Xanthomonas euvesicatoria has become a serious problem in Physalis pubescens, leading to substantial crop losses. In our previous investigation, we used rapid molecular detection techniques to identify X. euvesicatoria
however, this pathogen's diversity and population structure remain poorly understood, despite their importance in disease management. To address this knowledge gap, we analyzed the diversity of X. euvesicatoria using BOX-PCR and ERIC-PCR fingerprinting techniques. A total of 103 isolates were collected from 13 counties across Heilongjiang province during the 2018 and 2019 growing seasons. Our findings revealed 635 unique genetic patterns from ERIC-PCR fingerprinting, compared to 360 patterns from BOX-PCR. BOX-PCR analysis identified 12 distinct genotypic clusters, whereas ERIC-PCR identified 14 clusters through unweighted pair group approach with arithmetic average analysis, demonstrating substantial genetic variability. STRUCTURE analysis further identified five distinct genetic clusters in the BOX-PCR data and two in the ERIC-PCR data. The Hailin isolates showed the highest level of diversification compared to other regional isolates. AMOVA results indicated that 85% of the genetic variation in BOX-PCR was attributable to within-population differences, while 78% of ERIC-PCR variation was due to differences across populations. In addition, a Mantel test demonstrated a tenuous correlation between BOX-PCR and ERIC-PCR genetic markers, indicating distinct genetic profiles. This extensive genetic information enhances our understanding of the epidemiology of bacterial leaf spot and its potential therapeutic prospects. These data can provide insights into Xanthomonas strains' diversity and geographical dissemination.