Predicting Phosphorus Availability from Soil‐Applied Composted and Non‐Composted Cattle Feedlot Manure
Bibliographic record
Abstract
Prediction of phosphorus (P) availability from soil-applied composts and manure is important for agronomic and environmental reasons. This study utilized chemical properties of eight composted and two non-composted beef cattle (Bos taurus) manures to predict cumulative phosphorus uptake (CPU) during a 363-d controlled environment chamber bioassay. Ten growth cycles of canola (Brassica napus L.) were raised in pots containing 2 kg of a Dark Brown Chernozemic clay loam soil (fine-loamy, mixed, Typic Haploboroll) mixed with 0.04 kg of the amendments. Inorganic P fertilizer (KH2PO4) and an unamended control were included for comparison. All treatments received a nutrient solution containing an adequate supply of all essential nutrients, except P, which was supplied by the amendments. Cumulative P uptake was similar for composted (74 mg kg-1 soil) and non-composted manures (60 mg kg-1 soil) and for the latter and the fertilizer (40 mg kg-1 soil). However, the CPU was significantly higher for organic amendments than the control (24 mg kg-1 soil) and for composted manure than the fertilizer. Apparent phosphorus recovery (APR) from composted manure (24%) was significantly lower than that from non-composted manure (33%), but there was no significant difference in APR between the organic amendments and the fertilizer (27%). Partial least squares (PLS) regression indicated that only two parameters [total water-extractable phosphorus (TPH2O) and total phosphorus (TP) concentration of amendments] were adequate to model amendment-derived cumulative phosphorus uptake (ACPU), explaining 81% of the variation in ACPU. These results suggest that P availability from soil-applied composted and non-composted manures can be adequately predicted from a few simple amendment chemical measurements. Accurate prediction of P availability and plant P recovery may help tailor manure and compost applications to plant needs and minimize the buildup of bioavailable P, which can contribute to eutrophication of sensitive aquatic systems.
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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) | 0.000 | 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".