Effects of feeding salt‐tolerant forage cultivated in saline‐alkaline land on rumen fermentation, feed digestibility and nitrogen balance in lamb
Bibliographic record
Abstract
BACKGROUND: Mixing salt-tolerant plants with other plants may affect rumen fermentation, which could result in an increase of feed conversion rate. The objective of this study was to evaluate the effects of partially or entirely replacing the corn stover with a mixture of salt-tolerant forage (Dahurian wildrye grass, weeping alkaligrass and erect milkvetch) in the diet of lambs on ruminal fermentation, feed digestibility and nitrogen (N) balance. Ratios of corn stover to the mixture of salt-tolerant forages in the four experimental diets were 100:0, 67:33, 33:67 and 0:100, respectively, for control, low (LF), medium (MF) and high (HF). RESULTS: Ruminal pH was lower (P = 0.048) with LF and MF than with control and HF diets. Total VFA concentration was consistently higher (P = 0.039) for LF and MF than for control and HF with increasing amount of salt-tolerant forage. Ratio of acetate to propionate was linearly (P = 0.019) decreased due to the decrease in acetate production. Digestibilities of OM, NDF and CP in the whole tract linearly (P < 0.002) decreased with increasing amount of salt-tolerant forage. Similarly, retained N and ratio of retained N to digestible N also linearly (P < 0.005) decreased. CONCLUSION: Feeding salt-tolerant forage cultivated in saline-alkaline land improved rumen fermentation with increased total VFA production, and changed the rumen fermentation pattern to increased butyrate production. However, the decreased feed digestibility in the whole digestive tract of lamb may reduce nutrient availability to animals and thus adversely affect animal productivity. Additionally, feeding salt-tolerant forages may require more protein supplement to meet animal requirements, because of the low protein content and low protein digestibility of the salt-tolerant forages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".