Isolation, screening, characterization, and selection of superior rhizobacterial strains as bioinoculants for seedling emergence and growth promotion of Mandarin orange (<i>Citrus reticulata</i>Blanco)
Bibliographic record
Abstract
Mandarin orange (MO) is an important fruit crop of tropical and subtropical regions of the world. A total of 217 morphologically distinct rhizobacteria from MO orchards in 3 states of northeastern India were isolated and analyzed for 4 plant-growth-promoting (PGP) attributes: nitrogen fixation, production of indole acetic acid like substances, solubilization of phosphate, and ability to antagonize pathogenic fungi. Isolates were ranked based on in-vitro-assayed PGP attributes, and 10 superior isolates were selected to test their effect on seedling emergence and seedling growth in a completely randomized pot experiment. These 10 isolates increased seedling emergence over a noninoculated control within 45 days after sowing. Five isolates, namely RCE1, RCE2, RCE3, RCE5, and RCE7, significantly increased shoot length, shoot dry biomass, and root dry biomass of 120-day-old seedlings over the noninoculated control. The beneficial effects of 4 selected strains, namely Enterobacter hormaechei RCE-1, Enterobacter asburiae RCE-2, Enterobacter ludwigii RCE-5, and Klebsiella pneumoniae RCE-7, on growth of the seedlings were visible up to 1 year after their transfer to 8 kg capacity pots. These strains were superior both in terms of in-vitro-assayed PGP attributes and of their beneficial effect in low phosphorus soil and, thus, may be promising bioinoculants for promoting early emergence and growth of MO seedlings.
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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".