Corn silage in dairy cow diets to reduce ruminal methanogenesis: Effects on the rumen metabolically active microbial communities
Bibliographic record
Abstract
Methane produced by the methanogenic Archaea that inhabit the rumen is a potent greenhouse gas and represents an energy loss for the animal. Although several strategies have been proposed to mitigate enteric CH4 production, little is known about the effects of dietary changes on the microbial consortia involved in ruminal methanogenesis. Thus, the current study aimed to examine how the metabolically active microbes are affected when dairy cows were fed diets with increasing proportions of corn silage (CS). For this purpose, 9 ruminally cannulated lactating dairy cows were used in a replicated 3 × 3 Latin square design and fed a total mixed ration (60:40 forage:concentrate ratio on a dry matter basis) with the forage portion being either alfalfa silage (0% CS), corn silage (100% CS), or a 50:50 mixture (50% CS). Enteric CH4 production was determined using respiration chambers and total rumen content was sampled for the determination of fermentation characteristics and molecular biology analyses (cDNA-based length heterogeneity PCR, quantitative PCR). The cDNA-based length heterogeneity PCR targeting active microbes revealed similar bacterial communities in cows fed 0% CS and 50% CS diets, whereas important differences were observed between 0% CS and 100% CS diets, including a reduction in the bacterial richness and diversity in cows fed 100% CS diet. As revealed by quantitative PCR, feeding the 100% CS diet increased the number of total bacteria, Prevotella spp., Archaea, and methanogenic activity, though it reduced protozoal number. Meanwhile, increasing the CS proportion in the diet increased propionate concentration but decreased ruminal pH, CH4 production (L/kg of dry matter intake), and concentrations of acetate and butyrate. Based on these microbial and fermentation changes, and because CH4 production was reduced by feeding 100% CS diet, this study shows that the use of cDNA-based quantitative PCR to estimate archaeal growth and activity is not reliable enough to reflect changes in ruminal methanogenesis. A more robust technique to characterize changes in archaeal community structures will help to better understand the microbial process involved in ruminal methanogenesis and, hence, enabling the development of more effective dietary CH4 mitigation strategies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".