Dinámica de crecimiento y categorización funcional del ganado lechero mediante monitoreo electrónico

Autores/as

DOI:

https://doi.org/10.61347/ei.v5i1.230

Palabras clave:

Categorización funcional, ganadería de precisión, ganado lechero, peso corporal

Resumen

La ganadería lechera requiere herramientas de monitoreo que permitan optimizar la eficiencia productiva y la toma de decisiones en los sistemas de producción animal. El objetivo de este estudio fue evaluar la dinámica de crecimiento y la categorización funcional del ganado lechero mediante el uso de monitoreo electrónico del peso corporal. La investigación se desarrolló durante 12 meses en un hato lechero, donde se evaluaron 42 bovinos mediante una báscula electrónica Tru-Test ezyweigh7, clasificándolos en categorías funcionales: vacas en producción, vacas secas, vaconas, fierros y terneras. Los datos obtenidos se analizaron mediante estadística descriptiva y análisis de varianza (ANOVA) para comparar las medias de peso entre categorías, considerando un nivel de significancia de P < 0,05. Los resultados mostraron que el 93 % de los animales presentó una ganancia progresiva de peso corporal, mientras que el 7 % evidenció disminuciones asociadas a periodos de estrés fisiológico periparto. La estructura funcional del hato estuvo conformada mayoritariamente por vacas en producción (64,29 %), seguidas por vacas secas (35,71 %). Se concluye que el monitoreo electrónico del peso corporal constituye una herramienta eficaz para la gestión zootécnica y la ganadería de precisión, al permitir el seguimiento objetivo del crecimiento y la optimización de la estructura funcional del hato lechero.

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Citas

Andrade, G., Andrade, M., Suárez-Usbek, A., Bautista-Espinoza, H., & Haro-Haro, A. (2023). Impacto socioeconómico de la ganadería lechera en comunidades indígenas del ecuador. EASI: Engineering and Applied Sciences in Industry, 2(1), 34–43. https://doi.org/10.53591/easi.v2i1.1907

Banda, L. J., Chiumia, D., Gondwe, T. N., & Gondwe, S. R. (2021). Smallholder dairy farming contributes to household resilience, food, and nutrition security besides income in rural households. Animal Frontiers, 11(2), 41–46. https://doi.org/10.1093/af/vfab009

Berry, D. P., & Evans, R. D. (2025). When is too small, too small? Evaluating the trade-offs of smaller dairy cows in pasture-based systems. JDS Communications. https://doi.org/10.3168/jdsc.2025-0935

Breda, J. C. dos S., Facury Filho, E. J., Flaiban, K. K. da C., & Lisboa, J. A. N. (2023). Effect of Parity, Body Condition Score at Calving, and Milk Yield on the Metabolic Profile of Gyr Cows in the Transition Period. Animals : An Open Access Journal from MDPI, 13(15), 2509. https://doi.org/10.3390/ani13152509

Du, A., Guo, H., Lu, J., Su, Y., Ma, Q., Ruchay, A., Marinello, F., & Pezzuolo, A. (2022). Automatic livestock body measurement based on keypoint detection with multiple depth cameras. Computers and Electronics in Agriculture, 198, 107059. https://doi.org/10.1016/j.compag.2022.107059

Durana, C., Murgueitio, E., & Murgueitio, B. (2023). Sustainability of dairy farming in Colombia’s High Andean region. Frontiers in Sustainable Food Systems, 7. https://doi.org/10.3389/fsufs.2023.1223184

Fiorillo, V., Amico, B. M., Fiorillo, V., & Amico, B. M. (2024). Milk Quality and Economic Sustainability in Dairy Farming: A Systematic Review of Performance Indicators. Dairy, 5(3), 384–402. https://doi.org/10.3390/dairy5030031

Han, Y., Si, Y., He, Z., Li, Q., Li, Z., Zhang, M., & Liu, G. (2025). Dynamic weighing system for dairy cows based on arrayed weighing platforms. Computers and Electronics in Agriculture, 230, 109943. https://doi.org/10.1016/j.compag.2025.109943

Hasan, F. M., Thomson, P. C., Islam, M. R., Clark, C. E. F., Chlingaryan, A., & Lomax, S. (2024). Monitoring cattle liveweight using a mobile, in-paddock weigh platform: Validation, attendance and utility. Smart Agricultural Technology, 9, 100639. https://doi.org/10.1016/j.atech.2024.100639

Jeon, E., Cho, S., Hwang, S., Cho, K., Gondro, C., & Choi, N.-J. (2024). Development of prediction model for body weight and energy balance indicators from milk traits in lactating dairy cows based on deep neural networks. Journal of King Saud University – Science, 36. https://doi.org/10.1016/j.jksus.2023.103008

Jiang, B., Tang, W., Cui, L., Deng, X., Jiang, B., Tang, W., Cui, L., & Deng, X. (2023). Precision Livestock Farming Research: A Global Scientometric Review. Animals, 13(13). https://doi.org/10.3390/ani13132096

Kim, D.-H., Song, J.-W., Cho, H., Lee, M., Lee, D.-H., Seo, S., Lee, W.-H., Kim, D.-H., Song, J.-W., Cho, H., Lee, M., Lee, D.-H., Seo, S., & Lee, W.-H. (2025). Multi-Stage Data Processing for Enhancing Korean Cattle (Hanwoo) Weight Estimations by Automated Weighing Systems. Animals, 15(12). https://doi.org/10.3390/ani15121785

Kırbaş, İ. (2026). AI-based automated weight prediction in cattle for herd health surveillance. Preventive Veterinary Medicine, 247, 106752. https://doi.org/10.1016/j.prevetmed.2025.106752

Li, M., Reed, K. F., Lauber, M. R., Fricke, P. M., & Cabrera, V. E. (2023). A stochastic animal life cycle simulation model for a whole dairy farm system model: Assessing the value of combined heifer and lactating dairy cow reproductive management programs. Journal of Dairy Science, 106(5), 3246–3267. https://doi.org/10.3168/jds.2022-22396

Liu, Y. F., Xiao, D. Q., Ni, X., & Li, W. G. (2024). Estimating yolk weight of duck eggs using VIS-NIR Spectroscopy and RGB images and whole egg weights. Poultry Science, 103(7), 103829. https://doi.org/10.1016/j.psj.2024.103829

Mahato, S., & Neethirajan, S. (2025). Integrating Artificial Intelligence in dairy farm management − biometric facial recognition for cows. Information Processing in Agriculture, 12(3), 312–325. https://doi.org/10.1016/j.inpa.2024.10.001

Mengyuan C., Yongsheng S., Qian L., & Gang L. (2022). Research advances in the automatic measurement technology for livestock body size. Transactions of the Chinese Society of Agricultural Engineering, 38(13), 228–240. https://doi.org/10.11975/j.issn.1002-6819.2022.13.026

Ojo, A. O., Mulim, H. A., Campos, G. S., Junqueira, V. S., Lemenager, R. P., Schoonmaker, J. P., Oliveira, H. R., Ojo, A. O., Mulim, H. A., Campos, G. S., Junqueira, V. S., Lemenager, R. P., Schoonmaker, J. P., & Oliveira, H. R. (2024). Exploring Feed Efficiency in Beef Cattle: From Data Collection to Genetic and Nutritional Modeling. Animals, 14(24). https://doi.org/10.3390/ani14243633

Oliveira, F. M. de, Ferraz, G. A. e S., André, A. L. G., Santana, L. S., Norton, T., Ferraz, P. F. P., Oliveira, F. M. de, Ferraz, G. A. e S., André, A. L. G., Santana, L. S., Norton, T., & Ferraz, P. F. P. (2024). Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis. Animals, 14(12). https://doi.org/10.3390/ani14121832

Papadopoulos, G., Papantonatou, M.-Z., Uyar, H., Kriezi, O., Mavrommatis, A., Psiroukis, V., Kasimati, A., Tsiplakou, E., & Fountas, S. (2025). Economic and environmental benefits of digital agricultural technological solutions in livestock farming: A review. Smart Agricultural Technology, 10, 100783. https://doi.org/10.1016/j.atech.2025.100783

Peiter, M., Caixeta, L., & Endres, M. I. (2023). Association between change in body weight during early lactation and milk production in automatic milking system herds. JDS Communications, 4(5), 369–372. https://doi.org/10.3168/jdsc.2022-0323

Rosa, D. R. da, Ferreira, N. C. R., Oliveira, C. E. A., Moreira, A. N. H., Battisti, R., Casaroli, D., Barbari, M., Bambi, G., Andrade, R. R., Rosa, D. R. da, Ferreira, N. C. R., Oliveira, C. E. A., Moreira, A. N. H., Battisti, R., Casaroli, D., Barbari, M., Bambi, G., & Andrade, R. R. (2025). Climate Change and State of the Art of the Sustainable Dairy Farming: A Systematic Review. Animals, 15(20). https://doi.org/10.3390/ani15202997

Sharpe, K. T., & Heins, B. J. (2023). Evaluation of a Forefront Weight Scale from an Automated Calf Milk Feeder for Holstein and Crossbred Dairy and Dairy–Beef Calves. Animals : An Open Access Journal from MDPI, 13(11), 1752. https://doi.org/10.3390/ani13111752

Si, Q. (2024). Advancements in Precision Livestock Farming: Technologies and Applications. Animal Molecular Breeding, 14(0). https://animalscipublisher.com/index.php/amb/article/view/3816

Tadele, E., Worku, D., Yigzaw, D., Muluneh, T., & Melese, A. (2025). Precision of dairy farming: Navigating challenges and seizing opportunities for sustainable dairy production in Africa. Frontiers in Animal Science, 6. https://doi.org/10.3389/fanim.2025.1541838

Vlaicu, P. A., Gras, M. A., Untea, A. E., Lefter, N. A., Rotar, M. C., Vlaicu, P. A., Gras, M. A., Untea, A. E., Lefter, N. A., & Rotar, M. C. (2024). Advancing Livestock Technology: Intelligent Systemization for Enhanced Productivity, Welfare, and Sustainability. AgriEngineering, 6(2), 1479–1496. https://doi.org/10.3390/agriengineering6020084

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Publicado

2026-01-05

Cómo citar

Balarezo Urresta, L. R., Benavides Rosales, H. R., & Mora Quilismal, S. R. (2026). Dinámica de crecimiento y categorización funcional del ganado lechero mediante monitoreo electrónico. Esprint Investigación, 5(1), 8–15. https://doi.org/10.61347/ei.v5i1.230