Dynamics of Puccinia striiformis f. sp. tritici Urediniospores in Longnan, a Critical Oversummering Region of China

Author:

Hu Xuemin1,Fu Songping2,Li Yuxiang1,Xu Xiangming3,Hu Xiaoping1ORCID

Affiliation:

1. State Key Laboratory of Crop Stress Biology for Arid Areas and College of Plant Protection, Northwest A&F University, Yangling 712100, China

2. Tianshui Station of Plant Protection and Quarantine, Tianshui, Gansu 741020, China

3. Pest & Pathogen Ecology, NIAB, West Malling, Kent ME19 6BJ, U.K.

Abstract

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici Erikss. (Pst), is a devastating disease resulting in yield reduction. Because the temperature limits the overwintering and oversummering of Pst, it cannot complete the whole year cycle in most areas of China. Longnan, located in the southeast of Gansu Province, is one of the annual cycle areas of Pst, which can supply urediniospores in autumn to eastern wheat-growing areas in China. In this study, a TaqMan real-time quantitative PCR (TaqMan-qPCR) detection system for Pst urediniospores was established, and the detection limit was a single urediniospore. The dynamics of Pst urediniospores in Longnan were monitored by spore trapping and TaqMan-qPCR for 3 years. Meanwhile, the meteorological conditions including air temperature, relative humidity, and precipitation were recorded. Results showed that Pst urediniospores can be captured from March to December, and two peaks of urediniospore density appeared in May and June, respectively. The density of urediniospore is closely related to temperature and precipitation from March to June. In addition, we found that the density of Pst urediniospore had the peak value when the average air temperature was 10 to 21°C, and the relative humidity was 60 to 85% from May to June. The exponential model could describe the variation of Pst urediniospore density based on average temperature and precipitation from March to June. It is worth mentioning that the exponential model based on average temperature 7 days before spore capture has a great advantage in predicting the urediniospore density in the air. This study laid a foundation for establishment of a prediction model for wheat stripe rust based on the density of urediniospores and meteorological factors.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Extension Project of Northwest A&F University

Major Science and Technology Project of Agricultural Collaborative Innovation and Promotion Association in Shaanxi Province

Publisher

Scientific Societies

Subject

Plant Science,Agronomy and Crop Science

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