天美传媒

Artificial insemination; Estrus synchronization; Goat reproduction; Reproductive efficiency; Hormonal protocols; Breeding management; Small ruminants; Genetic improvement; Fertility rate; Livestock productivity

Introduction

Goat farming plays a crucial role in the livelihoods of millions of rural families around the world, particularly in developing countries, where goats serve as a source of meat, milk, fiber, and income. However, reproductive inefficiency remains a major constraint in goat production systems due to irregular estrus cycles, seasonal breeding patterns, and difficulties in timely mating [1-5]. Advanced reproductive technologies such as artificial insemination (AI) and estrus synchronization offer a practical solution to overcome these limitations and boost productivity. These technologies allow for the precise timing of breeding, efficient use of superior genetics, and reduction in reproductive gaps, making them essential tools in modern goat herd management. This study explores the combined application of AI and estrus synchronization protocols in improving conception rates, kidding intervals, and overall reproductive performance in goats under field and semi-intensive systems [6-10].

Discussion

A total of 120 healthy does aged 2–4 years from three different goat breeds (Sirohi, Jamunapari, and Osmanabadi) were selected and randomly allocated into three treatment groups: Group A received estrus synchronization followed by AI using chilled semen; Group B received estrus synchronization followed by AI using frozen semen; and Group C served as the natural mating control group. The estrus synchronization was carried out using a CIDR (Controlled Internal Drug Release) device along with intramuscular injections of PMSG (Pregnant Mare Serum Gonadotropin) and PGF2α (Prostaglandin F2 alpha), designed to induce and synchronize estrus within a 48–72-hour window.

Following synchronization, estrus signs were monitored, and AI was performed 48–56 hours after CIDR removal. In Group A, conception rates were recorded at 70%, while Group B achieved 61%, compared to 52% in the naturally mated control group. Estrus synchronization significantly reduced the variability of estrus onset and allowed for efficient use of labor and genetic resources. The kidding rates in synchronized and AI groups were higher, and litter sizes were slightly increased due to improved timing and semen quality control.

The use of AI also enabled the introduction of superior genetic material from elite bucks, even across regions, without the need to transport live animals. The chilled semen group (Group A) had better fertility outcomes than the frozen semen group, likely due to reduced sperm viability loss during cryopreservation. However, frozen semen remains advantageous in terms of storage and transport for wider-scale implementation.

Farmer feedback indicated that estrus synchronization helped reduce breeding season limitations and allowed for batch kidding, which facilitated better management of feed, health, and market planning. Training programs conducted before the trials improved farmer understanding of AI benefits, timing, and animal handling.

Some limitations observed included the cost of synchronization hormones, the need for trained personnel for AI, and varying responses to hormonal treatments based on breed and nutrition status. Nevertheless, integrating AI and synchronization into breeding programs showed substantial gains in reproductive efficiency.

Conclusion

The combination of estrus synchronization and artificial insemination significantly enhances reproductive performance in goats by allowing precise control of breeding and increasing conception rates. These technologies reduce breeding intervals, improve litter management, and accelerate genetic improvement within herds. While challenges such as hormone cost and technical skill requirements exist, their benefits in terms of productivity and herd uniformity outweigh these limitations, especially in organized or semi-intensive systems. Promoting these reproductive technologies through farmer training, government subsidies, and mobile AI services could transform goat farming into a more profitable and efficient enterprise. Future research should focus on breed-specific protocol optimization, long-term fertility tracking, and integration with genetic selection programs for sustainable small ruminant development.

References

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