Phosphorus Speciation in Sequentially Extracted Agro‐Industrial By‐Products: Evidence from X‐ray Absorption Near Edge Structure Spectroscopy
Bibliographic record
Abstract
The phosphorus (P) in agro-industrial by-products--a potential source of freshwater eutrophication but also a valuable fertilizer--needs to be speciated to evaluate its fate in the environment. We investigated to what extent X-ray absorption near edge structure (XANES) spectroscopy at the P K- and L2.3-edges reflected differences in sequentially extracted filter cakes from sugarcane (Saccharum officinarum L.) (FIC) and niger seed (Guizotia abyssinica Cass.; NIC) processing industry in Ethiopia. The P fractionation removed more labile (54%) and H2SO4-P (28%) from FIC than from NIC (18% labile, 12% H2SO4-P). For the FIC residues after each extraction step, linear combination (LC) fitting of P K-edge spectra provided evidence for the enrichment of Ca-P after the NaOH-extraction and its almost complete removal after the H2SO4-treatment. The LC-fitting was unsuccessful for the NIC samples, likely because of the predominance of organic P compounds. The different proportions of Ca-P compounds between FIC (large) and NIC (small) were more distinctive in L2-than in the K-edge XANES spectra. In conclusion, the added value of complementary P K- and L2.3-edge XANES was clearly demonstrated, and the P fractionation and speciation results together justify using FIC and NIC as soil amendments in the tropics.
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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".