Pregnancy Outcomes Following GnRH- or Prostaglandin-Based Timed Artificial Insemination Protocols in Water Buffaloes (Bubalus bubalis)
Bibliographic record
Abstract
The efficiencies of Timed Artificial Insemination (TAI) protocols in post-partum riverine dairy buffaloes were evaluated in the present research work. In Study 1, GnRH-based ovulation synchronization for Fixed Time Artificial Insemination (FTAI) protocol was evaluated for pregnancy. Buffaloes in Treatment 1 were subjected to the Ovsynch (GnRH-PGF2α-GnRH) protocol. Buffaloes in Treatment 2 were subjected to Controlled Internal Drug Release–Gonadotrophin Releasing Hormone (CIDR-Synch-GnRH) protocol, and buffaloes in Treatment 3 were subjected to CIDR-Synch-human Chorionic Gonadotrophin (CIDR-Synch-hCG) protocol. In Study 2, Prostaglandin-based estrus synchronization protocols were similarly evaluated for pregnancy. Buffaloes in Treatment 1 were treated with Prostaglandin hormone alone; buffaloes in Treatment 2 were subjected to Prostaglandin-GnRH protocol, while buffaloes in Treatment 3 were subjected to Prostaglandin-hCG protocol. Results in Study 1 revealed that supplementation of Ovsynch with CIDR in Treatment 2 and 3 resulted in significantly higher (P<0.05) pregnancy rates compared with Ovsynch alone (T1). Meanwhile, the use of hCG as the final ovulatory hormone in FTAI protocol (T3) yielded a significantly higher (P<0.05) pregnancy rate than GnRH (T2). In Study 2, results showed that prostaglandin protocols enhanced with GnRH (T2) or with hCG (T3) resulted in significantly higher (P<0.05) pregnancy rates (31.88±3.39 and 34.62±1.53), respectively, compared with Prostaglandin alone (T1, 23.91±2.49). However, pregnancy rates in Prostaglandin-based protocols (T2) and (T3) were not significantly different (P<0.05). In sum, the present study demonstrated that supplementation with exogenous progesterone (CIDR) improved the efficiency of Ovsynch FTAI protocol while using hCG as the final ovulatory hormone is found to be the best among FTAI protocols. Meanwhile, a Prostaglandin-based protocol enhanced with ovulatory hormones, either GnRH or hCG, on the day of AI improved pregnancy rates in post-partum water buffaloes.
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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 | 0.001 | 0.001 |
| 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".