Developing Diversity Arrays Technology genetic markers to detect herbicide resistance in annual ryegrass (Lolium rigidum Gaud.)

Research output: ThesisDoctoral Thesis

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Herbicide resistance is a tenacious and constantly evolving problem for the control of weeds worldwide. Effective management strategies are required to reduce the incidence of herbicide resistance and to affect greater herbicide use efficiency, reduce production costs and ensure proper herbicide stewardship (Swanton and Weise, 1991). Australia's most damaging cropping weed annual ryegrass (Lolium rigidum Gaudin) costs the agricultural industries $250-500 million per year to manage, a significant portion of which is for herbicides (Jones et al., 2005). Control of ryegrass is problematic as it has the propensity the evolve herbicide resistance, having already evolved resistance to 11 different herbicide groups and sub-groups. This is due to its high genetic variability as it is an obligate outcrosser (Owen et al., 2007).
The use of genetic assays offers a new and effective tool in weed management through the identification of genetic markers linked to herbicide resistance. Largely, research into weed genetics is dedicated to the elucidation and identification of different forms of herbicide resistance. Fewer studies have been conducted refining this research for the development of the next generation of wide scale herbicide resistance assays, the tools needed to combat the increasing herbicide resistance problem (Tranel and Horvath, 2009). This thesis addresses this by detailing the development of assays using two genotyping technologies, Diversity Arrays Technology (DArT) and Diversity Arrays Technology genotyping by sequencing (DArTseq), to identify and link genetic markers to multiple forms of herbicide resistance in annual ryegrass.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Charles Sturt University
  • Pratley, Jim, Principal Supervisor
  • Kilian, Andrzej, Principal Supervisor
Publication statusPublished - 2017

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