Bithell Sean L, McKay Alan, Butler Ruth C, Ophel-Keller Kathy, Hartley Diana, Cromey Matthew G
The New Zealand Institute for Plant & Food Research Limited, Private Bag 4704, Christchurch, New Zealand.
South Australian Research and Development Institute (SARDI), GPO Box 397, Adelaide, SA 5001, Australia.
Plant Dis. 2012 Mar;96(3):443-451. doi: 10.1094/PDIS-05-11-0445.
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.
土壤中禾顶囊壳小麦变种接种体的准确检测缺乏，阻碍了小麦种植者预测小麦全蚀病严重风险的努力。本研究采用分子方法对新西兰商业小麦田中土壤禾顶囊壳小麦变种的浓度进行量化，并将其与三个生长季节中超过可见和中度至重度全蚀病阈值的作物比例进行比较。该研究评估了澳大利亚开发的一种基于土壤禾顶囊壳小麦变种DNA的全蚀病预测系统，该系统有四个全蚀病风险类别。发现这些类别有助于预测第二季小麦的病害严重程度，但未明确区分中高风险类别田间的风险。在接种体浓度与超过两个病害阈值的田块比例之间确定了一种S形关系。使用逻辑响应曲线进一步研究这种关系，并评估全蚀病风险类别之间的界限。中高风险类别之间的禾顶囊壳小麦变种界限聚集在该关系的上平台附近或之内。确定了用于三类系统的替代禾顶囊壳小麦变种界限，这些界限能更好地区分不同类别之间的全蚀病风险。这些信息可改善对严重全蚀病风险的预测。
