A5073956193- Remote Sensing in Agriculture
- Leaf Properties and Growth Measurement
- Spectroscopy and Chemometric Analyses
- Remote Sensing and Land Use
- Smart Agriculture and AI
- Remote-Sensing Image Classification
Charles Sturt University
2025
Australian Centre for Plant Functional Genomics
2019-2020
The University of Adelaide
2019-2020
Quantifying plant water content and nitrogen levels determining phenotypes is important for crop management achieving optimal yield quality. Hyperspectral methods have the potential to advance high throughput phenotyping efforts by providing a rapid, accurate non-destructive alternative estimating biochemical physiological traits. Our study (i) acquired hyperspectral images of wheat plants using system, (ii) developed regression models capable predicting (iii) applied coefficients from...
Abstract Hyperspectral instruments acquire spectral information in many narrow, contiguous bands throughout the visible, near‐infrared and shortwave regions of electromagnetic spectrum. techniques are becoming very powerful tools for characterizing plants nondestructively quantifying their chemical physical properties because ability to provide layered trait within same region. However, effectively make use hyperspectral sensing, an understanding theory behind these techniques, power,...
The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying lines with use efficiency informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise providing measurements a fast manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches expanded to cameras operating different...