{
    "abstract": "Timed artificial insemination (TAI) is a technology widely used in cattle production based on controlling ovarian follicular growth. This study analyzed a large database aiming to determine the influence of several intrinsic and extrinsic female factors, as well as their interactions to determine risk factors and produce prediction ability in beef cattle. A total of 1\u00a0832\u00a0999 TAIs conducted on 2\u00a0002 farms across South American countries were considered for the analysis, including 15 main fixed effects or interactions in the statistical model, in addition to five random effects. The pregnancy/A.I. (P/AI) was affected by Order of service (1st TAI\u00a0>\u00a0resynchronizations), body condition class (BCS) (high\u00a0>\u00a0medium\u00a0>\u00a0low), female genetic group [Bos taurus and crossbreds\u00a0>\u00a0Bos indicus], breeding season (reduction of the P/AI every year), female category [Non-lactating multiparous\u00a0>\u00a0Suckled multiparous\u00a0>\u00a0Suckled primiparous\u00a0>\u00a0Nulliparous heifers], period of year (July-September, October-December and January-March\u00a0>\u00a0April-June) and climatic region as well as the interactions between Order of service and female category, BCS class and female genetic group (impact of BCS: Bos taurus or crossbreed animals\u00a0>\u00a0Bos indicus), BCS and female category (impact of BC:S Suckling\u00a0>\u00a0non-Suckling categories), female category and time of female availability, female category and female genetic group, female category and climatic region, and climatic region and period of the year. Farm, technician, and sire were the variables with the highest predictive ability for P/AI. At the same time, breeding season, climatic region, and time of female availability were the variables with the lowest predictive ability. In conclusion, the main female intrinsic factors that affected fertility in commercial beef cattle A.I. programs were the Order of service, BCS class, female category, and female genetic group. The female extrinsic factors that most affected P/AI were the breeding season and the climatic region. Farm, A.I. technician, sire, and the interaction between the female category and BCS class were the variables with the highest predictive abilities on pregnancy per TAI. Conjunctural factors, which are more adjustable, have a higher impact on P/AI prediction ability than structural factors. Thus, farm management and structure, A.I. technician, bull semen, and female BCS should be the main factors of attention to obtain good results in applying this biotechnology in beef cattle. Despite the influence of each factor, this study demonstrated the usefulness of analyzing big databases, allowing to determine effects that cannot be studied with experimental approaches, providing a complementary approach to decide where to focus future studies to enhance TAI pregnancy rates in beef cattle.",
    "authors": [
        {
            "affiliation": "Universidade de S\u00e3o Paulo- Faculdade de Zootecnia e Engenheira dos Alimentos, Departamento de Medicina Veterin\u00e1ria, Pirassununga 13635-900, Brasil.",
            "firstname": "R E F",
            "initials": "REF",
            "lastname": "Assis"
        },
        {
            "affiliation": "Universidade Estadual Paulista - Faculdade de Ci\u00eancias Agrarias e Veterin\u00e1rias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brasil.",
            "firstname": "F",
            "initials": "F",
            "lastname": "Baldi"
        },
        {
            "affiliation": "Universidade Estadual Paulista - Faculdade de Ci\u00eancias Agrarias e Veterin\u00e1rias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brasil.",
            "firstname": "L B",
            "initials": "LB",
            "lastname": "Temp"
        },
        {
            "affiliation": "Departamento de Biociencias Veterinarias, Facultad de Veterinaria, Universidad de la Rep\u00fablica, Montevideo 13000, Uruguay. Electronic address: rungerfeld@gmail.com.",
            "firstname": "R",
            "initials": "R",
            "lastname": "Ungerfeld"
        },
        {
            "affiliation": "Alta Genetics Brasil Ltda., Uberaba 38055-010, Brazil.",
            "firstname": "M F",
            "initials": "MF",
            "lastname": "de S\u00e1 Filho"
        }
    ],
    "conclusions": null,
    "copyrights": "Copyright \u00a9 2025 The Authors. Published by Elsevier B.V. All rights reserved.",
    "doi": "10.1016/j.animal.2024.101410",
    "journal": "Animal : an international journal of animal bioscience",
    "keywords": [
        "Bovine",
        "Conception",
        "Cow-calf",
        "Pregnancy outcome",
        "Reproduction"
    ],
    "methods": null,
    "publication_date": "2025-01-26",
    "pubmed_id": "39862568",
    "results": null,
    "title": "Determinants of fertility in timed artificial insemination programs in beef cattle: predictive ability and risk factors from almost 2 million data points.",
    "xml": "<Element 'PubmedArticle' at 0x7885062e7150>"
}