Endophytic microbial diversity in coffee cherries of<i>Coffea arabica</i>from southeastern Brazil
Bibliographic record
Abstract
The microbiota associated with coffee plants may play a critical role in the final expression of coffee quality. However, the microbial diversity in coffee cherries is still poorly characterized. Here, we investigated the endophytic diversity in cherries of Coffea arabica by using culture-independent approaches to identify the associated microbes, ultimately to better understand their ecology and potential role in determining coffee quality. Group-specific 16S rRNA and 26S rRNA genes polymerase chain reaction - denaturing gradient gel electrophoresis and clone library sequencing showed that the endophytic community is composed of members of the 3 domains of life. Bacterial sequences showing high similarity with cultured and uncultured bacteria belonged to the Betaproteobacteria, Gammaproteobacteria, and Firmicutes phyla. Phylogenetic analyses of cloned sequences from Firmicutes revealed that most sequences fell into 3 major genera: Bacillus, Staphylococcus, and Paenibacillus. Archaeal sequences revealed the presence of operational taxonomic units belonging to Euryarchaeota and Crenarchaeota phyla. Sequences from endophytic yeast were not recovered, but various distinct sequences showing high identity with filamentous fungi were found. There was no obvious correlation between the microbial composition and cultivar or geographic location of the coffee plant. To the best of our knowledge, this is the first report demonstrating internal tissue colonization of plant fruits by members of the Archaea domain. The finding of archaeal small-subunit rRNA in coffee cherries, although not sufficient to indicate their role as active endophytes, certainly expands our perspectives toward considering members of this domain as potential endophytic microbes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".