Phosphorus Speciation in Agro-Industrial Byproducts: Sequential Fractionation, Solution <sup>31</sup>P NMR, and P <i>K</i>- and <i>L</i><sub>2,3</sub>-Edge XANES Spectroscopy
Bibliographic record
Abstract
Little is known about P species in agro-industrial byproducts from developing countries, which may be either pollutants or valuable soil amendments. The present study speciated P in dry (COD) and wet (COW) coffee, sisal (SIS), barley malt (BEB) and sugar cane processing (FIC) byproducts, and filter cakes of linseed (LIC) and niger seed (NIC)with sequential fractionation, solution (31)P nuclear magnetic resonance (NMR) spectroscopy, and P K- and L(2,3)-edge X-ray absorption near-edge structure (XANES) spectroscopy. The sequential P fractionation recovered 59% to almost 100% of total P (P(t)), and more than 50% of P(t) was extracted by H(2)O and NaHCO(3) in five out of seven samples. Similarly, the NaOH + EDTA extraction for solution (31)P NMR recovered 48-94% of P(t). The (31)P NMR spectra revealed orthophosphate (6-81%), pyrophosphate (0-10%), and orthophosphate monoesters (6-94%). Orthophosphate predominated in COD, COW, SIS, and FIC, whereas BEB, UC, and NIC were rich in orthophosphate monoesters. The concentrations of P(i), and P(o) determined in the sequential and NaOH + EDTA extractions and (31)P NMR spectra were strongly and positively correlated (r = 0.88-1.00). Furthermore, the P K- and L(2,3)-edge XANES confirmed the H(2)SO(4)--P(i) detected in the sequential fractionation by unequivocal identification of Ca--P phases in a few samples. The results indicate that the combined use of all four analytical methods is crucial for comprehensive P speciation in environmental samples and the application of these byproducts to soil.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".