Abstract

Stripe rust is one of the main diseases of wheat, which seriously threatens wheat production and food security all over the world. Xiangyang located in the Northwest of Hubei province in China is one of the main winter propagation and spring epidemic regions of Puccinia striiformis f. sp. tritici (Pst), which can provide urediniospores to the major wheat-growing regions in eastern and northeastern China. Understanding the dynamic of Pst urediniospore is important for giving prediction of wheat stripe rust epidemic for eastern and northeastern China and controlling the epidemic of wheat stripe rust. In this study, spore trapper and TaqMan real-time quantitative PCR (TaqMan-qPCR) detection system were employed to monitor Pst urediniospore from December 2018 to December 2022 in Xiangyang. Weather variables including air temperature, relative humidity, sunshine duration and rainfall were collected to clarify the relationship with urediniospore density in the air. In addition, the relationship between disease index of wheat stripe rust and urediniospore density in the air was analyzed. Results showed that Pst urediniospore could be captured in the air all year round. The order of the density of urediniospore from most to least was from April to June, October to December, January to March, and July to September except 2022. The urediniospore density reached the peak when the air temperature was 10–22 °C and the relative humidity was 70%∼85% from April to May in 2019, 2020 and 2021. The density of Pst urediniospores from February to April was linearly related to the total precipitation of 25 days prior to the final day of a 7-day trapping period. There was a significant positive correlation between the disease index of wheat stripe rust and the cumulative urediniospore density 2–4 weeks before the investigation date of wheat stripe rust from March to May (P < 0.05). There was no significant correlation between the disease index and the cumulative urediniospore density from 1–4 weeks after the investigation date of stripe rust from March to May (P > 0.05). This study laid a foundation for the establishment of wheat stripe rust prediction model based on urediniospore density and meteorological factors.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.