Dietary condensed tannins in bovine faeces and effects on soil microbial dynamics: are there environmental benefits for cattle production systems?
Bibliographic record
Abstract
Context Plant bioactive compounds such as condensed tannins (CT) are seen as an alternative to rumen chemical modulators to mitigate rumen methanogenesis in livestock; however, the presence of CT in ruminant faeces also produces a series of changes in soil microbiomes. Little is known about these effects on soil nutrient dynamics. Therefore, whether CT affect the decomposition process of faecal organic matter, delaying it and consequently increasing soil carbon and nitrogen (N) sequestration, merits study. Aims Our study investigated the effects of a diet rich in CT on bovine faecal composition and on subsequent dynamics of a soil microbial population. Methods Faeces were analysed from cattle fed the following diets: control (no CT), 1.25% CT, 2.5% CT. In a greenhouse pot experiment over a period of 60 days, faeces from the three dietary treatments were applied to soil and the soil microbial populations were measured against a control with no faeces applied. Key results The presence of CT increased the excretion of faecal N and of neutral and acid detergent fibres and lignin, and the higher rate of CT reduced the rate of soil organic matter decomposition. Treatments with dietary CT resulted in greater total numbers of bacteria in the soil than in the no-faeces control and stimulated numbers of Actinobacteria, Proteobacteria (α-Proteobacteria) and Firmicutes. Conclusions The study showed that CT alter N recycling and other nutrient inputs in a soil–animal ecosystem by increasing faecal N inputs, delaying organic matter breakdown, and changing soil microbial dynamics. Implications The presence of CT in ruminant diets can be beneficial to the soil environment. Sustainable management practices should be encouraged by providing ruminants with feed including high-CT legumes in silvopastoral 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 | 0.001 | 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".