First report of <i>Pantoea ananatis</i> causing leaf blight disease of pomegranate in India
Bibliographic record
Abstract
Pomegranate (Punica granatum) is an economically important fruit crop and India ranks first for its cultivation globally (Chathalingath & Gunasekar, 2023). During December 2022, pomegranate in Tamil Nadu, India was found with leaf abnormalities. Diseased leaves showed brown necrotic spots surrounded by yellowish margins and the edges of the leaves were wrinkled (Figure 1). Diseased leaves were collected and surface sterilised with 0.2% sodium hypochlorite, and then the lesion-bearing areas were cut and ground with sterile water. The suspension was spread onto nutrient glucose agar and incubated at 28±2°C for five days (Doddaraju et al., 2019). All the colonies on the medium showed similar morphological features and a single colony was selected and assigned the name PBL5. The isolate was Gram-negative and yellow-pigmented, circular with a glistening morphology, positive for starch hydrolysis, catalase, oxidase and methyl red but negative for citrate utilisation, Voges-Proskauer and casein hydrolysis. The isolate was incapable of producing indole and urease. The pathogenicity of the isolate was tested by the foliar spray method on seedlings. Pathogenicity was confirmed after observation of symptoms, resembling those seen in the field, within a week of inoculation (Figure 2). The pathogen was successfully isolated from the inoculated leaves and identified by PCR amplification with universal 16S rRNA primers (27F and 1492R) followed by Sanger sequencing (Chathalingath et al., 2023). An amplicon of 1400 bp was sequenced (GenBank Accession no. OP269843.1) and BLAST analysis of this sequence showed 99.91% of identity with the 16S ribosomal RNA gene of P. ananatis strain OSD3 (MK818494.1). A phylogenetic study revealed that PBL5 had affinity with Flavobacterium acidificum, Pantoea sp., an unnamed species of Enterobacteriaceae and Erwinia uredovora (Figure 3). Pantoea ananatis has already been identified in many food crops. For instance, leaf blights caused by P. ananatis have been reported in rice in India (Mondal et al., 2011) and in strawberries in Canada (Bajpai et al., 2020). Liao et al. (2016) also found a P. ananatis-induced soft rot bacterial disease in peach fruit in China. To the best of our knowledge, this is the first evidence of P. ananatis as the cause of bacterial blight of pomegranate in India and worldwide. Since P. ananatis causes a range of diseases in economically important food crops, a detailed study is required to understand the mode of transmission since this is still unknown. The authors would like to thank the PG and Research Department of Biotechnology, Kongunadu Arts and Science College (KASC) and Department of Biotechnology, PSGR Krishnammal College for Women (PSGRKCW) for supporting all the laboratory facilities. We thank the DBT and DST-FIST for providing laboratory facilities to the Biotechnology Department, KASC and PSGRKCW.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".