Identification of fungi causing pre-harvest anthracnose and anthracnose-like symptoms on mango fruits ( <i>Mangifera indica</i> )
Bibliographic record
Abstract
During field surveys in Uttar Pradesh, India between 2020–2022, we consistently encountered pre-harvest anthracnose and anthracnose-like symptoms on green mangoes, with incidence levels ranging from 20% to 40%, particularly during periods of heavy rainfall. This study aimed to identify the fungal pathogens associated with these symptoms using a polyphasic approach. Pathogenicity was confirmed on detached fruits of mango cv. Dashehari, with isolated pathogens including Colletotrichum asianum, C. siamense, Botryosphaeria dothidea, Diaporthe phoenicicola, Alternaria burnsii, Lasiodiplodia hormozganensis, and Parasympodiella eucalyptii. Colletotrichum asianum and C. siamense were identified as predominant through phylogenetic analysis of multiple genes (internal transcribed spacer [ITS], actin [ACT], chitin synthase [CHS-1], glyceraldehyde-3-phosphate dehydrogenase [GAPDH], and Mat1–2 gene region [APMAT] genomic regions). Lasiodiplodia hormozganensis and A. burnsii were identified through phylogenetic analysis based on ITS and translation elongation factor-1alpha (TEF) genes. Diaporthe phoenicicola was identified using ITS, TEF, and β-tubulin (TUB2)-based phylogenetic analysis. To the best of our knowledge, association of D. phoenicicola and A. burnsii with mango fruit spots is being reported for the first time in this study. Lasiodiplodia hormozganensis was the most aggressive pathogen, followed by C. siamense, C. asianum, B. dothidea, A. burnsii, D. phoenicicola, and P. eucalypti. Although the pathogenic behaviour of P. eucalyptii has been demonstrated on detached leaves and fruits, its role remains questionable due to its rare isolation. This study underscores the involvement of multiple Colletotrichum species and other fungal pathogens in mango anthracnose and highlights the need for further research into the diversity and geographical distribution of Colletotrichum species causing mango anthracnose in India.
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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".