Milk yield and composition in dairy goats fed extruded flaxseed or a high-palmitic acid fat supplement
Bibliographic record
Abstract
Abstract We compared the potential of dietary lipid supplements of different fatty acid compositions to affect milk performance when early lactation dairy goats were fed a high-concentrate diet. Thirty Alpine goats at 23 ± 5 d in milk were allocated to 1 of 10 blocks according to parity and milk fat concentration. Within each block, goats were randomly assigned to receive, during a period of 41 d, either CONT) a basal diet with a forage to concentrate ratio of 45:55, used as control, or PALM) the basal diet + 2% of a palmitic acid-enriched fat supplement, or FLAX) the basal diet + 7% of extruded flaxseed. Body weight, dry matter intake and milk yield were not different between treatments. As compared with CONT, goats fed PALM and FLAX had a greater milk fat concentration. Moreover, milk fat yield was numerically (but non-significantly) greater with PALM than with CONT. Milk fat from goats receiving PALM had a greater concentration of 16:0 as compared with CONT and FLAX, whereas a greater concentration of cis -9, cis -12, cis -15 18:3 was observed when goats were fed FLAX as compared with CONT and PALM. Under the conditions of the current experiment, dietary fat supplementation had only minor impacts on the yield of major milk constituents, with the exception of a modest increase in fat yield when goats were fed PALM. The impact of a greater concentration of 16:0 in milk fat of goats receiving this feed ingredient on the nutritive value of dairy products remains to be determined.
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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) | 0.001 | 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".