Hyperspectral imaging to determine pigment content in leaves
Agriculture has played an increasingly large role in the cultivation of crops in society today, whether for food or raw materials in the production of many items that we use in our daily lives. The rapid increase in the world’s population and widespread trade has seen an exponential increase in dema...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/10356/76254 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Agriculture has played an increasingly large role in the cultivation of crops in society today, whether for food or raw materials in the production of many items that we use in our daily lives. The rapid increase in the world’s population and widespread trade has seen an exponential increase in demand for these goods. This increases the demand for agricultural crops as a result of globalisation and has spurred the research and development for new innovations in the technology being used in agriculture, in order to fulfil the rising demand for agricultural crops through achieving faster and larger yields.
Hyperspectral imaging is a non-destructive method of imaging that allows fast and effective crop-monitoring. It can provide a significant amount of spectral and spatial information on the subject at a specific user defined region-of-interest (ROI). Its ability to distinguish between minute differences in physical, chemical and biological characteristics has shown huge potential in future breakthroughs that this technology can bring for precision agriculture, even outside of just monitoring crops.
In this research, a snapshot hyperspectral imaging framework was used to obtain data on the samples for further processing. This framework was coupled with the software Andor Solis to capture data from the scanning process. The data processing was then done using MATLAB, a fast and effective data processing software that helps to present the raw data obtained in easier-to-read formats such as images and graphs.
The hyperspectral imaging technique has not only shown great potential in precision agriculture, its benefits are also highly anticipated in fields such as medical diagnostics and food technology as well. |
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