Screening of potential phosphate solubilizing bacteria inoculants should consider the contrast in phosphorus bio-solubilization rate along with plant growth promotion and phosphorus use efficiency
Bibliographic record
Abstract
AIMS: Although phosphate solubilizing bacteria (PSB) have been globally reported to improve soil phosphorus (P) availability and plant growth, technical gaps such as the lack of an ideal screening approach, is yet to be addressed. The potential of non-halo-forming PSB remains underestimated because of the currently adopted screening protocols that exclusively consider halo-forming and PSB with high phosphorus solubilization (PS) capacities. Yet, caution should be taken to properly assess PSB with contrasting PS rates regardless of the presence or absence of the solubilization halo. METHODS AND RESULTS: This study sought to examine the PS rate and plant growth promotion ability of 12 PSB categorized as high PSB (H-PSB), medium PSB (M-PSB), and low PSB (L-PSB) based on their PS rates of rock phosphate (RP). The non-halo-forming PSB Arthrobacter pascens was categorized as H-PSB, which might have been eliminated during the classical screening process. In addition, induction of organic acids and phosphatase activity in rhizosphere soils by H-, M-, and L-PSB was proportional to increased wheat P content by 143.22, 154.21, and 77.76 mg P g-1 compared to uninoculated plants (18.1 mg P g-1). CONCLUSIONS: Isolates considered as M- and L-PSB could positively influence wheat above-ground physiology and root traits as high as H-PSB. In addition, non-halo-forming PSB revealed significant PS rates along with positive effects on plant growth as high as halo-forming PSB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 teacher head, 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".