THE META-ANALYSIS OF CERVICAL AND POST-CERVICAL ARTIFICIAL INSEMINATION OF SOWS

DOI: 10.32900/2312-8402-2025-133-93-107

Nataliia PLATONOVA,
Doctor of Agricultural Sciences,
https://orcid.org/0000-0003-2256-7932,
Institute of Pig Breeding and Agroindustrial Production of the NAAS, Poltava, Ukraine

Keywords: Sows artificial insemination, traditional cervical insemination (CAI), post-cervical artificial insemination (PCAI), meta-analysis, the farrowing rate, fecundity index, the litter size


The efficiency of artificial insemination (AI) in pig breeding plays a critical role in improving reproductive performance, reducing breeding costs, and increasing the sustainability of the pig farming industry. Unlike cervical insemination (CAI), PCAI allows for more precise sperm deposition in the uterus, improving the chances of conception and this ensures more effective intensive boar management.

To evaluate the effectiveness of PCAI in improving pig breeding efficiency, a meta-analysis was conducted using Jamovi software and algorithms from the metaphor package (R). Publication bias estimation was integrated into the analysis to ensure the reliability of the findings. The meta-analysis compared PCAI and CAI across three critical reproductive parameters: farrowing rate, fecundity index, and litter size. Criteria for study inclusion were defined to ensure the integrity of the analysis:  the exclusion of studies involving exogenous hormonal treatments that could interfere with natural reproductive processes, the inclusion of studies with at least 20 animals per group, availability of group sizes and insemination doses, and provision of relevant variation statistics.

A total of 34 studies were included in the analysis for the farrowing rate, 33 studies for the fecundity index, and 33 studies for the litter size. The inclusion of such a large number of studies enhanced the robustness of the meta-analysis and allowed for a comprehensive evaluation of PCAI’s impact on pig breeding efficiency.

The meta-analysis results showed that PCAI does not significantly worsen the farrowing rate. Specifically, the average log odds ratio based on the random-effects model was 0.0061 (95% CI: -0.2042 to 0.2163), indicating no detrimental effect on the farrowing rate when PCAI was used. Similarly, no significant differences were found between PCAI and CAI for the fecundity index (average standardized mean difference was 0.1156; 95% CI: -0.0790 to 0.3103), nor for litter size (average standardized mean difference was 0.0226; 95% CI: -0.0670 to 0.1123). These findings suggest that PCAI is comparable to traditional AI methods in terms of key reproductive parameters, which is a crucial consideration for breeders seeking to improve their production efficiency.

The publication showed that use of PCAI can offer several economic benefits. By increasing the efficiency of boars and making desirable genetics more accessible, PCAI reduces the need for maintaining a large number of boars on farms. This not only reduces the costs associated with keeping boars, but also promotes the wider use of high-quality genetic material, leading to the genetic improvement of industrial pigs.

 

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