Lower Pregnancy Losses in Lactating Dairy Cows Fed a Diet Enriched in α-Linolenic Acid
Bibliographic record
Abstract
The objectives were to determine if a diet enriched in alpha-linolenic acid (ALA) would influence ovarian function, early embryo survival, conception rates, and pregnancy losses in lactating dairy cows. Beginning 28 d before breeding, Holstein cows (55 +/- 22 d postpartum; mean +/- SD) were assigned to diets supplemented with either rolled flaxseed (FLAX; 56.7% ALA, n = 62) or rolled sunflower seed (SUNF; 0.1% ALA, n = 59) to provide approximately 750 g of oil/d. Diets continued for 32 d after timed artificial insemination (TAI, d 0) following a Presynch/Ovsynch protocol. Barley silage- and barley grain-based TMR were formulated to meet or exceed National Research Council requirements. Metabolizable protein and net energy for lactation concentrations were similar in the 2 diets. Based upon a mean dry matter intake of 22 kg/d, cows fed FLAX or SUNF consumed > 410 g or < 1 g of ALA, respectively. Pregnancy was confirmed by ultrasound 32 d after TAI. Nonpregnant cows were placed on a second Ovsynch regimen and reinseminated 42 d after first TAI, and received oilseeds for 32 d after second TAI. Relative to prediet levels, FLAX increased the ALA content of milk by 187%. Ovarian ultrasonography was performed in 8 cows per diet; the mean diameter of ovulatory follicles was larger in cows fed FLAX compared with SUNF (16.9 +/- 0.9 vs. 14.1 +/- 0.9 mm), but follicle number, corpus luteum size, and plasma progesterone concentrations remained unaffected. Presumptive conception (progesterone < 1 ng/mL on d 0 and > 1 ng/mL on d 21) rates to first TAI were greater in FLAX than in SUNF (72.6 vs. 47.5%). Pregnancy losses were lower in cows fed FLAX (9.8%) compared with those fed SUNF (27.3%). Including flaxseed in the ration of dairy cows increased the size of the ovulatory follicle and reduced pregnancy losses.
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".