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Effects of short and long - term nutrition and progesterone supplementation on the success of fixed - time artificial insemination in the ewe. | LitMetric

AI Article Synopsis

  • The study investigated how long-term nutrition (LTN), short-term nutrition (STN), and progesterone supplementation affect the timing of estrus and reproductive success in ewes.
  • High LTN improved pregnancy rates and litter size but interacted with STN in affecting estrus timing, while STN alone raised pregnancy rates without changing litter size.
  • Progesterone supplementation enhanced estrus synchrony but delayed its onset and did not impact overall pregnancy rates or litter size, indicating nutrition strategies are crucial for improving artificial insemination outcomes.

Article Abstract

The success of fixed - time artificial insemination (AI) in the ewe is variable due to poor synchrony of estrus. We examined the effects of long-term nutrition (LTN; low, medium, high - 6 months), short-term nutrition (STN; 1.0 M, 1.5 M - 14 days) and progesterone supplementation (P; single pessary, replacement on Day 9) on synchrony and reproductive outcomes. High LTN advanced (P < 0.05) estrus, increased (P = 0.06) pregnancy (range 71.1 - 81.1%) and improved (P < 0.01) litter size (range 1.30 - 1.50). STN increased (P < 0.05) pregnancy (79.0 versus 72.3%) but not litter size or timing of estrus. A LTN x STN interaction (P < 0.01) for time of estrus indicates that the effects of LTN were moderated by STN depending on the level of LTN. Pessary replacement delayed (P < 0.05) the onset of estrus, improved synchrony but did not affect pregnancy or litter size. High LTN increased (P < 0.05) the number of large (≥ 3.8 mm) and medium - size follicles (2.0 - 3.7 mm) but the diameter of large follicles tended to be reduced (P = 0.08) on Day 12. STN did not affect follicle number or size whilst P reduced (P < 0.05) the diameter of large follicles on Day 12 (4.83 versus 5.10 mm) and increased the number of medium - size follicles (3.56 versus 2.74 mm). In conclusion, both LTN and STN are major sources of variability in AI programs whilst pessary replacement has potential to reduce variability.

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Source
http://dx.doi.org/10.1016/j.anireprosci.2024.107477DOI Listing

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