."
Targeting specific yields
Mr Zerner says having a real-time, non-destructive measure of nitrogen content will improve the ability of grain growers to target specific grain yield and quality parameters for a given season.
This provides much more information relating to the chemical composition of the crop canopy compared to just how green it is in the visible spectra, as per NDVI sensors.
"For example, plant nitrogen will relate to the supply of mineralised and fertiliser nitrogen and could help growers manage grain protein through rapid crop assessments for timely applications of nitrogen," Mr Zemer says.
He says the NIR prediction could be used to comfortably distinguish nutritional zones within the paddock for improved management of nitrogen fertiliser.
"The ability to make cheap measurements in-field in a matter of seconds enables many more measurements to be taken and therefore provides much more information across the entire paddock rather than targeting a single test in specific zones, as currently practiced with tissue testing," he says.
More information: Michael Zerner, 0439 802 600, firstname.lastname@example.org