The blueberry industry, a fast-growing industry in Florida, is threatened by bacterial wilt, caused by the Ralstonia solanacearum species complex (RSSC). In 2016, distinct RSSC populations were found in Florida causing disease in blueberry. Currently, there are no tools that discriminate between RSSC populations pathogenic to blueberry and other RSSC strains. Early detection of specific RSSC strains is critical, and the Microbe Finder (MiFi) web application is a sensitive and specific tool used to detect known target pathogens in sequenced samples. MiFi is used to develop e-probes and subsequently query sample metagenomes with them. We report the development and validation of e-probes for three different RSSC populations pathogenic to blueberry using the MiFi platform. We also present preliminary data to assess the feasibility of a cost-effective integrated diagnostics system, MiFi, in combination with MinION, a pocket-sized, portable sequencer. The e-probes were validated in silico, generating simulated metagenomes; in vitro by using blueberry DNA spiked with pathogen DNA; and in vivo with soil and stem samples. We tested several methods of DNA extraction for soil and blueberry stems and several MinION libraries with or without barcodes. MiFi blueberry e-probes effectively identified target pathogens at a very specific level with high sensitivity. The MiFi system combined with MinION sequencing using Flongle cells was optimized to produce results in one day. Further optimization and tests can improve greatly the cost effectiveness and flexibility of this system by adding e-probes to test for new blueberry strains and many other pathogens affecting blueberry in one test. Copyright ? 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.