Date of Award

2018

Document Type

Doctoral Thesis

Degree Name

Doctor of Philosophy

Department

Department of Chemistry

First Advisor

Dr. Ambrose Furey

Second Advisor

Dr. Martin Danaher

Abstract

In this project, cost-effective multi-class analytical methods were developed to detect a range of antiparasitic, feed additive and pesticide substances in foodstuffs of animal origin. These substances have the potential to enter the food chain through their occurrence as residues either through the animals themselves or other routes e.g. contamination. To ensure the continued safety of food destined for human consumption regulatory control limits have been established for permitted levels of these residues in foods of animal origin. Despite these controls the continued monitoring of foodstuffs is necessary to ensure these limits are not breached and that substances are not administered except as approved to food producing animals. In this work an analytical method for the detection of pyrethrin and pyrethroid residues in the fat of different animal species was developed. This was advantageous in that, residues such as tralomethrin and flumethrin not easily assessed by GC could be directly analysed by LC. In addition this method employed green chemistry which allowed for minimal solvent usage, reduced waste outputs, improved sample throughput and improved laboratory turnaround times. To take advantage of this economic and sensitive method it was extended to the analysis of pesticide residues in honey matrices. A new automated high-throughput sample preparation protocol for the detection and quantification of anthelmintic residues in animal tissue was also developed. This was a significant contribution to the area of residue control as the use of automated steps allowed for a reduction in method variability and improved sample throughput for laboratories. Finally a new HILIC approach for the analysis of polar anticoccidial residues in animal muscle was developed and an older C8 approach updated to include a larger number of analytes.

Access Level

info:eu-repo/semantics/openAccess

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