Short-term legacy effects of feedlot manure amendments on irrigated barley yield and soil macronutrient supply
Bibliographic record
Abstract
Limited research exists on short-term legacy effects of land application of different feedlot manures on barley (Hordeum vulgare L.) yield and soil macronutrient (NO3-N, PO4-P, K, and SO4-S) supply. In a study conducted in southern Alberta, feedlot manures with straw (ST) or wood-chip (WD) bedding were either stockpiled or composted and applied annually to a clay loam soil at 13, 39, and 77 Mg ha−1 dry wt. for 17 yr. Control treatments without any amendments or with inorganic fertilizer were included. In the second and third year (2016–2017) after discontinuing manure applications in 2014, barley silage yield and soil nutrient supply measured in situ with plant root simulator (PRS®) probes were determined. No significant (P > 0.05) treatment effects occurred on barley yield. Significant treatment effects occurred on soil nutrient supply, but these depended on date and interaction with other treatment factors. Manure rate generally increased soil nutrient supply. Soil NO3-N and PO4-P supply were 40%–59% lower for composted manure with ST than the other three manure type-bedding treatments, and they were 26%–53% greater for stockpiled than composted manure. This indicated variable manure type effects at different dates. At the two highest rates, soil K supply was 60%–106% greater for ST than WD bedding, and the reverse trend occurred where SO4-S supply was 40%–174% greater for WD than ST bedding. Overall, short-term legacy effects of feedlot manure type and bedding were more persistent on soil macronutrient supply than barley silage yield.
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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) | 0.001 | 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".