Chemical composition and ruminal degradability of lucerne (<i>Medicago sativa</i>) products
Bibliographic record
Abstract
Abstract A study was conducted to determine the chemical composition and in situ nutrient ruminal degradability of three lucerne products. These were dehydrated pellets, sun‐cured pellets and cubes. Results of the chemical analysis showed that sun‐cured pellets had the highest (P < 0.05) neutral and acid detergent fibre as well as total carbohydrate levels, followed by cubes and dehydrated pellets respectively. Crude protein (CP) content was highest (P < 0.05) for dehydrated pellets (204.3 g kg−1), intermediate for sun‐cured pellets (160.0 g kg−1) and lowest for cubes (153.2 g kg−1). Intermediately degradable CP (buffer‐insoluble CP minus neutral detergent‐insoluble CP) was the main protein fraction in the three products and was higher (P < 0.05) in cubes than in dehydrated and sun‐cured pellets. Estimated net energy of lactation was highest (P < 0.05) for dehydrated pellets (5.9 MJ kg−1), intermediate for cubes (5.23 MJ kg−1) and lowest (P < 0.05) for sun‐cured pellets (5.15 MJ kg−1). Results of the in situ experiment indicated that dehydrated pellets had higher (P < 0.05) ruminal protein degradability than sun‐cured pellets and cubes. The estimated ruminal escape protein values for dehydrated pellets, sun‐cured pellets and cubes were 361, 420 and 498 g kg−1 CP respectively. It was concluded that differences in chemical composition and ruminal degradability among the three lucerne products were mainly due to differences in stage of maturity. It was also concluded that the dehydration process failed to increase the ruminal escape protein value of dehydrated pellets relative to sun‐cured pellets and cubes. © 2001 Society of Chemical Industry
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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 | 0.001 | 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".