Phosphorus Biofertilizers from Ash and Bones—Agronomic Evaluation of Functional Properties
Bibliographic record
Abstract
Renewable raw materials could be a valuable source of phosphorus for plants. The bioavailability of this element can be enhanced by phosphorus-solubilizing bacteria. Suspension biofertilizers have been produced from sewage sludge ash and animal bones and enriched with the bacteria Bacillus megaterium. The functional properties of these preparations were compared in field experiments (northeast Poland, 2014, four replications) on spring wheat (Triticum aestivum ssp. vulgare Mac Key) to conventional fertilizers (superphosphate, phosphorite), ash-water solution (without microorganisms) and a control treatment without P fertilization. The soil type and cultivation regime were adjusted to the requirements of spring wheat in line with good agricultural practice. The effects of biofertilizers on the following were investigated: wheat yield, ear density, number of grains in the ear, the weight of 1000 grains, harvest index, weed infestation, the weight and structure of crop residues, and the pH of soil. Phosphorus biofertilizers from ash and bones equalled commercial fertilizers in terms of their crop-enhancing efficiency. Biofertilizer from ash, and ash diluted with water reduced weed infestation of the growing crop. Biofertilizer from bones resulted in a greater weight of wheat crop residues. Biofertilizers did not change the pH of soil. It is expected that the production of biofertilizers containing recycled phosphorus will be an alternative to its non-renewable resources and will also contribute to effective waste management.
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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 | 0.000 | 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".