Rhizobium population dynamics in the pea rhizosphere of rhizobial inoculant strain applied in different formulations
Bibliographic record
Abstract
The effect of inoculant formulation on the population dynamics of rhizobia in the pea rhizosphere was investigated using a streptomycin-resistant mutant of Rhizobium leguminosarum bv. viceae NITRAGIN128C56G (128C56G strR). The isolate was formulated into liquid, peat powder, and granular peat carriers, and was tested on pea at field sites near Saskatoon, Saskatchewan, and Beaverlodge, Alberta, in 1996 and 1997. The liquid and peat powder formulations were applied to seed while the granular inoculant was applied to soil. In three out of four site years, population dynamics were similar among formulations: an initial decline or lag period lasting 2-5 days followed by an increase to approximately 10(5) colony-forming units (CFU)/seedling by 14-28 days after planting (DAP) and, where sampled, a continuing increase from 10(7) to 10(8) CFU/plant at 63 DAP. In these same site years, nodule number (not determined at Beaverlodge in 1997) and nodule occupancy at 60 days were not significantly different among formulations. In contrast, soil populations of 128C56G strR from the liquid formulation declined to near zero by 28 DAP at Beaverlodge in 1996, when soil moisture was excessive in spring because of high rainfall. Populations increased in this treatment after this time, but remained significantly lower than the populations of the other two formulations throughout the sampling period. Pea seed yields were not significantly different among treatments in either year at Beaverlodge, but were significantly higher with granular inoculant than the noninoculated control in Saskatoon. Within inoculated treatments at Saskatoon, there were no significant differences in grain yield.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".