Morpho-Molecular Identification and Race Detection of Xanthomonas campestris pv. campestris Causing Black Rot Disease of Cabbage in Bangladesh

Black rot disease, caused by the seed-borne bacterial pathogen Xanthomonas campestris pv. campestris (Xcc), reduces cabbage yield, featuring V-shaped chlorotic lesions along leaf margins. In December 2024, typical black rot symptoms were observed on cabbage plants in Churamonkathi Union, Jessore District, Bangladesh. Bacteria isolated from symptomatic leaf tissues on King’s medium B base agar were consistent with Xcc based on morphological and biochemical characteristics. Pathogenicity was confirmed by Koch’s postulates, with characteristic symptoms reproduced on healthy cabbage plants 7–14 days after inoculation (DAI). These pathogenic isolates were consolidated as Xcc by Xcc-specific primers (Xcc_53F/R). Subsequently, race determination using race-specific primers revealed that all pathogenic isolates belonged to race 1, as the primer pair Xcc_R2_89.2 F/R produced a 1523 bp amplicon. Partial 16S rRNA gene sequencing of one representative isolate and phylogenetic analysis confirmed its identity as Xcc. This study provides the morpho-molecular confirmation and race detection of Xcc race 1 causing black rot on cabbage in Bangladesh, where the pathogen was previously reported only from mustard seeds without detailed characterization. The findings will facilitate the development of effective disease management strategies for sustainable cabbage production in the country.

Authors

Institutions

Publication Details

Journal
Australasian Plant Pathology
Published
2026-07-16
DOI
https://doi.org/10.1007/s13313-026-01171-5
Primary Topic
Plant Pathogenic Bacteria Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Morpho-Molecular Identification and Race Detection of Xanthomonas campestris pv. campestris Causing Black Rot Disease of Cabbage in Bangladesh

Jong‐In Park, Mahmudul Hasan, Ujjal Kumar Nath, Pijush Kanti Jhan et al.
Australasian Plant Pathology
Plant Pathogenic Bacteria Studies
article

Morpho-Molecular Identification and Race Detection of Xanthomonas campestris pv. campestris Causing Black Rot Disease of Cabbage in Bangladesh

Jong‐In Park, Mahmudul Hasan, Ujjal Kumar Nath, Pijush Kanti Jhan, Tofazzal Islam, Mehede Hassan Rubel, Arnab Goswami, Nafisa Akter Sadia
article en

Abstract

Black rot disease, caused by the seed-borne bacterial pathogen Xanthomonas campestris pv. campestris (Xcc), reduces cabbage yield, featuring V-shaped chlorotic lesions along leaf margins. In December 2024, typical black rot symptoms were observed on cabbage plants in Churamonkathi Union, Jessore District, Bangladesh. Bacteria isolated from symptomatic leaf tissues on King’s medium B base agar were consistent with Xcc based on morphological and biochemical characteristics. Pathogenicity was confirmed by Koch’s postulates, with characteristic symptoms reproduced on healthy cabbage plants 7–14 days after inoculation (DAI). These pathogenic isolates were consolidated as Xcc by Xcc-specific primers (Xcc_53F/R). Subsequently, race determination using race-specific primers revealed that all pathogenic isolates belonged to race 1, as the primer pair Xcc_R2_89.2 F/R produced a 1523 bp amplicon. Partial 16S rRNA gene sequencing of one representative isolate and phylogenetic analysis confirmed its identity as Xcc. This study provides the morpho-molecular confirmation and race detection of Xcc race 1 causing black rot on cabbage in Bangladesh, where the pathogen was previously reported only from mustard seeds without detailed characterization. The findings will facilitate the development of effective disease management strategies for sustainable cabbage production in the country.

Australasian Plant PathologyVol. 55(4)
Sunchon National University (KR), Bangladesh Agricultural University (BD), Noakhali Science and Technology University (BD), Bangladesh Agricultural Research Institute (BD)
Openalex Percentile: Top 10%
Plant Pathogenic Bacteria Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.