Comparing phosphorus mobilization strategies using Aspergillus niger for the mineral dissolution of three phosphate rocks
Bibliographic record
Abstract
Phosphorus deficiencies are limiting crop production in agricultural soils worldwide. Locally available sources of raw phosphate rock (PR) are being recognized for their potential role in soil fertility improvement. Phosphorus bioavailability is essential for the efficiency of PRs and can be increased by acid treatments. The utilization of organic acid producing micro-organisms, notably Aspergillus niger, presents a sustainable alternative to the use of strong inorganic acids, but acid production of A. niger strongly depends on the mineral content of the growth media. This study compared the phosphorus mobilization efficiency of two biological treatments, namely addition of acidic cell-free supernatants from A. niger cultivations to PRs and the direct cultivation of A. niger with PRs. The results show that addition of PR to cultivations leads to significant differences in the profile of organic acids produced by A. niger. Additions of PR, especially igneous rocks containing high amounts of iron and manganese, lead to reduced citric acid concentrations. In spite of these differences, phosphorus mobilization was similar between treatments, suggesting that the simpler direct cultivation method was not inferior. In addition to citric acid, it is suggested that oxalic acid contributes to PR solubilization in direct cultivations with A. niger, which would benefit farmers in developing countries where conventional fertilizers are not adequately accessible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".