The Statistics for the Australian Grains Industry project (SAGI) was a Grains Research and Development Corporation (GRDC) program under the leadership of Prof Brian Cullis, University of Wollongong. This program is currently growing through independent regional nodes and the Southern node is presented by the University of Adelaide, School of Agriculture Food and Wine.
The current issue of The GRDC’s Ground Cover Supplement highlights the important role statistics plays in the research investment of the Australian Grains Industry. Two of the articles are written by Waite Biometry Hub members, Drs Beverley Gogel and Julian Taylor. Extracts of these are below and the full issue of the Ground Cover Supplement can be found at: https://grdc.com.au/GCS126?pg=1&all=0
Mapping genes a faster route to crop improvement
Authors: Dr Julian Taylor and Dr David Butler
Plant breeders have enthusiastically embraced an Australian software program that maps plant genomes to drive efficiency gains in the breeding pipeline. The ASMap software program has been widely adopted by researchers at the University of Adelaide’s Waite campus, who are now using it to identify molecular markers linked to economically important traits for wheat and chickpea breeding.
ASMap is a linkage mapping program developed by Statistics for the Australian Grains Industry (SAGI) in conjunction with research staff from the Australian Wheat and Barley Molecular Marker Program. Breeders use linkage mapping to identify genetic markers that have a close proximity on the chromosome to a desirable, but as yet unidentified, gene. DNA sequences that are closely located are more likely to be inherited together.
The software has now been widely adopted within University of Adelaide plant research groups, where it has been used to help identify markers in wheat associated with abiotic stressors such as drought, salt, heat and frost. It has also played a key role at the University of Adelaide in accurately identifying genomic regions related to disease and drought resistance in chickpeas.
The timely identification and accurate quantification of important genomic regions relies heavily on the software used to construct the genetic map for the underlying crop genome. ASMap’s quality, efficiency and diagnostic capabilities have ensured it plays a pivotal role in the analysis pipeline used by plant research groups working on delivering high-quality marker information to breeders.
Building on the widespread use of ASMap, SAGI developers have formed strong collaborative links with multiple research groups and private breeding companies, ensuring the fast delivery of important genetic information so that breeders can efficiently select better crop varieties.
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LMA defect detection enhances new wheat varieties
Authors: Dr Beverley Gogel, Professor Brian Cullis and Dr David Butler
World-class statistical research and technology is at the core of an Australian testing protocol for late maturity alpha-amylase.
Late maturity alpha-amylase (LMA) is triggered in wheat grain under the right environmental conditions and can cause low falling number (FN). The FN test is an international standard test for LMA and for pre-harvest sprouting in wheat and other grains. Grain samples with a low FN test can be downgraded or rejected at receival, resulting in a much lower financial return to growers.
To reduce this risk, potential new wheat varieties are screened for their genetic potential to express LMA and only those with acceptably low levels of LMA proceed to commercial release.
Australian plant breeding companies rank LMA research as their highest priority and Professor Daryl Mares, from the University of Adelaide, is the world leader in this area. The testing protocol for LMA, developed by UA’s Dr Kolumbina Mrva and Professor Mares, is a complex process involving several linked stages.
High levels of alpha-amylase indicate that LMA has been expressed, although in such a complex process there are many factors contributing to data variation. In a single experiment, variation in results is caused by natural genetic variation along with environmental factors such as temperature during grain development.
In the early days of LMA testing there was a lack of statistical design in the process, resulting in a comparatively simple analysis of test results. But since 2008, Statistics for the Australian Grains Industry (SAGI) biometricians have partnered with the University of Adelaide, Wheat Quality Australia and the Wheat Advisory Board to introduce sophisticated multi-phase trial design and analysis, producing a classification tool which is accepted by the Australian wheat industry as a prerequisite for new variety release.
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