The Influence of Manure Phytic Acid on Phosphorus Solubility in Calcareous Soils
Bibliographic record
Abstract
Manure characteristics can influence the potential for P transfer in runoff following land application of manures. This research assessed the influence of manure characteristics on P solubility in calcareous soils using manures from poultry ( Gallus Domisticus ) fed a variety of grain‐based diets with the manures containing a range of total P (5.6–16.4 g P kg −1 ), water‐extractable P (WEP, 0.9–4.7 g P kg −1 ), phytic acid P (0.1–7.6), total N/P ratios (2.6–5.1), and total C/P ratios (19.5–75.7). In addition, mono‐ammonium phosphate fertilizer and reagent grade inositol hexaphosphate (phytic acid [PA]), were included, as well as a control treatment with no P additions. Treatments were incorporated into two soils (Portneuf [Coarse‐silty, mixed, superactive, mesic Durinodic Xeric Haplocalcids] and Millville [Coarse‐silty, carbonatic, mesic Typic Haploxerolls]) at three rates (10, 20, and 40 mg P kg −1 ) and incubated for a total of 18 wk with subsamples taken at 2, 5, 9, and 18 wk. Soil samples were analyzed for inorganic and organic NaHCO 3 (Olsen) extractable P and select soils were analyzed at 0 and 12 wk by 31 P nuclear magnetic resonance spectroscopy (NMR) for soil P characterization. The percentage of WEP and PA (of total P) in the manures were linearly related ( r 2 = 0.94). Increases in Olsen P over time were positively related to the percentage of monoester P in the treatments. At 2 wk, there was a strong negative correlation between the amount of PA added in the treatments and increases in Olsen P. However, by 18 wk, Olsen P was more closely related to the amount of C or N added with the treatments. Changes in PA content of manures due to dietary modification may influence P sorption on calcareous soils in the short‐term while other characteristics such as C/P ratio may exert a stronger influence over changes in soil test P over longer time periods.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".