Effect of humic substances on rumen fermentation, nutrient digestibility, methane emissions, and rumen microbiota in beef heifers1
Bibliographic record
Abstract
Ruminants play an important role in food security, but there is a growing concern about the impact of cattle on the environment, particularly regarding greenhouse gas emissions. The objective of this study was to examine the effect of humic substances (HS) on rumen fermentation, nutrient digestibility, methane (CH4) emissions, and the rumen microbiome of beef heifers fed a barley silage-based diet. The experiment was designed as a replicated 4 × 4 Latin square using 8 ruminally cannulated Angus × Hereford heifers (758 ± 40.7 kg initial BW). Heifers were offered a basal diet consisting of 60% barley silage and 40% concentrate (DM basis) with either 0- (control), 100-, 200- or 300-mg granulated HS/kg BW. Each period was 28 d with 14 d of adaptation. Rumen samples were taken on day 15 at 0, 3, 6, and 12 h postfeeding. Total urine and feces were collected from days 18 to 22. Blood samples were taken on day 22 at 0 and 6 h postfeeding. Between days 26 and 28, heifers were placed in open-circuit respiratory chambers to measure CH4. Ruminal pH was recorded continuously during the periods of CH4 measurement using indwelling pH loggers. Intake was similar (P = 0.47) across treatments. Concentration of ammonia-N and counts of rumen protozoa responded quadratically (P = 0.03), where both increased at H100 and then decreased for the H300 treatments. Apparent total tract digestibility of CP (P = 0.04) was linearly increased by HS and total N retention (g/d, % N intake, g/kg BW0.75) was improved (P = 0.04) for HS when compared with the control. There was no effect of HS on CH4 production (g/d; P = 0.83); however, HS decreased the relative abundance of Proteobacteria (P = 0.04) and increased the relative abundance of Synergistetes (P = 0.01) and Euryarchaeota (P = 0.04). Results suggest that HS included at up to 300 mg/kg BW may improve N retention and CP digestibility, but there was no impact on CH4 production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".