EDUCAÇÃO E CAPACITAÇÃO DE PRODUTORES PARA O MELHORAMENTO GENÉTICO ANIMAL
DOI:
https://doi.org/10.63330/aurumpub.075-003Palabras clave:
Avaliação genética, Dados zootécnicos, SeleçãoResumen
A educação e a capacitação de produtores constituem estratégias fundamentais para ampliar a aplicação do melhoramento genético animal nos sistemas de produção. Trata-se de uma revisão bibliográfica de caráter didático, que reúne conceitos e exemplos práticos voltados à capacitação de produtores. O conhecimento dos fundamentos do melhoramento permite compreender os princípios da seleção e o uso adequado das informações genéticas. Nesse processo, a realização de registros zootécnicos e a qualidade dos dados assumem papel essencial, pois fornecem informações confiáveis para as avaliações e para a tomada de decisões. Além disso, a capacitação favorece a interpretação dos resultados das avaliações genéticas e sua aplicação na escolha de animais, acasalamentos e estratégias de seleção. Dessa forma, ações educativas e de capacitação podem aproximar o conhecimento técnico da realidade dos produtores, contribuindo para o uso mais eficiente das ferramentas de melhoramento genético animal dentro dos rebanhos.
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Referencias
BALDIN, M. et al. Standardization for data generation and collection in the dairy industry: addressing challenges and charting a path forward. Animals, v. 15, n. 2, art. 250, 2025. DOI: 10.3390/ani15020250.
BARWICK, S. A. et al. Estimation of accuracies and expected genetic change from selection for selection indexes that use multiple-trait predictions of breeding values. Journal of Animal Breeding and Genetics, 2013. DOI: 10.1111/jbg.12011.
BASIR, M. S. et al. From pen and paper to digital precision: a comprehensive review of on-farm recordkeeping. Precision Agriculture, v. 25, p. 2643-2682, 2024. DOI: 10.1007/s11119-024-10172-7.
BERRY, D. P. et al. Genetics of animal health and disease in cattle. Irish Veterinary Journal, v. 64, n. 1, art. 5, 2011. DOI: 10.1186/2046-0481-64-5.
BIJMA, P. The Price equation as a bridge between animal breeding and evolutionary biology. Philosophical Transactions of the Royal Society B: Biological Sciences, v. 375, n. 1797, art. 20190360, 2020. DOI: 10.1098/rstb.2019.0360.
BOURDON, R. M. Understanding animal breeding. 2. ed. Upper Saddle River: Prentice Hall, 2000.
BOYLES, S. Expected progeny differences and their accuracy. Ohio BEEF Cattle Letter. Columbus: Ohio State University Extension, 2021. Disponível em: https://u.osu.edu/beef/?p=11555. Acesso em: 15 out. 2026.
BRITO, L. F. et al. Review: Genetic selection of high-yielding dairy cattle toward sustainable farming systems in a rapidly changing world. Animal, v. 15, supl. 1, art. 100292, 2021. DOI: 10.1016/j.animal.2021.100292.
COLE, J. B. Are there too many traits in our selection indices? Journal of Dairy Science, v. 108, n. 11, p. 12483-12505, 2025. DOI: 10.3168/jds.2024-25833.
COLE, J. B.; DÜRR, J. W.; NICOLAZZI, E. L. Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides? Journal of Dairy Science, v. 104, n. 5, p. 5111-5124, 2021. DOI: 10.3168/jds.2020-19777.
FATHONI, A. et al. An appropriate genetic approach for improving reproductive traits in crossbred Thai–Holstein cattle under heat stress conditions. Veterinary Sciences, v. 9, n. 4, art. 163, 2022. DOI: 10.3390/vetsci9040163.
FERNANDES JÚNIOR, G. A. et al. Current applications and perspectives of genomic selection in Bos indicus (Nellore) cattle. Livestock Science, v. 263, art. 105001, 2022. DOI: 10.1016/j.livsci.2022.105001.
GICHOHI, P. M. The role of record keeping and maintenance in enhancing decision making among smallholder dairy farmers in Gitugi Ward in Murang'a County, Kenya. Information Development, v. 36, n. 4, p. 535-545, 2020.
HAILE, A. et al. How to succeed in implementing community-based breeding programs: lessons from the field in Eastern and Southern Africa. Frontiers in Genetics, v. 14, art. 1119024, 2023. DOI: 10.3389/fgene.2023.1119024.
HATEW, B. et al. Synergies of feed, management trainings, and genetics on milk production of dairy cows in the tropics: the case of Ethiopian smallholder farmers. Frontiers in Animal Science, v. 4, art. 1119786, 2023. DOI: 10.3389/fanim.2023.1119786.
HUSIEN, H. M. et al. The evolution and role of molecular tools in measuring diversity and genomic selection in livestock populations (traditional and up-to-date insights): a comprehensive exploration. Veterinary Sciences, v. 11, n. 12, art. 627, 2024. DOI: 10.3390/vetsci11120627.
JOURDAN-PINEAU, H. et al. Estimating heritability in honeybees: comparison of three major methods based on empirical and simulated datasets. Ecology and Evolution, v. 11, n. 13, 2021. DOI: 10.1002/ece3.7389.
LEE, J.; JUNG, J. H.; OH, S.-H. Enhancing animal breeding through quality control in genomic data – a review. Journal of Animal Science and Technology, v. 66, n. 6, p. 1099-1108, 2024. DOI: 10.5187/jast.2024.e92.
MARTÍN, N. et al. Estimated breeding values of beef sires can predict performance of beef-cross-dairy progeny. Frontiers in Genetics, v. 12, art. 712715, 2021. DOI: 10.3389/fgene.2021.712715.
MARTIN-COLLADO, D. et al. Measuring farmers' attitude towards breeding tools: the Livestock Breeding Attitude Scale. Animal, v. 15, n. 2, art. 100062, 2021. DOI: 10.1016/j.animal.2020.100062.
MENCHON, P. et al. Exploration of extension research to promote genetic improvement in cattle production: systematic review. Animals, v. 14, n. 2, art. 231, 2024. DOI: 10.3390/ani14020231.
MÉSZÁROS, G. et al. Framework for assessing genetic variation in livestock using demographic, pedigree, and genomic measures. Frontiers in Genetics, v. 17, art. 1792347, 2026. DOI: 10.3389/fgene.2026.1792347.
MISZTAL, I.; LOURENCO, D.; LEGARRA, A. Current status of genomic evaluation. Journal of Animal Science, v. 98, n. 4, p. 1-14, 2020. DOI: 10.1093/jas/skaa101.
MWANGA, G. et al. How information communication technology can enhance evidence-based decisions and farm-to-fork animal traceability for livestock farmers. The Scientific World Journal, v. 2020, art. 1279569, 2020. DOI: 10.1155/2020/1279569.
PÉRTILE, S. F. N. et al. Seleção e associação genômica ampla para o melhoramento genético animal com uso do método ssGBLUP. Pesquisa Agropecuária Brasileira, Brasília, v. 51, n. 10, p. 1729-1736, out. 2016. DOI: 10.1590/S0100-204X2016001000004.
PIMENTEL, E. C. G. et al. How pedigree errors affect genetic evaluations and validation statistics. Journal of Dairy Science, v. 107, n. 6, p. 3716-3723, 2024. DOI: 10.3168/jds.2023-24070.
RESTI, Y. et al. A review of on-farm recording tools for smallholder dairy farming in developing countries. Tropical Animal Health and Production, v. 56, n. 5, art. 168, 2024. DOI: 10.1007/s11250-024-04024-9.
ROMERO-ZÚÑIGA, J. J. et al. Productive and reproductive record keeping in low-to-middle-income tropical livestock systems: challenges and perspectives. Animals, v. 16, n. 11, art. 1691, 2026. DOI: 10.3390/ani16111691.
SCHULTZ, B.; SERÃO, N. V. L.; ROSS, J. W. Genetic improvement of livestock, from conventional breeding to biotechnological approaches. In: BAZER, F. W.; LAMB, G. C.; WU, G. (ed.). Animal agriculture: sustainability, challenges and innovations. [S. l.]: Academic Press, 2020. p. 393-405. DOI: 10.1016/B978-0-12-817052-6.00023-9.
SCHULZ, P. et al. Exploring the role of smartphone apps for livestock farmers: data management, extension and informed decision making. The Journal of Agricultural Education and Extension, v. 28, n. 1, p. 93-114, 2022. DOI: 10.1080/1389224X.2021.1910524.
TADE, B.; MELESSE, A. A review on the application of genomic selection in the improvement of dairy cattle productivity. Ecological Genetics and Genomics, v. 31, art. 100257, 2024. DOI: 10.1016/j.egg.2024.100257.
TOGHIANI, S. Quantitative genetic application in the selection process for livestock production. In: JAVED, K. (ed.). Livestock production. Rijeka: InTech, 2012. p. 3-32. DOI: 10.5772/51027.
ULE, A.; ERJAVEC, K.; KLOPČIČ, M. Influence of dairy farmers' knowledge on their attitudes towards breeding tools and genomic selection. Animal, v. 17, n. 6, art. 100852, 2023. DOI: 10.1016/j.animal.2023.100852.
ULLAH, K.; WAHEED, A. Review: genetic improvement in livestock: a journey from conventional breeding to genomic precision. Veterinary Biomedical and Clinical Journal, v. 7, n. 1, p. 30-44, 2025. DOI: 10.21776/ub.VetBioClinJ.2025.007.01.3.
VAN EENENNAAM, A. L. Current and future uses of genetic improvement technologies in livestock breeding programs. Animal Frontiers, v. 15, n. 1, p. 80-90, 2025. DOI: 10.1093/af/vfae042.
VAN TASSELL, C. P. et al. The African Goat Improvement Network: a scientific group empowering smallholder farmers. Frontiers in Genetics, v. 14, art. 1183240, 2023. DOI: 10.3389/fgene.2023.1183240.
WANGEN, S. R. et al. Improving farm decisions: the application of data engineering techniques to manage data streams from contemporary dairy operations. Livestock Science, v. 250, art. 104602, 2021. DOI: 10.1016/j.livsci.2021.104602.
WELLMANN, R. Selection index theory for populations under directional and stabilizing selection. Genetics Selection Evolution, v. 55, n. 1, art. 10, 2023. DOI: 10.1186/s12711-023-00776-4.
WU, X.-L. et al. Handling errors in the response: considerations for leveraging unsupervised or incomplete data for genetic evaluations. JDS Communications, v. 6, n. 5, p. 675-680, 2025. DOI: 10.3168/jdsc.2024-0668.
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Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
