Bio-based fertilisers can replace conventional inorganic P fertilisers under European pedoclimatic conditions
Bibliographic record
Abstract
Mineable phosphorus (P) resources are finite and unevenly distributed globally. Recycling of P from different waste streams as bio-based fertilisers (BBFs) provides a viable option for closing nutrient cycles. To implement this approach effectively, it is necessary to evaluate the P fertiliser efficiency of BBFs under field conditions using a mechanistic approach that links their performance to their chemical composition. This study aimed to test to which extent BBFs can replace conventional inorganic P fertilisers under different pedoclimatic conditions. To this end, the same eight BBFs were tested in field experiments over two consecutive years at five different sites in Europe growing cereals and sunflower. Furthermore, the residual effect of the BBFs in a succeeding crop was investigated. We found that none of the tested P-BBFs resulted in significantly lower yield or total P uptake than triple superphosphate. Ammonium magnesium phosphate (struvite), dicalcium phosphate and phytate-based fertilisers performed best across all field experiments (mean mineral replacement values of 80 – 125 %). No consistent effect of soil or climatic conditions was found. Only marginal residual effects were observed, suggesting that longer trials with repeated applications are necessary to quantify residual effects. The fact that two out of five trial sites were not responsive to P fertilisation highlights the need to consider soil P status for the successful implementation of P fertiliser field trials as well as for fertilising recommendations. In conclusion, most tested BBFs have the potential to replace conventional inorganic P fertilisers across a range of European soils and climate. • 8 P bio-based fertilisers (BBFs) tested in field trials in five European countries. • Similar yield & total P uptake obtained with BBFs compared to inorganic fertiliser. • BBFs reached mean mineral replacement values between 43 % and 125 %. • The ranking of BBFs between countries and years was not consistent. • Struvite, dicalcium-P and phytate-based BBFs performed best across sites and years.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".