Production performance and metabolic characteristics of cows fed whole plant faba bean silage in comparison with barley and corn silage
Bibliographic record
Abstract
This study aims to determine the effect of partial (50% and 75%) and complete (100%) replacement of barley and corn silage with whole plant faba bean silage on milk production, feed intake and efficiency, digestibility, and rumen fermentation characteristics of high producing cows. A repeated 4 × 4 Latin square (early lactating cows: four cannulated and four non-cannulated) design was used. The silage used for four treatments were different: control diet (T0; 18.37% corn silage + 12.23% barley silage), diet one (T50; 9.18% corn silage + 6.12% barley silage + 15.30% faba bean silage), diet two (T75; 4.59% corn silage + 3.06% barley silage + 22.95% faba bean silage), and diet three (T100; 30.60% faba bean silage). The results showed that fat corrected milk (3.5% FCM) and energy corrected milk (ECM) were linearly increased with increasing level of whole plant faba bean silage in the diets. The starch digestibility was linearly decreased from 95.3% to 90.4% with increasing supplementation using faba bean silage. Rumen fermentation characteristics (pH, ammonia, volatile fatty acids) were similar among all the treatments. In conclusion, the inclusion of whole plant faba bean silage improved FCM, ECM, milk fat yield, and efficiency without negatively affecting the intake of dry matter. This study showed that whole plant faba bean silage can be used as an alternative feed for dairy cows.
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".