Characterizing the phosphorus forms extracted from soil by the Mehlich III soil test
Bibliographic record
Abstract
Phosphorus (P) can limit crop production in many soils, and soil testing is used to guide fertilizer recommendations. The Mehlich III (M3) soil test is widely used in North America, followed by colorimetric analysis for P, or by inductively coupled plasma-based spectrometry (ICP) for P and cations. However, differences have been observed in M3 P concentrations measured by these methods. Using 31P nuclear magnetic resonance (P-NMR) and mass spectrometry (MS), we characterized P forms in M3 extracts. In addition to the orthophosphate that would be detected during colorimetric analysis, several organic P forms were present in M3 extracts that would be unreactive colorimetrically but measured by ICP (molybdate unreactive P, MUP). Extraction of these P forms by M3 was confirmed by P-NMR and MS in NaOH-ethylenediaminetetraacetic acid extracts of whole soils and residues after M3 extraction. The most abundant P form in M3 extracts was myo-inositol hexaphosphate (myo-IHP, phytate), a compound that may not contribute to plant-available P if tightly sorbed in soil. Concentrations of myo-IHP and other organic P forms varied among soils, and even among treatment plots on the same soil. Extraction of myo-IHP in M3 appeared to be linked to cations, with substantially more myo-IHP extracted from soils fertilized with alum-treated poultry litter than untreated litter. These results suggest that ICP analysis may substantially over-estimate plant-available P in samples with high MUP concentrations, but there is no way at present to determine MUP concentrations without analysis by both colorimetry and ICP. This study also tested procedures that will improve future soil P-NMR studies, such as treatment of acid extracts, and demonstrated that techniques such as P-NMR and MS are complimentary, each yielding additional information that analysis by a single technique may not provide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".