Nitrogen transformations and loss over winter in manure-amended soils with cover crops
Bibliographic record
Abstract
Many farmers apply manure in the fall (autumn season), but without an actively growing crop in the ground, the nitrogen (N) in the manure is susceptible to over-winter losses.Periods of freezethaw cycling can exacerbate N losses by stimulating soil microbes to transform reactive substrates like soil mineral N into nitrous oxide (N2O), a potent greenhouse gas.The uptake of reactive N from fall-applied manure by a fall-sown cover crop may reduce over-winter N losses.The objective of my research was to investigate the effect of combining fall manure application with cover cropping on soil N dynamics over winter and during periods of freeze-thaw cycling under field and laboratory conditions.I also examined the relationship between N2O production and reactive soil substrate concentrations.The field experiment was a full factorial in a randomized complete block design with three manure treatments (none, liquid, solid) and four cover crop types (no cover crop, 100% ryegrass [Lolium multiflorum Lam.], a 75% ryegrass/25% hairy vetch [Vicia villosa Roth] mixture and a 50% ryegrass/50% vetch mixture).The experiment was established at two field sites in Québec, Canada.A partial N mass balance (g N m -2 ) was calculated in fall (sum of the fall soil N stock to 0.15 m depth, N in fall-applied manure, and N in cover crop biomass) and in spring (sum of the spring soil N stock to 0.15 m depth and N in the winter-killed cover crop) for each treatment combination.After terminating the cover crop, spring wheat (Triticum aestivum L.) was planted, and each main plot was split into two subplots that received either 100 kg N ha -1 urea fertilizer or no fertilizer.Wheat samples were taken at tillering, flowering, and maturity to determine N content.Final yield was also measured.Cover crops were not effective at retaining manure N (≤7% uptake) and there was no difference in the fall and spring N balance among the manure and non-manure plots.Residual N was not
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".