Investigating the Capability of Hyperspectral Imaging for the Estimation of Wheat Leaf Rust Disease
2016-09-03
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Investigating the Capability of Hyperspectral Imaging for the Estimation of Wheat Leaf Rust Disease
Authors
Published Date
2016-09-03
Publisher
Type
Scholarly Text or Essay
Abstract
Detecting disease in crops increases yields and reduces economic loss. Traditional methods detect plant disease severity by hand, but it is a slow, time-consuming, and subjective process. Because there are physical, chemical, and physiological changes in plants with diseases, current research focuses on optical imaging as a more useful technique for monitoring disease. This experiment uses hyperspectral imaging (HSI) to investigate its capability as a diagnostic tool for wheat leaf rust disease. HSI has the potential to create more efficient High Throughput Phenotyping (HTP) methods to assist wheat breeders in the selection of a more resistant wheat variety. To collect data for this purpose, a HSI camera was attached to a ground vehicle that scanned wheat plots on an experimental field in St. Paul a month after the fungus was inoculated into the plots. White panels were laid out into the field to normalize the radiance based on the irradiance. Preprocessing techniques converted the pixels from their digital number to reflectance, which measures any physiological changes. The average spectral signatures of pixels were then compared to scoring data on a spectrum of R (resistant) to S (susceptible). Other categories include MR (moderately resistant), MS (moderately susceptible), etc. However, the spectral signatures that matched with R, MR, MRMS, MS, S, etc. varied unreasonably. R and S spectral lines were very similar to each other and did not exist as a maximum and minimum. This study is inconclusive which could be due to the calibration process since light cannot be controlled perfectly. It could also be because of the lack of control with varied wheat during data collection times.
Description
Related to
Replaces
License
Series/Report Number
Funding information
This research was supported by the Undergraduate Research Opportunities Program (UROP).
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Crowell, Olivia L. (2016). Investigating the Capability of Hyperspectral Imaging for the Estimation of Wheat Leaf Rust Disease. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/182058.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.