Seleção de inoculantes à base de turfa contendo bactérias diazotróficas em duas variedades de arroz
Bibliographic record
Abstract
The study consisted of a comparison of two-peat materials (Brazil and Canada) containing different C-total content. The peats were inoculated with strains of Herbaspirillum seropedicae ZAE 94, Burkholderia sp. M130, and Azospirillum brasilense Sp109, and monitored during a period of six months in relation to variation on humidity and survival of bacteria in the inoculant. The quantification of viable cells in the inoculant was measured by the Most Probable Number (MPN) method. The rice seeds were pelleted with the respective inoculants, grown in pots containing soil and maintained outside a greenhouse. The dry mass accumulation, N percent, N-total and yield were determined during the plant cycle. The humidity content varied with storage period. The survival measurement showed that only Burkholderia sp. M130 maintained the number of viable cells around 108 g-1 of peat, while there was a reduction in population of other strains. An increase of yield and total N of 13 and 19.4%, respectively in comparison to treatment fertilized with 40 kg N ha-1 was observed for variety IAC4440, inoculated with strain ZAE94. There was no difference in yield of the IR42 inoculated with either ZAE94 or M130, as compared to N control treatment. No significant difference in development of both rice varieties was observed for both peat used. The results suggest that peat can be used as a carrier for production of an inoculant based on diazotrophic bacteria, since it allowed maintenance of a bacterial population up to 108 cells g-1 peat during the storage period of up to 100 days. The results obtained encourage the practice of inoculation of non-leguminous plants.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".