Clonal Expansion in Multiple Phyllosticta Species Causing Citrus Black Spot or Similar Symptoms in China
Bibliographic record
Abstract
Phyllosticta spp. are important pathogens of citrus plants. Several Phyllosticta species associated with Citrus species grown in China have been reported; however, the relative prevalences of individual species and the distributions of their genotypes among host Citrus species remain largely unknown. In this study, we conducted an extensive survey of Phyllosticta species across 11 citrus-producing provinces in southern China. From fruits and leaves with black spots or black-spot-like symptoms, a total of 461 Phyllosticta strains were isolated. Based on molecular (ITS, actA, tef1, gapdh, LSU, and rpb2 sequences) and morphological data, the strains were systematically identified as belonging to five species: P. capitalensis, P. citrichinaensis, P. citriasiana, P. citricarpa, and P. paracitricarpa. To further understand intraspecific genetic diversity and relationships, strains of five species from different geographic and host sources were analyzed based on the multilocus sequence data. Our population genetic analyses revealed that all five Phyllosticta species on citrus showed evidence for clonal dispersals within and among geographic regions. In addition, pathogenicity tests using representative strains showed that all five species can cause disease on the tested Citrus spp. We discuss the implications of our results for the control and management of Citrus Black Spot and related diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".