The USDA-APHIS Plant Germplasm Quarantine Program (PGQP) uses conventional testing (i.e. molecular, serological, biological indexing) and contemporary high-throughput sequencing (HTS)-based methods for the identification of viruses and virus-like pathogens in imported plant germplasm. Implementing HTS-based technologies, such as total RNA metagenomic sequencing, for pathogen diagnosis enables rapid detection and identification of quarantine pathogens. To test the efficacy of these diagnostic methods, we compared the diagnostic capabilities of conventional testing versus HTS data analysis pipelines using Poaceae quarantine germplasm. The HTS-based bioinformatics analyses included two approaches: 1) read assembly and subsequent BLAST-based pathogen detection pipeline; and 2) read mapping-based pathogen detection pipeline. By comparing the results for 142 quarantine Poaceae accessions, we demonstrated that HTS-based methods were capable of detecting all expected viruses in addition to novel viruses undetected by conventional testing. Comparable results were obtained for the detection of 20 of the 24 viral pathogens when tested with conventional testing and the BLAST-based HTS approach. The remaining four viruses were only identified by HTS. The read mapping-based HTS pipeline outperformed the BLAST-based HTS pipeline in detecting novel viruses and quantifying viral titer. These results demonstrate the effectiveness of HTS data analysis pipelines as a robust method for detecting plant viruses that can enhance our ability to diagnose viral pathogens of quarantine significance.