Phosphorus Accumulation in Cultivated Soils from Long‐Term Annual Applications of Cattle Feedlot Manure
Bibliographic record
Abstract
Historically, manure has been recognized as an excellent soil amendment that can improve soil quality and provide nutrients for crop production. In areas of high animal density, however, the potential for water pollution resulting from improper storage or disposal of manure may be significant. The objective of this study was to determine the P balance of cultivated soils under barley (Hordeum vulgare L.) production that have received long-term annual manure amendments. Nonirrigated soils at the study site in Lethbridge, AB, Canada, have received 0, 30, 60, or 90 Mg manure ha(-1) (wet wt. basis) while irrigated plots received 0, 60, 120, and 180 Mg ha(-1) annually for 16 yr. The amount of P removed in barley grain and straw during the 16-yr period was between 5 and 18% of the cumulative manure P applied. There was a balance between P applied in manure and P recovered in crops and soils (to the 150-cm depth) of nonirrigated plots during the 16-yr study. In irrigated plots, as much as 1.4 Mg P ha(-1) added (180 Mg ha(-1) yr(-1) treatment) was not recovered over 16 yr, and was probably lost through leaching. The risk of ground water contamination with P from manure was greater in irrigated than nonirrigated plots that have received long-term annual manure amendments. Manure application rates should be reduced in nonirrigated and irrigated plots to more closely match manure P inputs to crop P requirements.
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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 | 0.001 | 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".