LMA defect detection enhances new wheat varieties

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Key points

  • Wheat with a low falling number can be rejected at delivery
  • Late maturity alpha-amylase (LMA) is one of the causes of low falling number
  • An accurate test for LMA is in use, thanks to a partnership between researchers and biometricians
Photo of Dr Kolumbina Mrva

Dr Kolumbina Mrva conducts much of her LMA screening work in the glasshouse.

PHOTO: Daryl Mares

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 (UA), 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.

Plants are grown in the glasshouse, tillers are then transferred to a water bath under cool temperature conditions with alternating 12-hour periods of light and darkness for 7 to 10 days. The tillers are then returned to the warm glasshouse to ripen. Finally, composite grain samples are assayed to determine how much alpha-amylase has been produced (high alpha-amylase gives low falling number).

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 UA, 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.

The SAGI trial design is sophisticated enough to handle the complex biology involved while minimising both the cost and resources required.

Trial designs provide for both genetic and non-genetic sources of variation in the two main phases of the testing process (glasshouse and assay phases), and the statistical analysis uses advanced methods to model data that span the LMA experiments conducted by UA annually (one each in winter and summer) across multiple years (four in the most recent analysis).

Varieties with alpha-amylase levels greater than the benchmark variety Wyalkatchem, an intermediate LMA expressor, are classified as expressors.

Future research is working to improve the protocol, and field testing will lead to a better understanding of LMA expression for varieties within a grey zone around the current classification limit.

Footnote Since 2008, members of the Statistics for the Australian Grains Industry project, Professor Brian Cullis, Dr David Butler and Dr Beverley Gogel have worked in close partnership with Professor Daryl Mares and

Dr Kolumbina Mrva.

More information:

Dr Beverley Gogel,
University of Adelaide,
08 8313 0240,



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