Pregnancy detection methods in sows
DOI:
https://doi.org/10.15517/cg8fwh92Keywords:
Sows, pregnancy detection, diagnosis, methods, porcine reproductionAbstract
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.
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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.
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