Use of condensed tannin extract from quebracho trees to reduce methane emissions from cattle1
Bibliographic record
Abstract
Our objective was to determine if condensed tannin extract from quebracho trees (Schinopsis quebracho-colorado; red quebracho) could be used to reduce enteric methane emissions from cattle. The experiment was designed as a repeated 3 x 3 Latin square (4 squares) with 3 treatments (0, 1, and 2% of dietary DM as quebracho tannin extract) and 3 28-d periods. Six spayed Angus heifers (238 +/- 13.3 kg of initial BW) and 6 Angus steers (207 +/- 8.2 kg of initial BW) were each assigned to 2 squares. The measured condensed tannin content of the extract was 91%, and the basal diet contained 70% forage (DM basis). Feeding quebracho tannin extract had no effect on BW, ADG, or nutrient intakes. Furthermore, it had no effect on DM, energy, or fiber (ADF and NDF) digestibility, but apparent digestibility of CP decreased linearly (P < 0.001) by 5 and 15% with 1 and 2% quebracho tannin extract, respectively. There were no effects of quebracho tannin extract on methane emissions (g/d, g/kg of DM, % of GE intake, or % of DE intake). Feeding up to 2% of the dietary DM as quebracho tannin extract failed to reduce enteric methane emissions from growing cattle, although the protein-binding effect of the quebracho tannin extract was evident.
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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".