Co-inoculation of beneficial microorganisms in upland rice cultivated at different phosphorus levels
Bibliographic record
Abstract
Beneficial microorganisms can sustainably improve rice production. This study characterized indole-acetic-acid-producing and P-solubilizing bacteria, investigating their impact on upland rice through single or co-inoculation. Four bacterial strains (BRM 063573, BRM 67205, BRM 063574, and BRM 67206) were identified by 16S rRNA gene sequencing. A greenhouse experiment was arranged in a 20 × 3 factorial design with four replications. The first factor included 18 bacterial combinations and two controls (without fertilization or inoculant, and with fertilization but no inoculant). The second factor tested three phosphorus doses (25%, 50%, and 100% of the recommended P dosage). Growth and productivity parameters were determined. Based on the 16S rRNA gene sequencing, the bacteria BRM 063574 was closely related to Stenotrophomonas maltophilia, while BRM 063573 and BRM 67206 were closely related to Bacillus pumilus and BRM 67205 was closely related to Paenibacillus pabuli. Co-inoculation treatments generally outperformed single inoculations, improving performance in number of tillers, plant height, root volume, root weight, and shoot weight. Single inoculation and co-inoculation had different effects on number of pods, number of full grain and grain weight, with co-inoculation consistently giving better results. The variability in response to single inoculation suggests an inconsistency in the performance of single inoculants. Co-inoculation, on the other hand, consistently offered advantages, improving the number of pods, number of full grains and grain weight at different phosphate doses. Based on grain production, the co-inoculants BRM 67207 + BRM 67206 and BRM 67207 + BRM 063574 are most promising for use as rice inoculants, offering consistent benefits for improving yield.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".