Soil microbiomes from the groundnut basin of Senegal contain plant growth-promoting bacteria with potential for crop improvement in arid soils
Bibliographic record
Abstract
The principal methods to maintain soil fertility in Sahel soils are largely allowing fields to go fallow and manure addition. These methods are not currently sufficient to improve soil fertility. To promote biological amendments, we aimed to understand the plant-growth promoting traits of various soil microbial isolates. The soils collected in different areas in Senegal exhibited a similar eDNA profile of bacteria; the dominant microbes were Firmicutes, followed by Proteobacteria and Actinobacteria. Of 17 isolates identified and tested, the vast majority solubilized rock phosphate and a large number grew on culture medium containing 6% salt, but very few degraded starches or hydrolysed carboxymethyl cellulose or produced siderophores. Upon single inoculation, Peribacillus asahii RC16 and Dietzia cinnamea 55 significantly increased pearl millet growth and yield parameters. For cowpea, plant shoot length was significantly increased by Pseudarthrobacter phenanthrenivorans MKAG7 co-inoculated with Bradyrhizobium elkanii 20TpCR5, and nearly all rhizobacteria tested significantly improved cowpea dry weight and pod weight. Additionally, the double inoculation of Dietzia cinnamea 55 and MKAG7 significantly increased shoot length, dry weight, and seed head weight of pearl millet. These isolates are promising inoculants because they are ecologically-friendly, cost-effective, sustainable, and have fewer negative effects on the soil and its inhabitants.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".