Supplementation of lactating ewes with a glucogenic preparation or β-carotene in mid- to late lactation, on subsequent milk yield and luteinizing hormone secretion
Bibliographic record
Abstract
The effects of a glucogenic preparation (Nutrimix®) or β-carotene (Rovimix® beta carotene) supplementation of ewes during mid- to late-lactation on their milk yield were assessed in a study where 66 Chios-breed ewes were allocated into three equal (n = 22) groups. Ewes in group A received daily a glucogenic preparation and those in group B β-carotene, starting 35 d before estrus synchronization until 7 d after artificial insemination (supplementation period); ewes in group C were untreated controls. The estrus cycle was synchronized and double AI was carried out 48 and 60 h after withdrawal of progestagen sponges. Milk yield was measured daily during the supplementation period. Blood samples were collected at 2-h intervals, from 28 to 54 h after sponge withdrawal; the concentration of plasma luteinizing hormone (LH) was measured. Increased milk yield was recorded after supplementation with the glucogenic preparation (P < 0.05), but not with β-carotene (P > 0.05). There were no differences in LH concentration during surge release in supplemented ewes; furthermore, there were no differences between groups in body weight and litter size. It is concluded that supplementation of ewes with a glucogenic preparation during mid- to late-lactation may lead to improved milk production. Key words: Sheep reproduction, milk yield, β-carotene, energy, luteinizing hormone
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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 | 0.000 | 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".