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Detection and quantification of airborne spores from six important wheat fungal pathogens in southern Alberta
Canadian Journal of Plant Pathology ( IF 2 ) Pub Date : 2020-11-27 , DOI: 10.1080/07060661.2020.1817795
Gabriela T. Araujo 1, 2 , Eric Amundsen 1 , Michele Frick 1 , Denis A. Gaudet 1 , Reem Aboukhaddour 1 , Brent Selinger 2 , James Thomas 2 , André Laroche 1
Affiliation  

Abstract

Wheat is affected by many fungal diseases that can cause severe yield and quality losses. Disease prediction models generally employ weather data to estimate potential for infection to determine timing for fungicide applications, but these models fail to account for the presence and quantity of pathogen inoculum. This study adapted highly specific qPCR primers to identify and quantify, in real-time, inoculum present in air for the six most important wheat pathogens in Canada. Fungal spores were collected using either Burkard spore collectors and quantified using qPCR or microscope slides covered with adhesive tape and identified and quantified using microscopy. Samples were collected from seven different sites in southern Alberta throughout the 2015–2017 growing seasons. The results demonstrated that qPCR can reliably identify and quantify spores from Puccinia striiformis f. sp. tritici, P. triticina, P. graminis f. sp. tritici, Blumeria graminis f. sp. tritici, Pyrenophora tritici-repentis, and Fusarium graminearum. The limits of detection of DNA for primer pairs in singleplex tests ranged from 0.0001 ng for P. graminis to 0.001 ng for P. tritici-repentis, which corresponded to approximately 3 spores for P. tritici-repentis and F. graminearum and 1 spore for the other pathogens. Conversely, microscopy permitted identification of rusts to the genus but not to the species level and was ineffective in quantification of the remainder of the wheat pathogens. This study will contribute to the development of a fast and reliable forecasting system that will enable identification and quantification of airborne pathogens in real-time before initial disease symptoms appear.



中文翻译:

艾伯塔省南部六种重要小麦真菌病原体的空气传播孢子的检测和定量

摘要

小麦受到许多真菌病害的影响,这些病害可导致严重的产量和质量损失。疾病预测模型通常使用天气数据来估计感染的可能性,以确定杀真菌剂应用的时间,但这些模型未能考虑病原体接种物的存在和数量。本研究采用高度特异性的 qPCR 引物来实时识别和量化加拿大六种最重要的小麦病原体的空气中存在的接种物。使用 Burkard 孢子收集器收集真菌孢子,并使用 qPCR 或用胶带覆盖的显微镜载玻片进行量化,并使用显微镜进行识别和量化。在整个 2015-2017 生长季节从艾伯塔省南部的七个不同地点收集样品。Puccinia striiformis f. sp. 小麦, P. triticina, P. graminis f. sp. 小麦, Blumeria graminis f. sp. 小麦、Pyrenophora tritici-repentis镰刀菌。单重测试中引物对 DNA 的检测限范围从禾本科小麦的0.0001 ng 到禾本科小麦的0.001 ng ,这对应于禾本科小麦禾本科小麦的大约 3 个孢子和 1 个孢子用于其他病原体。相反,显微镜可以将锈病鉴定到属但不能鉴定到种水平,并且在量化其余小麦病原体方面无效。这项研究将有助于开发一个快速可靠的预测系统,该系统将能够在初始疾病症状出现之前实时识别和量化空气传播的病原体。

更新日期:2020-11-27
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