Enhanced Soybean Plant Growth Resulting from Coinoculation of <i>Bacillus</i> Strains with <i>Bradyrhizobium japonicum</i>
Bibliographic record
Abstract
Nodulation and subsequent nitrogen fixation by soybean [Glycine max (L.) Merr.] plants are inhibited by low root zone temperatures (RZTs). Plant growth promoting bacteria can help overcome these deleterious effects. Three Bacillus strains, B. subtilis NEB4 and NEB5 and B. thuringiensis NEB17, were isolated from inside the nodules of vigorous field‐grown soybean plants in 1998, and were shown to have plant growth promoting activity on pouch‐grown soybean plants under greenhouse conditions. To test their ability to improve soybean nodulation and growth under low RZTs, these strains were coinoculated onto soybean plants, with Bradyrhizobium japonicum, under greenhouse conditions at RZTs of 25, 17, and 15°C, and under field conditions in a short growing season area. In all cases, the experiments were conducted with soybean cultivar OAC Bayfield. All the three Bacillus strains enhanced soybean nodulation and growth in greenhouse and field experiments. Coinoculation with NEB17 provided the largest and most consistent increases in nodule number, nodule weight, shoot weight, root weight, total biomass, total nitrogen, and grain yield. The other two strains provided positive responses in only 1 of the 2 yr of field‐testing. Thus, B. thuringiensis NEB17 would be suitable for use as a plant growth promoting bacterial strain in soybean production systems in short growing season regions.
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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) | 0.001 | 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".