Identification and Characterization of Pestalotioid Fungi Causing Leaf Spots on Mango in Southern China
Bibliographic record
Abstract
Mango is an economically important fruit crop in southern China. However, leaf spots restrict the development of mango trees, reducing the yield and production. Pestalotioid fungi are one of the major agents causing leaf spots on mango. During 2016 and 2017, 21 isolates of pestalotioid fungi associated with leaf spots on mango leaves were collected from five provinces in southern China: Guangxi, Hainan, Yunnan, Guangdong, and Fujian. All 21 isolates were subjected to morphological characterization and DNA sequence analysis. The morphological data were combined with analyses of concatenated sequences of the ITS (internal transcribed spacer), TEF 1-α (translation elongation factor), and TUB2 (β-tubulin) for higher resolution of the species identity of these isolates. The results showed that these isolates belong to Neopestalotiopsis clavispora, Pestalotiopsis adusta, P. anacardiacearum, P. asiatica, P. photinicola, P. saprophyta, P. trachicarpicola, and Pseudopestalotiopsis ampullacea. Pathogenicity test results showed that all these species could cause symptoms. On detached mango leaves (cv. Tainong), early foliar symptoms on leaves were small yellow-to-brown lesions. Later, these spots expanded with uneven borders, turned white to gray, and coalesced to form larger gray patches. To our knowledge, this is the first description of N. clavispora, P. adusta, P. asiatica, P. photinicola, P. saprophyta, P. trachicarpicola, or Ps. ampullacea as causal agents for leaf spots on mango worldwide.
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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".