Isolation, Characterization and Selection of Bacteria that Promote Plant Growth in Grapevines (Vitis sp.)
Bibliographic record
Abstract
Certain bacteria can promote and stimulate plant growth, increasing the production of biomass and reducing damage caused by phytopathogens. With that in mind, this research effort set out to select these plant growth-promoting bacteria in order to evaluate their effects on the growth of grapevines (Vitis sp.). The bacteria were isolated from several vineyard soil samples, and evaluated based on their production of IAA (Indole-3-Acetic Acid), siderophores and cellulase, as well as their phosphate solubilization and nitrogen fixation capabilities. In vivo testing included six separate treatments with the following bacterial isolates: C12, O7, B3, I3, a control group and a blended group. The tests were performed in a greenhouse with bacterial suspension inoculation placed around the roots of Paulsen 1103 rootstock cuttings. The data collected included the following: number of leaves per plant, branch lengths, chlorophyll content, fresh and dry mass, and Carbon, Hydrogen, Nitrogen and Sulfur concentrations. Forty-six separate bacteria were isolated, of which 100% produced IAA, 65.21% produced siderophores, 63.04% solubilized phosphate, 34.78% produced cellulase, and 30.43% showed nitrogen fixation. The in vivo testing also revealed significant increases in the length of the branch and in percentages of Carbon and Nitrogen. The C12 isolate exhibited the highest increase in branch length (76.704 cm), whereas the O7 and C12 were identified as Bacillus amyloliquefaciens and Bacillus thuringiensis, respectively.
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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 | 0.000 | 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".