Stamford, John (2020) Using spectral signatures as a toolbox for determining crop health status. PhD thesis, University of Essex.
Stamford, John (2020) Using spectral signatures as a toolbox for determining crop health status. PhD thesis, University of Essex.
Stamford, John (2020) Using spectral signatures as a toolbox for determining crop health status. PhD thesis, University of Essex.
Abstract
Spectral based techniques allow for rapid, non-invasive probing of plant and crop performance, and have potential to overcome current phenotyping bottlenecks for breeders and researchers while enabling farmers to optimise the inputs of fertilizer, irrigation and pesticides on their crops to maximise yields and reduce expenditure. The Normalised Difference Vegetation Index (NDVI), uses the reflectance of near infra-red and visible red light to assess the performance and greenness of plants due to variation in chlorophyll content. Increasing the accessibility of NDVI imaging systems through the development of a small, low cost, and easy to use imaging system has potential to increase the uptake of NDVI imaging systems, especially amongst farmers and breeders. We first described a method for using a dual camera system based on the widely available Raspberry Pi platform to produce calibrated NDVI imagery, generating more robust estimates of NDVI than other low cost systems. Then, we developed novel reflectance based spectral indices to assess plant water status, exploiting water content induced changes in leaf internal structure and subsequent variation in the reflectance of NIR. These indices used visible and NIR wavelengths to allow for a reflectance based assessment of leaf water status with standard VIS-NIR spectrometry and imaging systems, which are widely available and already is use by farmers and researchers over other systems that measure water content via short wave infra-red wavelengths, expanding the availability of accessible tools that can be used to assess leaf water status . Finally, we developed a toolbox of spectral techniques can be used to track water and nitrogen of plants, as well as overall plant performance. The index of stomatal conductance (Ig), a thermographic technique, can be used to assess water content, predominantly soil relative water content (RWC). Chlorophyll fluorescence can be used to indicate overall plant performance and changes in soil RWC, and spectral reflectance indices can be used to measure both water and nitrogen content. To date, this is the first spectral toolbox developed utilizing these techniques that has been used to assess water and nitrogen content, demonstrating the potential of a multi-technique spectral toolbox to monitor plant performance. The advantage of a spectral toolbox is primarily through the remote, non-invasive and rapid measurement compared to other techniques, which allows for a higher throughput of measurements, benefiting farmers and crop breeders who need to monitor crops grown over a large area of land, and reduced labour requirements over conventional leaf level technique. The spectral toolbox serves as a foundation for future work using the combination of these techniques, intending to proliferate precision agriculture as a method to apply precise, site-specific applications of agricultural inputs such as fertilizer and irrigation based on crop requirements rather than blanket application, reducing costs to farmers through reduced inventory, fuel and labour. The rapid assessment of plant performance afforded by spectral techniques can additionally improve the phenotyping of future crop varieties for improved yields and growth, a necessary step in mitigating the effects of a changing climate and global population growth.
Item Type: | Thesis (PhD) |
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Subjects: | Q Science > Q Science (General) Q Science > QH Natural history > QH301 Biology Q Science > QK Botany |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Life Sciences, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 27 Jul 2020 14:31 |
Last Modified: | 27 Jul 2022 01:00 |
URI: | http://repository.essex.ac.uk/id/eprint/28330 |
Available files
Filename: Thesis_JDSTAM.pdf