Effect of presynchronization prior to Ovsynch on ovulatory response to first GnRH, ovulatory follicle diameter and pregnancy per AI in multiparous Holstein cows during summer in Iran
Bibliographic record
Abstract
Abstract The aim was to evaluate the effect of presynchronization with GnRH and PGF2α prior to Ovsynch on ovulatory response to first GnRH, diameter of largest follicle at TAI and pregnancy per AI (P/AI) in multiparous dairy cows during summer. Cows (n=1069) were randomly assigned to one of three timed-AI (TAI) protocols. The TAI protocols were: 1) Ovsynch (O; n=425), GnRH- 7d-PGF2α-56h-GnRH-16h-TAI), 2) double-Ovsynch (DO; n=302), GnRH-7d-PGF2α-3d-GnRH and Ovsynch was initiated 7 days later, and 3) G7G-Ovsynch (G7G; n=342), PGF2α-2d-GnRH and Ovsynch was initiated 7 days later. Ovarian examinations were performed by transrectal ultrasonography during Ovsynch to determine ovulatory response to first GnRH and diameter of largest follicle at TAI. Presynchronization increased ovulatory response after first GnRH of Ovsynch (P=0.001), which was greater in DO (74.0%) and G7G (76.0%) groups compared to O group (50.0%). Means (±SEM) diameter (mm) of largest follicle at TAI was smaller in cows presynchronized before Ovsynch (DO and G7G, overall 15.7±0.3) compared to that in cows subjected to a standard Ovsynch without presynchronization (18.5±0.42). P/AI at 32 d after Al was greater (P=0.001) in G7G (32.7%) and DO (31.1%) groups compared to Ovsynch (19.7%) group. Presynchronization prior to Ovsynch also affected P/AI at 60 and 150 d after AI (P<0.05). In conclusion, DO and G7G protocols resulted in greater ovulatory response to first GnRH, smaller ovulatory follicles and greater P/AI compared to a standard Ovsynch protocol. Therefore, TAI protocols that include a presynchronization with GnRH and PGF2α prior to Ovsynch should be used in multiparous cows during summer to achieve acceptable reproductive performance.
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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".