Molecular speciation and aromaticity of biochar-manure: Insights from elemental, stable isotope and solid-state DPMAS 13C NMR analyses
Bibliographic record
Abstract
The use of biochar (BC) in feedlot cattle diets has recently been explored as an approach to simultaneously improving animal production and reducing enteric methane (CH4) emissions. This study examines the impact of BC on manure properties and whether BC affects manure composition and carbon (C) and nitrogen (N) outputs from feedlot steers offered a barley-based diet with BC at 0.0, 0.5, 1.0 and 2.0% (BC0, BC0.5, BC1 and BC2) of diet dry matter. Manure was sampled three times over a 235 day feeding trial conducted in southern Alberta, Canada. Results showed that BC2 increased total C and the C/N ratio by 5.7 and 6.6% relative to BC0, respectively (P < 0.05), while total N exhibited a quadratic response from BC0 to BC2 (P = 0.005). Manure 15δN signatures, ranging from +3.83 to +7.34‰, were not affected (P > 0.05) by BC treatment. DPMAS 13C NMR revealed similar structural features among BC0 and BC2; indigestible BC had a minor impact on the bulk-C speciation of manure organic matter (OM). Compositional changes were limited to the aromatic-C region of the 13C NMR spectra. Fused-ring domains, mainly pyrogenic-C, were increased by 1.56-fold at BC2 relative to BC0. Overall, results demonstrated that BC stabilizes recalcitrant-C in manure OM, potentially sequestering soil-C when applied to croplands. This approach provides an added value to its use in ruminant diets, mainly from a nutrient cycling perspective. However, whole-farm studies are further required to validate the incorporation of BC into beef production 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".