Root and Rhizosphere Colonization of Soybean [<i>Glycine max</i> (L.) Merr.] by Plant‐Growth‐Promoting Rhizobacteria at Low Root Zone Temperatures and under Short‐Season Conditions
Bibliographic record
Abstract
Co‐inoculation of plant‐growth‐promoting rhizobacteria (PGPR) with B. japonicum has been shown to increase soybean [Glycine max (L.) Merr.] nodulation, nitrogen fixation, growth and physiological activity at suboptimal root zone temperatures (RZTs). We studied the survival and growth of seven PGPR inoculated on soybean in a sterile rooting medium at three RZTs (25, 17.5 and 15 °C) on a growth bench. The survival of the two most promising strains (Serratia liquefaciens 2‐68 and S. proteamaculans1‐102) was studied under field conditions in methyl bromide fumigated and non‐fumigated soils. In general, population densities varied with temperature. PGPR strains generally colonized the rhizosphere and root surface effeciently at higher RZTs; however, S. proteamaculans 1‐102 colonized best at a low RZT (15 °C). The population of PGPR applied to the rhizosphere either with or without addition of B. japonicum increased over time in fumigated soil as compared to non‐fumigated soil, indicating that the PGPR survive and proliferate better under fumigated conditions. S. liquefaciens 2‐68 had higher population densities both on the root and in the rhizosphere, demonstrating, their ability to colonize under short‐season conditions. The possible interactions between the two cultivars (Maple Glen and AC Bravor) and the PGPR were generally not significant, despite observations that growth and yield of AC Bravor respond more strongly to PGPR inoculation.
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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) | 0.000 | 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".