Australia
August 17, 2020
A new study by research fellow Dr Huajian Liu at APPF’s The Plant Accelerator, at the Waite campus, has unearthed the optimal wavelength ranges, band centres and bandwidths for Hyperspectral sensors to determine the nitrogen content in Wheat.
Healthy plants generally have 3-4% of their total nitrogen housed in the above ground tissue. Nitrogen is used for a variety of essential procedures to maintain plant health and increase yield. Present in both chlorophyll and a major component in amino acids, nitrogen management and diagnosis of of plant nitrogen status are essential to maximising yields and are best based on real-time monitoring of biomass and plant nitrogen levels. Traditional methods of chemical nitrogen analysis are generally destructive, time consuming and expensive in a laboratory approach.
The fast-developing area of hyperspectral imaging integrates imaging and spectroscopy technologies and provides both visual representations of targets as well as the corresponding spectral information. The integration of spatial and spectral information has enabled the merging of computer vision technologies and spectroscopy, providing enriched datasets for the non-destructive measurement of plants.
In contrast to spectrometers, hyperspectral cameras usually have limited spectral ranges and wider bandwidths. In proximal sensing, hyperspectral cameras have been used to estimate nitrogen in wheat and pepper. In aerial remote sensing, hyperspectral systems have been successfully used to measure the nitrogen content of wheat, mangrove and maize.
Plant (a) (left) was treated with 50 mg/kg of N whereas plant (b) was treated with 200 mg/kg N. The red colour indicates a high concentration of Nitrogen and blue inidcates a low concentration.
Dr Liu’s study has demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of nitrogen content in wheat accurately. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of nitrogen in wheat.
Full Article:
The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat
Topics
Species
