Identification of <i>Lasiodiplodia pseudotheobromae</i> causing mango dieback in Korea
Bibliographic record
Abstract
Mango (Mangifera indica) is an economically important fruit grown in tropical regions. Mango cultivation has increased in Korea as the fruit has become more popular; however, the majority of the fruit is imported. Mango dieback was observed for the first time in July 2016, in Tongyeong, South Korea. The aim of the present study was to identify the causal pathogen. Identification of the fungus was based on morphological and cultural characteristics, and sequencing of the internal transcribed spacer rRNA region and gene encoding translation elongation factor 1-alpha. A phylogenetic analysis of the sequences confirmed that the fungus isolated from diseased mango plants was Lasiodiplodia pseudotheobromae. Koch’s postulates were completed by pathogenicity tests conducted on healthy leaves, fruit and whole plants. Based on the morphological characteristics, pathogenicity tests, and molecular identification, the causal fungus was identified as L. pseudotheobromae. This is the first report of mango dieback caused by L. pseudotheobromae in Korea. The recent occurrence of the disease indicates that the fungus poses a potential threat to mango production in Korea.
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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 | 0.001 | 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".