Alternative rooting induction of semi-hardwood olive cuttings by several auxin-producing bacteria for organic agriculture systems
Bibliographic record
Abstract
Southern Spain is the largest olive oil producer region in the world. In recent years organic agriculture systems have grown exponentially so that new alternative systems to produce organic olive cuttings are needed. Several bacterial isolates, namely Pantoea sp. AG9, Chryseobacterium sp. AG13, Chryseobacterium sp. CT348, Pseudomonas sp. CT364 and Azospirillum brasilense Cd (ATCC 29729), have been used to induce rooting in olive semi-hardwood cuttings of Arbequina, Hojiblanca and Picual cultivars of olive (Olea europea L). The first four strains were previously selected as auxin-producing bacteria and by their ability to promote rooting in model plants. They have been classified on the basis of their 16S rDNA gene sequence. The known auxin producer A. brasilense Cd strain has been used as a reference. The inoculation of olive cuttings was performed in two different ways: (i) by dipping cuttings in a liquid bacterial culture or (ii) by immersing them in a paste made of solid bacterial inoculant and sterile water. Under nursery conditions all of the tested bacterial strains were able to induce the rooting of olive cuttings to a similar or greater extent than the control cuttings treated with indole-3-butyric acid (IBA). The olive cultivars responded differently depending on the bacterial strain and the inoculation method. The strain that consistently gave the best results was Pantoea sp. AG9, the only one of the tested bacterial strains to express the enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase. The results are also discussed in terms of potential commercial interest and nursery feasibility performance of these strains.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".