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Efficacy of a modified Double-Ovsynch protocol for the enhancement of reproductive performance in Hanwoo cattle

  • Jae Kwan Jeong (College of Veterinary Medicine, Chungbuk National University) ;
  • Ui Hyung Kim (Hanwoo Research Institute, National Institute of Animal Science, Rural Development Administration) ;
  • Ill Hwa Kim (College of Veterinary Medicine, Chungbuk National University)
  • Received : 2022.09.13
  • Accepted : 2022.11.21
  • Published : 2023.04.01

Abstract

Objective: We aimed to evaluate the efficacy of a modified Double-Ovsynch protocol vs artificial insemination following estrus detection (AIED) for the enhancement of reproductive performance in Hanwoo cattle. Methods: Four hundred twelve Hanwoo cows were allocated to two treatment groups. The first group of cows were administered gonadotropin releasing hormone (GnRH) on Day 36 (±0.6), prostaglandin F (PGF) on Day 46 (8 to 12 days later), and GnRH on Day 49, which was followed by Ovsynch, consisting of an injection of GnRH on Day 56, PGF on Day 63, and GnRH 56 h and timed AI (TAI) 16 h later (modified Double-Ovsynch group, n = 203). The second group of cows underwent AIED (AIED group, n = 209) and were designated as controls. Results: The pregnancy per AI 60 days after the first AI was higher in the modified Double-Ovsynch (68.5%) than in the AIED (56.5%) group, resulting in a higher probability of pregnancy per AI (odds ratio: 1.68, p<0.05). Moreover, cows in the modified Double-Ovsynch group were more likely (hazard ratio: 1.28, p<0.05) to be pregnant by 150 days after calving than cows in the AIED group, and this difference was associated with a lower mean number of AIs per conception (1.27 vs 1.39, p<0.05) and a shorter median interval between calving and pregnancy (72 vs 78 days, p<0.1). Conclusion: The modified Double-Ovsynch protocol, adjusted according to the herd visit schedule, can be readily used to increase the pregnancy per AI following the first AI and to shorten the interval between calving and pregnancy in beef herds.

Keywords

Acknowledgement

This research was supported by Chungbuk National University Korea National University Development Project (2022).

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