No abstract

Stripe rust, caused byPuccinia striiformisf. sp.tritici(Pst), is one of the important wheat diseases worldwide. In this study, the spectral data were collected from wheat canopy during the latent period inoculated with three different concentrations of urediniospores and classification models based on discriminant partial least squares (DPLS) were built to differentiate leaves with and without infection of the stripe rust pathogen. The effects of different spectra features, wavebands, and the number of the samples used in modeling on the performances of the models were assessed. The results showed that, in the spectral region of 325–1075 nm, the model with the spectral feature of 2nd derivative of Pseudoabsorption index had better accuracy than others. The average accuracy rate was 97.28% for the training set and 92.98% for the testing set. In the waveband of 925–1075 nm, the model with the spectral feature of 1st derivative Pseudoabsorption index had better accuracy than other models, and the average accuracy rates were 98.27% and 94.33% for the training and testing sets, respectively. The results demonstrated that wheat stripe rust in latent period can be qualitatively identified based on the canopy spectral detection. Thus, the method can be used for early monitoring of infections of wheat stripe rust.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is the most devastating wheat disease in China. Early and accurate detection of the pathogens would facilitate effective control of the diseases. DNA‐based methods now provide essential tools for accurate plant disease diagnosis. In this study, inter‐simple sequence repeats (ISSR) technique has been successfully applied to develop a sequence‐characterized amplified region (SCAR) marker for diagnosis of stripe rust of wheat and detection of Pst. In this study, one fragment unique to Pst was identified by ISSR and then sequenced. Based on the specific fragment, a pair of SCAR primers (616AF/616AR) was designed to amplify a 299‐bp DNA fragment within the sequenced region. The primers can amplify a unique DNA fragment for all tested isolates of Pst but not for the other pathogens of wheat leaves and the uninfected leaves. The polymerase chain reaction (PCR) assay could detect as low as 0.1 ng of genomic DNA in a 25.0 μl PCR reaction mixture and detect the pathogen from asymptomatic wheat leaves inoculated with Pst under glasshouse conditions.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most important fungal diseases affecting wheat (Triticum aestivum L.) worldwide. In this study, the genetic diversity and population structure of Pst isolates were analyzed using 15 microsatellite markers. Isolates were collected from five wheat cultivars with different levels of resistance from Yanting county and Fucheng district, Mianyang city, Sichuan province, China. The aim of this study was to investigate whether Pst populations are differentiated by wheat genotype or geographic origin. Seventy-six multilocus genotypes (MLGs) were identified from all 289 single uredinial isolates. In general, the genotypic diversity of Pst populations from five wheat cultivars in Fucheng was higher than that in Yanting. In addition, the genetic diversity was highest in the Pst populations from Mianmai 367, a cultivar considered to be highly resistant. The unweighted pair group method with arithmetic mean (UPGMA) phylogenetic tree, Bayesian clustering analysis, and minimum spanning network for the MLGs revealed two major genetic clusters based on geographical location. Greater differentiation was observed between the populations from the two sampling locations than between the populations from different hosts in the same location. The results suggest that geographic and environmental differences could partially explain the genetic differentiation of Pst more than wheat genotype. This study provides novel insight into the interactions between Pst populations and their hosts. The results could be helpful in designing more effective management strategies for stripe rust in wheat production.