Barley dry matter yield, crop uptake, and soil nutrients under fresh and composted manure containing straw or wood-chip bedding
Bibliographic record
Abstract
Limited information exists on the effect of fresh versus composted beef cattle manure containing straw or wood chips on barley (Hordeum vulgare) yield, nutrient uptake, and soil nutrient status in the Great Plains region of North America. Barley was grown on an irrigated clay loam soil in southern Alberta from 1999 to 2001. The treatments were three rates (13, 39, 77 Mg dry material per hectare) of fresh manure (FM) or composted manure (CM) containing either straw (ST) or wood-chip (WD) bedding, one inorganic (IN) fertilizer treatment (100 kg N ha-1, 17 kg P ha-1), and a control treatment; applied in the fall of 1998, 1999, and 2000. Dry matter yield was not significantly (P > 0.05) influenced by manure type or bedding material. Crop protein was 7% higher under FM (12.7 g kg-1) than CM (11.9 g kg-1) in 2001, and crop N uptake was 11 to 13% higher for CM-ST (171.3 kg ha-1) and FM-WD (174.9 kg ha-1) than CM-WD (154.7 kg ha-1) over the 3 yr. Soil available N was 20 to 261% higher for FM than CM at the 39 and 77 Mg ha-1 rates, and it was 62 to 199% higher for FM than CM in 2000 and 2001. Soil available N was 48 to 57% higher for ST than WD at the two higher application rates, and it was 26 to 65% higher for ST than WD in all 3 yr. Overall, manure type and bedding influenced certain crop and soil parameters, and higher available soil N under FM and ST indicated a potential for greater mineralization under these treatments. Key words: Barley yield, nutrient uptake, soil nutrients, fresh manure, compost, bedding
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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) | 0.001 | 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".