A successful breeding program depends on understanding the onset of pregnancy in beef herds. Monitoring heat cycles, observing the right timing for insemination, and identifying/addressing fertility problems are all parts of this process. Artificial Insemination (AI), for example, can increase pregnancy rates and improve genetic progress in beef herds. Indeed, the beef industry has been using reproductive technologies at an increasing rate, such as in vitro fertilization and genomic selection. In this episode, Dr. Cliff Lamb discusses how these technologies can improve breeding programs, make them more efficient and accurate, and thus, improve genetics and herd performance.
“We utilize embryo transfer and in vitro fertilization. Those technologies are continuously evolving and may have a bigger role in the future, rather than just the utilization in synchronization for AI." - Dr. Cliff Lamb
What you’ll learn:
- Highlight (00:00)
- Introduction (0:30)
- The future of applied reproduction in beef (8:22)
- Pregnancy rates in beef cattle (13:24)
- Possible reasons for embryonic losses (16:37)
- Doppler ultrasound technique (27:43)
- Zinc Sparks (29:52)
- In vitro fertilization (32:20)
- The use of beef semen and, possibly, beef embryos in dairy cows (35:35)
- Sexed semen (37:36)
- Ovulation: humans and cows (43:02)
- Final thoughts (45:36)
- 3 final questions (50:16)
Meet the guest: Dr. Cliff Lamb
Experience:
- Current: Director at Texas A&M AgriLife Research
- Past: Head of Department at Texas A&M Department of Animal Science; Assistant Director and Professor at the University of Florida - NFREC; Associate Professor at the University of Minnesota.
Background:
- Ph.D., Reproductive Physiology (Kansas State University)
- M.Sc., Reproductive Physiology (Kansas State University)
- B.Sc., Animal Sciences (Middle Tennessee State University)
Connect with the guest on Social Media: LinkedIn
𝗟𝗶𝘀𝘁𝗲𝗻 𝗼𝗻 𝗔𝗽𝗽𝗹𝗲 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀, 𝗦𝗽𝗼𝘁𝗶𝗳𝘆 𝗼𝗿 𝗮𝗻𝘆 𝗺𝗮𝗷𝗼𝗿 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺.
Information
- Show
- FrequencyUpdated Weekly
- PublishedFebruary 1, 2023 at 9:25 PM UTC
- Length56 min
- Season1
- Episode11
- RatingClean