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Record W4415490820 · doi:10.3390/jof11110762

Mating and Pathogenicity of the Dominant Colletotrichum Species Associated with Anthracnose Disease of Mango

2025· article· en· W4415490820 on OpenAlexaff
Rui Wang, Juan Shu, Suiping Huang, Lihua Tang, Tangxun Guo, Xiaolin Chen, Tom Hsiang, Qili Li

Bibliographic record

VenueJournal of Fungi · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of Guelph
FundersGuangxi Academy of Agricultural SciencesNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of China
KeywordsIntraspecific competitionMatingPathogenicityVirulenceMating typeMating systemSexual reproductionMating design

Abstract

fetched live from OpenAlex

Anthracnose is one of the main diseases of mango, which seriously affects the yield and quality. Previous studies found that mango anthracnose in China involves at least 13 species of Colletotrichum. From mango with anthracnose symptoms samples, we previously obtained 134 strains from 13 species, and 26.0% were C. fructicola, while 27.6% were C. siamense, and 31.3% were C. asianum, with a few specimens for each of the remaining species. These three main species were used in intraspecific mating tests to assess sexual reproduction. The intraspecific mating tests revealed that C. fructicola and C. siamense readily produced ascospores, while C. asianum did not. From the 595 intraspecific crosses with 35 isolates of C. fructicola, 34 crosses were considered fertile. Among these, thirty single-ascospore isolates were chosen for pathogenicity testing and genetic variation analysis (ITS and ApMat loci). The results revealed that some progeny showed higher aggressiveness than their parents, while some progeny showed lower aggressiveness. Future tests are needed to assess the genetic basis of these aggressiveness differences. The results provide a scientific basis for further research on sexual reproduction and pathogenicity of Colletotrichum, which may allow for comprehensive disease prevention and control.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.209
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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