Abstract
The Argentine Criollo Cattle (BCA) breed was predominant until the early 20th century. However, in the Salado Basin—Argentina’s main beef calf-producing region—it currently represents a minority population. The objective of this study was to analyze the productive lifespan (LVP) and stayability (S) of dams in a BCA herd within this region. A total of 196 dams that both began and completed their reproductive lives were evaluated. The average LVP was 93.85 months (range: 5.84–205.20), and the average total number of calves (NCT) per cow was 8.23 (range: 1–18). Cows with traditional mating (EPP36) outperformed those with early mating (EPP24), with an average advantage of 20.6 months in LVP and 1.67 more calves. Based on productivity, three groups of dams were identified: low (BP, n = 40), intermediate (IP, n = 52), and high (AP, n = 104). As productivity increased, the average kinship within each group decreased, suggesting greater genetic variability among the most productive cows. The logistic regression model for stayability (S) showed that an increase in age at first calving (EPP) was associated with a higher probability of a cow weaning at least seven calves lifelong, supporting the differences observed between EPP24 and EPP36 groups. More frequent use of the BCA breed could contribute to increasing average productivity in the extensive livestock systems of the Salado Basin.
References
Aliloo, H., & Clark, S. (2022). Estimation of variance components for female longevity in Australian Angus cattle using random regression models. Proceedings of the 12th World Congress on Genetics Applied to Livestock Production (WCGALP). https://doi.org/10.3920/978-90-8686-940-4_642
Barsky, O., & Gelman, J. (2009). Historia del agro argentino: Desde la Conquista hasta principios del siglo XXI. Editorial Sudamericana.
Bavera, G. (2011). Razas bovinas y bufalinas de la Argentina. Editorial Imberti-Bavera.
Beef Improvement Company. (2021). Stayability. https://guidelines.beefimprovement.org/index.php/Stayability
Brzáková, M., Svitáková, A., Čítek, J., Veselá, Z., & Vostrý, L. (2019). Genetic parameters of longevity for improving profitability of beef cattle. Journal of Animal Science, 97(1), 19–28. https://doi.org/10.1093/jas/sky390
Cauhepe, M. A., & Cafaro La Menza, N. (2014). Servicio precoz en vacunos en la Pampa Inundable y base científica de prácticas corrientes: Revisión bibliográfica. Revista Argentina de Producción Animal, 34, 23–31.
Coster, A. (2022). pedigree: Pedigree functions (Version 1.4.2) [R package]. https://CRAN.R-project.org/package=pedigree
Dákay, I., Márton, D., Bene, S., Kiss, B., Zsuppán, Z., & Szabó, F. (2006). The age at first calving and the longevity of beef cows in Hungary. Archiv für Tierzucht / Archives Animal Breeding, 49, 417–425. https://doi.org/10.5194/aab-49-417
Flores, A. J., Rochinotti, D., Hug, M. G., & Gómez, M. (2014). Factores que afectan la tasa de preñez de vaquillas de 15 meses de edad. En 37º Congreso de la Asociación Argentina de Producción Animal (RAPA), 34(Supl. 1), 21.
Hidalgo-Moreno, J. A., Núñez-Domínguez, R., Domínguez-Viveros, J., Ramírez-Valverde, R., & Rodríguez-Almeida, F. (2019). Asociación genética del índice de productividad anual con características reproductivas y de crecimiento en bovinos productores de carne. Agrociencia, 53(8), 1203–1220.
Holgado, F., Rabasa, A., & Ortega, M. F. (2021). El bovino Criollo Argentino: Principales características de la raza. Archivos Latinoamericanos de Producción Animal, 29, 101–112. http://www.doi.org/10.53588/alpa.293403
Hudson, G. F. S., & Van Vleck, L. D. (1981). Relations between production and stayability in Holstein cattle. Journal of Dairy Science, 64, 2246–2250.
Navure Team. (2023). Navure (Version 2.8.0): A data-science-statistic oriented application for making evidence-based decisions. http://www.navure.com
Martínez, R. D. (2008). Caracterización genética y morfológica del bovino criollo argentino de origen patagónico [Tesis doctoral, Universidad Politécnica de Valencia]. https://riunet.upv.es
Núñez-Domínguez, R., Ramírez-Valverde, R., Saavedra-Jiménez, L. A., & García-Muñiz, J. G. (2016). La adaptabilidad de los recursos zoogenéticos criollos, base para enfrentar los desafíos de la producción animal. Archivos de Zootecnia, 65(251), 461–468.
Queiroz, S. A., Figueiredo, G., Silva, J. A., Espasandin, A. C., Meirelles, S. L., & Oliveira, J. A. (2007). Estimativa de parâmetros genéticos da habilidade de permanência aos 48, 60 e 72 meses de idade em vacas da raça Caracu. Revista Brasileira de Zootecnia, 36, 1316–1323.
R Core Team. (2024). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
Rearte, D. (2011). Situación actual y prospectiva de la ganadería argentina, un enfoque regional. Asociación Latinoamericana de Producción Animal, 19, 46–49.
Secretaría de Bioeconomía. (2024). Resultados económicos ganaderos: Informe trimestral Nº 50. https://www.argentina.gob.ar/economia/bioeconomia
Sesto, C. (2003). El modelo de innovación tecnológica: El caso del refinamiento del vacuno en la provincia de Buenos Aires (1856–1900). Mundo Agrario, 4(7). http://www.mundoagrario.unlp.edu.ar/
Urcola, H. A., Burges, J. C., Gouarderes, L., & Solman, S. (2018). El cambio climático y la ganadería bovina: Una evaluación para el sudeste bonaerense, Argentina. Chilean Journal of Agricultural & Animal Sciences, 34(3), 254–265.
Viñoles, C., Giorello, D., Soares de Lima, J. M., & Montossi, F. (2015). Entore precoz: Una alternativa para aumentar la competitividad de la cría. En Productividad de pasturas estivales en la región Noreste (pp. 89–92). INIA.
West, B. T., Welch, K. B., & Galecki, A. T. (2007). *Linear mixed models: A practical guide using statistical software
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