March
2012
, Volume
96
, Number
3
Pages
443
-
451
Authors
Sean L. Bithell, The New Zealand Institute for Plant & Food Research Limited, Private Bag 4704, Christchurch, New Zealand;
Alan McKay, South Australian Research and Development Institute (SARDI), GPO Box 397, Adelaide, SA 5001, Australia;
Ruth C. Butler, The New Zealand Institute for Plant & Food Research Limited, Christchurch;
Herdina and
Kathy Ophel-Keller, SARDI, Adelaide;
Diana Hartley, CSIRO Ecosystem Sciences, Black Mountain, ACT 2601, Australia; and
Matthew G. Cromey, The New Zealand Institute for Plant & Food Research Limited, Christchurch
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Accepted for publication 25 October 2011.
Abstract
Abstract
The lack of accurate detection of Gaeumannomyces graminis var. tritici inoculum in soil has hampered efforts to predict the risk of severe take-all for wheat growers. The current study used a molecular method to quantify soil G. graminis var. tritici concentrations in commercial wheat fields in New Zealand and to compare them with the proportion of crops surpassing the thresholds for visible and moderate to severe take-all over three growing seasons. The study evaluated a soil G. graminis var. tritici DNA-based take-all prediction system developed in Australia, with four take-all risk categories. These categories were found to be useful for predicting disease severity in second wheat but did not clearly separate risk between fields in medium- and high-risk categories. A sigmoidal relationship was identified between inoculum concentration and the proportion of fields exceeding the two disease thresholds. A logistic response curve was used to further examine this relationship and evaluate the boundaries between take-all risk categories. G. graminis var. tritici boundaries between medium- and high-risk categories were clustered near or within the upper plateau of the relationship. Alternative G. graminis var. tritici boundaries for a three-category system were identified that provided better separation of take-all risk between categories. This information could improve prediction of the risk of severe take-all.
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© 2012 The American Phytopathological Society