Characterization and pathogenicity of <i>Colletotrichum camelliae</i> causing brown blight disease of tea ( <i>Camellia sinensis</i> ) in Malaysia
Bibliographic record
Abstract
Tea (Camellia sinensis (L.) Kuntze) is a dicotyledonous woody shrub species widely cultivated to produce a beverage made from its leaves. Brown blight is a destructive foliar fungal disease that reduces tea production and degrades quality, resulting in lower market value. Typical brown blight symptoms observed in three commercial tea plantations in Malaysia were characterized as brownish to black lesions on young leaves. The lesions expanded with age, becoming darker and developing into necrotic cells. A total of 45 fungal isolates were isolated from brown blighted tea leaves and identified as Colletotrichum camelliae. Morphological characteristics coupled with universal spacer region and multigene phylogenetic relationships using the internal transcribed spacer (ITS), β-tubulin (tub2) and glyceraldehyde-3-phosphate dehydrogenase (gapdh) were used to accurately identify fungal isolates. The results of the pathogenicity test revealed that C. camelliae was responsible for causing brown blight disease of tea. This study highlights the occurrence of C. camelliae which causes tea brown blight in Malaysia. These findings may assist in disease monitoring, strict quarantine and effective control management of diseased tea plants.
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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) | 0.000 | 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 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".