Sensing at nanostructures for agri-food and enviromental applications
dc.check.embargoformat | Embargo not applicable (If you have not submitted an e-thesis or do not want to request an embargo) | en |
dc.check.info | Not applicable | en |
dc.check.opt-out | Not applicable | en |
dc.check.reason | Not applicable | en |
dc.check.type | No Embargo Required | |
dc.contributor.advisor | O'Riordan, Alan | en |
dc.contributor.author | Creedon, Niamh | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.date.accessioned | 2018-10-17T11:22:12Z | |
dc.date.available | 2018-10-17T11:22:12Z | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018 | |
dc.description.abstract | With a predicted population increase of 2.3 billion people, by 2050, agricultural productivity must be vastly improved and made sustainable. Globally, agriculture must deliver a 60% increase in food production to cope with the population demand. Moreover, this needs to be achieved against a changing climate, an exploitation of natural resources, and growing water and land scarcities. New digital technologies can optimise production efficiency and ensure food security and safety while also minimising waste within the production systems and the supply chain. To this end, new sensor technologies are being developed for applications in animal health diagnostics and environmental issues related to the global population, such as food & crop protection, pathogen and toxin detection, and environmental remediation. In this thesis, two new nanosensing diagnostic devices are developed and presented; surface enhanced Raman sensing and electrochemical sensing. Surface-enhanced Raman spectroscopy (SERS) substrates were fabricated by templating a flexible thermoplastic polymer against an aluminium drinks can followed by coating with a silver film, to produce a rough nanostructured metallic surface. SERS is used for both qualitative (molecular fingerprint) and quantitative detection of dye molecules and food toxins. In addition, the SERS technique is also applied in combination with nanoelectrochemical square wave voltammetry to detect nano-concentrations of neonicotinoid pesticides. The enhanced sensitivity and minimum sample preparation requirements provide tremendous opportunities for food safety and security sectors. An impedimetric immunosensor device (with a micro SD style pin-out) was also developed for the serological diagnosis of viruses and antibodies associated with bovine respiratory disease and bovine liver fluke. The silicon chip devices consist of six on-chip nanoband electrodes which can be independently modified with a polymer layer for covalent immobilisation of capture and target biomolecules. This electrochemical biosensor technology provides label-free and cost-efficient sensing capability in a compact size, and demonstrates the potential development of immunoassay-based point-of-use devices for on-farm diagnosis or therapeutic monitoring in animal health applications. | en |
dc.description.status | Not peer reviewed | en |
dc.description.version | Accepted Version | |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Creedon, N. 2018. Sensing at nanostructures for agri-food and enviromental applications. PhD Thesis, University College Cork. | en |
dc.identifier.endpage | 278 | en |
dc.identifier.uri | https://hdl.handle.net/10468/7014 | |
dc.language.iso | en | en |
dc.publisher | University College Cork | en |
dc.relation.project | Science Foundation Ireland (US-Ireland Program SFI12/US/12476) | en |
dc.rights | © 2018, Niamh Creedon. | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | en |
dc.subject | Nanotechnology | en |
dc.subject | SERS | en |
dc.subject | Impedance | en |
dc.subject | Neonicotinoids | en |
dc.subject | Electrochemical sensor | en |
dc.subject | Bovine respiratory disease | en |
dc.thesis.opt-out | false | |
dc.title | Sensing at nanostructures for agri-food and enviromental applications | en |
dc.type | Doctoral thesis | en |
dc.type.qualificationlevel | Doctoral | en |
dc.type.qualificationname | PhD | en |
ucc.workflow.supervisor | alan.oriordan@tyndall.ie |
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