Pregnancy detection methods in sows

Authors

DOI:

https://doi.org/10.15517/cg8fwh92

Keywords:

Sows, pregnancy detection, diagnosis, methods, porcine reproduction

Abstract

Reproductive efficiency in the swine industry depends largely on early and accurate pregnancy detection in sows. Over time, various methods for determining pregnancy status have been developed and refined, ranging from traditional techniques to cutting-edge technological tools. This review aims to provide a comprehensive and up-to-date overview of the main methods used for pregnancy detection in sows. Scientific databases such as PubMed, Scopus, Google Scholar, and Web of Science were consulted over a 10-year period. A total of 52 sources were selected based on thematic relevance, methodological quality, and applicability of results. These were organized using descriptive statistics along with a qualitative synthesis. Both conventional practices, such as behavioral observation, and modern technologies, including echography, hormonal analysis, and image processing techniques, were addressed. Return to estrus is considered a cost-effective method for pregnancy detection in sows, especially in small-scale production systems; however, it is limited by its longer detection intervals. In contrast, echography has improved diagnostic accuracy for confirming pregnancy status. Hormonal assays, which involve quantifying hormone levels in blood or urine samples, are less frequently employed due to their higher costs. Infrared thermography has been recently proposed as a potentially reliable tool for early pregnancy detection in sows. Although the selection of the method depends on a variety of factors, combining multiple approaches can be an effective strategy to improve the accuracy of pregnancy diagnosis and monitoring in sows.

Downloads

Download data is not yet available.

Author Biographies

  • Leonardo Andrés Molina-Cabrales, Universidad Francisco de Paula Santander Seccional Ocaña

    Professor and researcher at UFPSO Facultad de Ciencias Agrarias y del Ambiente, Universidad Francisco de Paula Santander Seccional Ocaña, Ocaña, Colombia.

  • Diego Enrique León-Chacón, Universidad Francisco de Paula Santander Seccional Ocaña

    Professor and researcher at UFPSO Facultad de Ciencias Agrarias y del Ambiente, Universidad Francisco de Paula Santander Seccional Ocaña, Ocaña, Colombia.

References

Almeida, F. C., & Alvarenga, A. N. (2022). Pregnancy in pigs: The journey of an early life. Domestic Animal Endocrinology, 78, 106656. https://doi.org/10.1016/j.domaniend.2021.106656

Almond, G. W. (2007). Diagnosis of pregnancy. En Current therapy in large animal theriogenology (pp. 773–778). Elsevier. https://doi.org/10.1016/B978-0-7216-9323-1.X5001-6

Astudillo, F. I. (2023). Viabilidad reproductiva en cerdas empleando inseminación artificial [Tesis de pregrado, Universidad Técnica de Babahoyo]. http://dspace.utb.edu.ec/handle/49000/13939

Balhara, A. K., Gupta, M., Singh, S., Mohanty, A. K., & Singh, I. (2013). Early pregnancy diagnosis in bovines: Current status and future directions. The Scientific World Journal, 2013, 958540. https://doi.org/10.1155/2013/958540

Bharti, M., & Jacob, N. (2019). Laboratory and imaging techniques for pregnancy. Journal of Entomology and Zoology Studies, 7(5), 639–647.

Chae, J. W., Choi, Y. H., Lee, J. N., Park, H. J., Jeong, Y. D., Cho, E. S., Kim, Y. S., Kim, T. K., Sa, S. J., & Cho, H. C. (2023). An intelligent method for pregnancy diagnosis in breeding sows according to ultrasonography algorithms. Journal of Animal Science and Technology, 65(2), 365–376. https://doi.org/10.5187/jast.2022.e107

Chang, H. J., Shin, H. S., Kim, T. H., Yoo, J. Y., Teasley, H. E., Zhao, J. J., Ha, U. H., & Jeong, J. W. (2018). PIK3CA is required for uterine gland development and pregnancy in mice. PLoS ONE, 13(1), e0191433. https://doi.org/10.1371/journal.pone.0191433

Cintra, M. F., García, L. P., Hernández, Y. S., & Pérez, M. S. (2006). Características reproductivas de la cerda: Influencia de algunos factores ambientales y nutricionales. REDVET, 7(1), 1–36.

Craig, J., & Jorquera-Chavez, M. (2024). Use of thermographic technology to detect reproductive state in sows and improve piglet performance in a commercial farrowing house. Rivalea. https://apri.com.au/wp-content/uploads/2024/06/6A-104-Final-Report.pdf

Giai, L. R., Williamson, D. M., Vélez, C., & Clauzure, M. (2022). Expresión de citoquinas durante la gestación porcina. Ciencia Veterinaria, 24(2). https://doi.org/10.19137/cienvet202224205

Gokuldas, P. P., Shinde, K. R., Naik, S., Sahu, A. R., Singh, S. K., & Chakukar, E. B. (2023). Assessment of diagnostic accuracy and effectiveness of trans-abdominal real-time ultrasound imaging for pregnancy diagnosis in breeding sows under intensive management. Tropical Animal Health and Production, 55(4), 239. https://doi.org/10.1007/s11250-023-03649-6

Groke, M., Feitosa Leal, D., Jorge Neto, P. N., & Cabral Viana, C. H. (2020). Application of real-time ultrasonography as a tool to increase reproductive efficiency of female pigs (Report No. 572). Brazilian Agricultural Research Corporation. https://doi.org/10.13140/RG.2.2.28411.54560

Gulliksen, S. M., Framstad, T., Kielland, C., et al. (2023). Infrared thermography as a possible technique for the estimation of parturition onset in sows. Porcine Health Management, 9, 3. https://doi.org/10.1186/s40813-022-00301-x

Hao, W., Han, W., Han, M., & Li, F. (2022). A novel improved YOLOv3-SC model for individual pig detection. Sensors, 22(22), 8792. https://doi.org/10.3390/s22228792

Hemanth, D. J., & Estrela, V. V. (2017). Deep learning for image processing applications. IOS Press.

Hinojosa, J. P. (2022). Diagnóstico apropiado del celo para una oportuna inseminación artificial en cerdas [Tesis de posgrado, Universidad Mayor de San Simón]. http://ddigital.umss.edu.bo/handle/123456789/34658

Kauffold, J., Peltoniemi, O., Wehrend, A., & Althouse, G. C. (2019). Principles and clinical uses of real-time ultrasonography in female swine reproduction. Animals, 9, 950. https://doi.org/10.3390/ani9110950

Kim, T.-K., Choi, Y.-H., Hong, J.-S., Park, H.-J., Kim, Y.-M., Kim, J.-E., Lee, J.-H., Sa, S.-J., Jeong,

Y.-D., Kim, J.-S., & Cho, H.-C. (2025). Deep learning-enhanced diagnosis of sow pregnancy through low-frequency ultrasound imaging. Animals, 15(3), 318. https://doi.org/10.3390/ani15030318

Knox, R. V. (2014). Impact of swine reproductive technologies on pig and global food production. En Advances in pork production. Springer. https://doi.org/10.1007/978-1-4614-8887-3_7

Knox, R. V. (2022). Breeding management of pigs. MSD Veterinary Manual. https://www.msdvetmanual.com

Knox, R. V., & Flowers, W. L. (2006). Using real-time ultrasound for pregnancy diagnosis in swine. North Carolina State University.

Koketsu, Y., Tani, S., & Iida, R. (2017). Factors for improving reproductive performance of sows. Porcine Health Management, 3(1). https://doi.org/10.1186/s40813-016-0049-7

Krueger, F., Knauf-Witzens, T., & Getto, S. (2019). New approach in thermal pregnancy diagnosis: Teat heating in babirusa. Theriogenology, 133, 144–148. https://doi.org/10.1016/j.theriogenology.2019.04.030

Liu, X., Schwarz, T., Murawski, M., Tayade, C., Kridli, R., Prieto Granados, A. M., Sharma, C., & Bartlewski, P. M. (2020). Progesterone and estrone sulfate levels as diagnostic/prognostic tools in porcine pregnancy. Domestic Animal Endocrinology, 71, 106402. https://doi.org/10.1016/j.domaniend.2019.106402

Luño, V., Gil, L., Olaciregui, M., Grandía, J., Ansó, T., & De Blas, I. (2015). Fertilisation rate with frozen-thawed boar semen with rosmarinic acid. Acta Veterinaria Hungarica, 63(1), 100–109.

Mellagi, A. P. G., Bernardi, M. L., Wentz, I., & Bortolozzo, F. P. (2015). Strategies to improve reproductive performance in gilts. Reproduction in Domestic Animals, 50(Suppl. 2), 9–15.

Miretti, S., Lecchi, C., Ceciliani, F., & Baratta, M. (2020). MicroRNAs as biomarkers for animal health and welfare in livestock. Frontiers in Veterinary Science, 7, 578193. https://doi.org/10.3389/fvets.2020.578193

Purohit, G. (2010). Methods of pregnancy diagnosis in domestic animals. WebmedCentral, 1(12). https://doi.org/10.9754/journal.wmc.2010.001305

Riaz, U., Idris, M., Ahmed, M., Ali, F., & Yang, L. (2023). Infrared thermography as a potential non-invasive tool for estrus detection in cattle and buffaloes. Animals, 13(8), 1425. https://doi.org/10.3390/ani13081425

Vélez, C. L. (2017). Integrinas y su regulación durante la gestación porcina [Tesis doctoral, Universidad Nacional de La Plata].

Willard, N. C. (2024). Sow body temperature and behavioral changes associated with the onset of estrus and ovulation [Tesis doctoral, University of Illinois at Urbana-Champaign]. https://www.ideals.illinois.edu/items/134274

Zhou, C., Cai, G., Meng, F., Hu, Q., Liang, G., Gu, T., Zheng, E., Li, Z., Wu, Z., & Hong, L. (2022). Urinary metabolomics in early pregnancy in pigs. Porcine Health Management, 8, 14.

Published

2025-12-23