Australia
January 10, 2008
With pathogens capable of
downgrading quality and slashing yields, disease resistant crop
varieties head the ‘Most Wanted’ list for most graingrowers.
While breeding for disease resistance is the most
environmentally favourable solution, most sources of resistance
to most pathogens are only partial.
The question is: “How do plant pathologists and breeders
accurately and reproducibly measure resistance in different
cultivars?”
 According
to Grains Research and
Development Corporation (GRDC) Western Panel member,
Professor Richard Oliver (photo), Director of the GRDC supported
Australian Centre for Nectrotrophic Fungal Pathogens at Murdoch
University, traditional visual and microscopic disease
assessments are time consuming, require rare, specialised skills
and the results can be subjective.
He has therefore tested a protocol to identify robust, resistant
crop cultivars based on a quantitative polymerase chain reaction
(qPCR) that measures pathogen biomass by duplicating sequences
in the pathogen’s DNA.
The pathogen used was the fungus Staganosporum nodorum, a major
disease-causing agent of wheat in WA. It causes S. nodorum
blotch and Glume blotch of wheat and related cereals and has a
simple, short lifecycle, making it a model pathogen to study
direct connections between biomass, symptoms and yield.
Professor Oliver compared four disease assessment methods to
determine levels of correlation between them. His baseline was
the reduction in the weight of 100 grains of wheat after
inoculation with the pathogen in a range of wheat cultivars.
Seven wheat lines, previously assessed on a nine point
resistance score, were used.
He concluded that qPCR was a versatile tool for disease risk
assessment.
“The protocol compared favourably with other visual and
microscopic techniques and although the relative expense of qPCR
was not evaluated, I believe that with automation the cost would
be very competitive,” he said.
Data from disease risk assessment using the qPCR protocol would
have several uses, including objective pre-harvest measurement
of disease and assessing disease development to optimise
fungicide application.
“Most fungicides work best if applied early in the infection
cycle before symptoms can be observed. We expect qPCR to give
growers vital early warning of diseases,” he said.
Further, the protocol could be used to predict the potential for
yield loss from diseases which could not be visually identified
until plant maturity. A major strength of qPCR was its
specificity, which allowed numerous diseases to be assayed
simultaneously, something that is very hard to do by traditional
methods. |
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