Genetic diversity of diazotrophs and total bacteria in the phyllosphere of <i>Pyrus serotina</i>, <i>Prunus armeniaca</i>, <i>Prunus avium</i>, and <i>Vitis vinifera</i>
Bibliographic record
Abstract
The phyllosphere, which supports a large number of microorganisms, represents the interface between the aboveground parts of plants and air. In this study, four nifH clone libraries were constructed from the phyllosphere of Pyrus serotina (L), Vitis vinifera (P), Prunus armeniaca (X), and Prunus avium (Y). Clones related to Skermanella (L, 12.1%; X, 15.6%; Y, 62.5%; P 70.8%), Bradyrhizobium (X, 2.1%; P, 15.1%; L, 63.7%), Erwinia (X, 68.8%), Pseudomonas (L, 3.3%; P, 7.6%), and Chroococcidiopsis (P, 0.9%; L, 4.4%, X; 5.2%, Y; 19.6%) were present at high percentages, highlighting their critical role in contributing nitrogen to the phyllosphere ecosystem. The 16S rDNA sequence analysis suggested that phyllosphere-associated bacteria were affiliated with a wide range of taxa, encompassing members from Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Cyanobacteria, Tenericutes, and Deinococcus–Thermus. Additionally, the abundance of the nifH gene and 16S rDNA was assessed with quantitative PCR. The number of copies of nifH and 16S rDNA ranged from 1.14 × 103 to 1.49 × 104 and from 3.72 × 106 to 7.02 × 107 copies/g fresh leaf sample, respectively. In conclusion, our work sheds light on the microbial communities of the phyllosphere that are important for plant growth. Moreover, we observed a unique composition of nitrogen-fixing bacteria in each phyllosphere sample, suggesting the existence of specific interactions between these functional microorganism and plants, which may provide information or be a reference for the development of bacterial fertilizers.
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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".