International Journal of Animal Biotechnology and Applications Review Article

Adoption Barriers to Advanced Reproductive Technologies in the Subsistence Dairy Farming Systems: Key Constraints and the Way Forward

  1. Md. Emran Hossain Department of Animal Science and Nutrition, Chattogram Veterinary and Animal Sciences University, Khulshi, Chattogram-4225

Abstract

The adoption of advanced reproductive technologies (ARTs) in subsistence dairy farming remains limited despite their potential to enhance genetic improvement, fertility rates, and overall productivity. This study explores the key constraints hindering the integration of ARTs, including artificial insemination, embryo transfer, and ovulation synchronization, within small-scale dairy production systems. Financial constraints, lack of awareness, inadequate veterinary support, and socio-cultural resistance are identified as primary barriers. Limited access to affordable credit, high costs of reproductive inputs, and weak market linkages discourage investment in ARTs. Additionally, infrastructural deficiencies such as inadequate cold storage for semen preservation, unreliable veterinary services, and poor transportation networks further impede adoption. Socio-cultural beliefs and traditional breeding preferences often deter farmers from embracing modern reproductive practices, while policy gaps, weak institutional support, and insufficient farmer training exacerbate the challenges. Environmental factors, including heat stress and seasonal variations, further influence reproductive efficiency in dairy cattle. Addressing these constraints requires a multifaceted approach, including financial incentives, capacity-building programs, strengthened veterinary extension services, and the development of localized, low-cost reproductive technologies. The study underscores the need for integrated policies and stakeholder collaboration to facilitate ART adoption, thereby improving the sustainability and productivity of subsistence dairy farming systems.

Keywords

References (82)

  1. Lamanna M, Bovo M, Cavallini D. Wearable Collar Technologies for Dairy Cows: A Systematized Review of the Current Applications and Future Innovations in Precision Livestock Farming. Animals. 2025;15(3):458. doi:10.3390/ani15030458
  2. Tadele E, Worku D, Yigzaw D, Muluneh T, Melese A. Precision of dairy farming: navigating challenges and seizing opportunities for sustainable dairy production in Africa. Frontiers in Animal Science. 2025;6. doi:10.3389/fanim.2025.1541838
  3. P. Seth, B. Chandran, B. Mittra, and P. Pingali, “Understanding the Determinants of Farmers’ Adoption of Artificial Insemination in Livestock A Systematic Review,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Payal-Seth/publication/389069912_Understanding_the_Determinants_of_Farmers’_Adoption_of_Artificial_Insemination_in_Livestock_A_Systematic_Review/links/67b40ad196e7fb48b9c5bd6c/Understanding-the-Determinants-of-Farmers-Adoption-of-Artificial-Insemination-in-Livestock-A-Systematic-Review.pdf
  4. Lopez-Helguera I, Colazo MG, Kastelic JP. Artificial Insemination in Cows. Encyclopedia of Livestock Medicine for Large Animal and Poultry Production. 2025:1-4. doi:10.1007/978-3-031-52133-1_8-1
  5. C. Mazzocchi, L. Zanchi, L. Orsi, and ..., “Should I stay or should I go? Tie stalls or loose housing to improve dairy cow welfare,” Ital. Rev. …, 2025, [Online]. Available: https://oajournals.fupress.net/index.php/rea/article/view/15296
  6. M. W. Brunt, C. Ritter, D. L. Renaud, S. J. LeBlanc, and ..., “Dairy producers’ awareness, perceptions, and barriers to early detection and treatment of lameness on dairy farms: A qualitative focus group study,” 2025, Elsevier. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0022030225002152
  7. Hufana-Duran D, Chaikhun-Marcou T, Duran PG, Atabay EP, Nguyen HT, Atabay EC, et al. Future of reproductive biotechnologies in water buffalo in Southeast Asian countries. Theriogenology. 2025;233:123-130. doi:10.1016/j.theriogenology.2024.11.016
  8. Y. P. Singh, J. Jaiswal, and Y. Dwivedi, “In-vitro Fertilization: Revolutionizing Livestock Breeding Efficiency,” 2025, journalspub.com. [Online]. Available: https://journalspub.com/wp-content/uploads/2025/03/1-5-Article-In-vitro-Fertilization-Revolutionizing.pdf
  9. A. S. NECULAI-VALEANU and ..., “PRECISION LIVESTOCK FARMING AND ITS ROLE FOR ASSURING A SUSTAINABLE CATTLE MANAGEMENT-A STUDY CASE ON CONNECTED COW.,” … Agric. …, 2025, [Online]. Available: https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=22847995&AN=184543058&h=RVOEcFvVOfLzl58A%2Fu%2BU6Q03WHDue%2Bt6A0s5MZ6ydSoppVqRiSgcWYxCZkeLBuPZa4kzJiGU01grF8HbIL2c6g%3D%3D&crl=c
  10. A. Kumar and S. Dwivedi, “Reproductive Biotechnology in Livestock Improvement,” 2025, vigyanvarta.in. [Online]. Available: https://www.vigyanvarta.in/adminpanel/upload_doc/VV_0325_81.pdf
  11. The Nature Conservancy – Sustainable Production Systems Program, Solarte A, Rico A, Centro para la Investigación en Sistemas Sostenibles de Producción Agropecuaria – CIPAV, Zapata C, Chará J, et al. Barriers and strategies for scaling up livestock agroforestry systems in the amazon piedmont, Caquetá - Colombia. Revista Colombiana de Ciencias Pecuarias. 2025;38(1). doi:10.17533/udea.rccp.v38n1a5
  12. Cabrera VE. Artificial intelligence applied to dairy science: insights from the Dairy Brain Initiative. Animal Frontiers. 2024;14(6):60-63. doi:10.1093/af/vfae040
  13. Tangorra FM, Buoio E, Calcante A, Bassi A, Costa A. Internet of Things (IoT): Sensors Application in Dairy Cattle Farming. Animals. 2024;14(21):3071. doi:10.3390/ani14213071
  14. Menchon P, Manning JK, Swain DL, Cosby A. Exploration of Extension Research to Promote Genetic Improvement in Cattle Production: Systematic Review. Animals. 2024;14(2):231. doi:10.3390/ani14020231
  15. Kaewbang J, Lohanawakul J, Ketnuam N, Prapakornmano K, Khamta P, Raza A, et al. Smart sensors in Thai dairy reproduction: A case study. Veterinary World. 2024:1251-1258. doi:10.14202/vetworld.2024.1251-1258
  16. Ule A, Erjavec K, Klopčič M. Farmers' preferences for breeding goal traits and selection indexes for Slovenian dairy cattle. Journal of Dairy Science. 2024;107(1):412-422. doi:10.3168/jds.2022-23202
  17. S. E. Elliott, L. M., Parcell, J. L., Patterson, D. J., Smith, M. F., & Poock, “Factors Influencing Beef Reproductive Technology Adoption.,” J. ASFMRA, pp. 100–119, 2013, [Online]. Available: http://www.jstor.org/stable/jasfmra.2013.100
  18. Drewry JL, Shutske JM, Trechter D, Luck BD, Pitman L. Assessment of digital technology adoption and access barriers among crop, dairy and livestock producers in Wisconsin. Computers and Electronics in Agriculture. 2019;165:104960. doi:10.1016/j.compag.2019.104960
  19. Reyes DC, Meredith J, Puro L, Berry K, Kersbergen R, Soder KJ, et al. Maine organic dairy producers’ receptiveness to seaweed supplementation and effect of Chondrus crispus on enteric methane emissions in lactating cows. Frontiers in Veterinary Science. 2023;10. doi:10.3389/fvets.2023.1153097
  20. B. Osman, A. Elkarim, E. M. Ali, K. Haj, and K. Elbadawi, “Adoption Rates of Some Improved Technological Practices of Dairy Cattle Milk Production among Smallholder Farmers in Nahir Atbara Locality-Kassala State-Sudan,” 2017, noveltyjournals.com. [Online]. Available: www.noveltyjournals.com
  21. S. Mishra, M. Sonawane, P. Lohar, and S. Sonawane, “Role of Digital Technologies in Livestock Management,” 2022, acscollegeyawal.org. [Online]. Available: www.iosrjournals.org
  22. T. Lijalem, “Breeding Technology Assessment at Small Holder Dairy Cattle Production Level in Selected Districts of HYDYA ZONE ,” 2015, core.ac.uk. [Online]. Available: https://core.ac.uk/download/pdf/234687196.pdf
  23. E. Ooi, M. A. Stevenson, A. J. Murray, D. S. Beggs, P. D. Mansell, and M. F. Pyman, “The Use of Genetic Selection to Improve Herd Reproductive Performance of Dairy Cattle in Northern Victoria , Australia : Preliminary Results,” Interbull Bull., no. 53, pp. 34–41, 2018, [Online]. Available: https://journal.interbull.org/index.php/ib/article/view/1809
  24. Odintsov Vaintrub M, Levit H, Chincarini M, Fusaro I, Giammarco M, Vignola G. Review: Precision livestock farming, automats and new technologies: possible applications in extensive dairy sheep farming. Animal. 2021;15(3):100143. doi:10.1016/j.animal.2020.100143
  25. Aamir Shahzad M. The need for national livestock surveillance in Pakistan. Journal of Dairy Research. 2022;89(1):13-18. doi:10.1017/s0022029922000012
  26. Eriksson S, Jonas E, Rydhmer L, Röcklinsberg H. Invited review: Breeding and ethical perspectives on genetically modified and genome edited cattle. Journal of Dairy Science. 2018;101(1):1-17. doi:10.3168/jds.2017-12962
  27. Bell A, Sangster N. Research, development and adoption for the north Australian beef cattle breeding industry: an analysis of needs and gaps. Animal Production Science. 2022;63(1):1-40. doi:10.1071/an22065
  28. Aamir Shahzad M. The need for national livestock surveillance in Pakistan. Journal of Dairy Research. 2022;89(1):13-18. doi:10.1017/s0022029922000012
  29. Ooi E, Stevenson MA, Beggs DS, Mansell PD, Pryce JE, Murray A, et al. Herd manager attitudes and intentions regarding the selection of high-fertility EBV sires in Australia. Journal of Dairy Science. 2021;104(4):4375-4389. doi:10.3168/jds.2020-18552
  30. Niles MT, Horner C, Chintala R, Tricarico J. A review of determinants for dairy farmer decision making on manure management strategies in high-income countries. Environmental Research Letters. 2019;14(5):053004. doi:10.1088/1748-9326/ab1059
  31. Kebebe EG, Oosting SJ, Baltenweck I, Duncan AJ. Characterisation of adopters and non-adopters of dairy technologies in Ethiopia and Kenya. Tropical Animal Health and Production. 2017;49(4):681-690. doi:10.1007/s11250-017-1241-8
  32. M. L. Madan, “Animal biotechnology: Applications and economic implications in developing countries,” 2005, kashvet.org. doi:10.20506/rst.24.1.1555.
  33. E. G. Kebebe, Understanding factors affecting technology adoption in smallholder livestock production systems in Ethiopia: the role of farm resources and the enabling environment. search.proquest.com, 2015. [Online]. Available: https://search.proquest.com/openview/89ce6af0d9318b53df9aa77742fd8a93/1?pq-origsite=gscholar&cbl=2026366&diss=y
  34. Burrow HM, Mrode R, Mwai AO, Coffey MP, Hayes BJ. Challenges and Opportunities in Applying Genomic Selection to Ruminants Owned by Smallholder Farmers. Agriculture. 2021;11(11):1172. doi:10.3390/agriculture11111172
  35. Mee JF. The role of the veterinarian in bovine fertility management on modern dairy farms. Theriogenology. 2007;68:S257-S265. doi:10.1016/j.theriogenology.2007.04.030
  36. Woods A. The farm as clinic: veterinary expertise and the transformation of dairy farming, 1930–1950. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 2007;38(2):462-487. doi:10.1016/j.shpsc.2007.03.009
  37. Sumner CL, von Keyserlingk MAG, Weary DM. Perspectives of farmers and veterinarians concerning dairy cattle welfare. Animal Frontiers. 2018;8(1):8-13. doi:10.1093/af/vfx006
  38. Sumner CL, von Keyserlingk MAG. Canadian dairy cattle veterinarian perspectives on calf welfare. Journal of Dairy Science. 2018;101(11):10303-10316. doi:10.3168/jds.2018-14859
  39. Magne MA, Quénon J. Dairy crossbreeding challenges the French dairy cattle sociotechnical regime. Agronomy for Sustainable Development. 2021;41(2). doi:10.1007/s13593-021-00683-2
  40. Nimbalkar V, Kumar Verma H, Singh J. Dairy Farming Innovations for Productivity Enhancement. New Advances in the Dairy Industry. 2022. doi:10.5772/intechopen.101373
  41. Hambisa AB. Enhancing Bovine Reproduction: The Progress of Artificial Insemination in Ethiopia. Reproduction in Domestic Animals. 2024;60(1). doi:10.1111/rda.70003
  42. Ferrari A, Bacco M, Gaber K, Jedlitschka A, Hess S, Kaipainen J, et al. Drivers, barriers and impacts of digitalisation in rural areas from the viewpoint of experts. Information and Software Technology. 2022;145:106816. doi:10.1016/j.infsof.2021.106816
  43. Kebebe E. Bridging technology adoption gaps in livestock sector in Ethiopia: A innovation system perspective. Technology in Society. 2019;57:30-37. doi:10.1016/j.techsoc.2018.12.002
  44. Weary DM, Ventura BA, von Keyserlingk MAG. Societal views and animal welfare science: understanding why the modified cage may fail and other stories. animal. 2016;10(2):309-317. doi:10.1017/s1751731115001160
  45. Gaard. Reproductive Technology, or Reproductive Justice?: An Ecofeminist, Environmental Justice Perspective on the Rhetoric of Choice. Ethics and the Environment. 2010;15(2):103. doi:10.2979/ete.2010.15.2.103
  46. Rosa L, Gabrielli P. Achieving net-zero emissions in agriculture: a review. Environmental Research Letters. 2023;18(6):063002. doi:10.1088/1748-9326/acd5e8
  47. Weller JI, Ezra E, Ron M. Invited review: A perspective on the future of genomic selection in dairy cattle. Journal of Dairy Science. 2017;100(11):8633-8644. doi:10.3168/jds.2017-12879
  48. Hansen PJ, Aréchiga CF. Strategies for managing reproduction in the heat-stressed dairy cow. Journal of Animal Science. 1997;77(suppl_2):36. doi:10.2527/1997.77suppl_236x
  49. López-Gatius F. Factors of a noninfectious nature affecting fertility after artificial insemination in lactating dairy cows. A review. Theriogenology. 2012;77(6):1029-1041. doi:10.1016/j.theriogenology.2011.10.014
  50. Neethirajan S, Kemp B. Digital Livestock Farming. Sensing and Bio-Sensing Research. 2021;32:100408. doi:10.1016/j.sbsr.2021.100408
  51. Bianchi MC, Bava L, Sandrucci A, Tangorra FM, Tamburini A, Gislon G, et al. Diffusion of precision livestock farming technologies in dairy cattle farms. animal. 2022;16(11):100650. doi:10.1016/j.animal.2022.100650
  52. Martin GB, Fordyce G, McGowan MR, Juengel JL. Perspectives for reproduction and production in grazing sheep and cattle in Australasia: The next 20 years. Theriogenology. 2024;230:174-182. doi:10.1016/j.theriogenology.2024.09.017
  53. M. D. Jelinski, D. F. Kelton, C. Luby, and C. Waldner, “Factors associated with the adoption of technologies by the Canadian dairy industry,” 2020, pmc.ncbi.nlm.nih.gov. [Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC7488376/
  54. Palma-Molina P, Hennessy T, O'Connor AH, Onakuse S, O'Leary N, Moran B, et al. Factors associated with intensity of technology adoption and with the adoption of 4 clusters of precision livestock farming technologies in Irish pasture-based dairy systems. Journal of Dairy Science. 2023;106(4):2498-2509. doi:10.3168/jds.2021-21503
  55. Piña R, Lange K, Machado V, Bratcher C. Big data technology adoption in beef production. Smart Agricultural Technology. 2023;5:100235. doi:10.1016/j.atech.2023.100235
  56. Neethirajan S. Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation. Sensors. 2023;23(16):7045. doi:10.3390/s23167045
  57. Thinawanga JM, Voster M, Nkhanedzeni BN, Khathutshelo AN, Tshimangadzo LN. Challenges with the implementation and adoption of assisted reproductive technologies under communal farming system. Journal of Veterinary Medicine and Animal Health. 2018;10(10):237-244. doi:10.5897/jvmah2018.0707
  58. Arthur PF, Archer JA, Herd RM. Feed intake and efficiency in beef cattle: overview of recent Australian research and challenges for the future. Australian Journal of Experimental Agriculture. 2004;44(5):361. doi:10.1071/ea02162
  59. Mercadante VRG, Dias NW, Pancini S, Goncherenko G, Craun H, Vidlund T, et al. 2 Challenges in Breeding and Genetics. Journal of Animal Science. 2023;101(Supplement_1):96-98. doi:10.1093/jas/skad068.115
  60. Maleko D, Msalya G, Mwilawa A, Pasape L, Mtei K. Smallholder dairy cattle feeding technologies and practices in Tanzania: failures, successes, challenges and prospects for sustainability. International Journal of Agricultural Sustainability. 2018;16(2):201-213. doi:10.1080/14735903.2018.1440474
  61. Limenih B. Women farmers’ adoption challenges on artificial inseminations service in outskirt of Addis Ababa. International Journal of Agricultural Extension. 2018;6(2):81-88. doi:10.33687/ijae.006.02.2417
  62. Erratum. Journal of Dairy Science. 2009;92(3):1313. doi:10.3168/jds.2009-92-3-1313
  63. Limenih B. Women farmers’ adoption challenges on artificial inseminations service in outskirt of Addis Ababa. International Journal of Agricultural Extension. 2018;6(2):81-88. doi:10.33687/ijae.006.02.2417
  64. Baldin M, Breunig T, Cue R, De Vries A, Doornink M, Drevenak J, et al. Integrated Decision Support Systems (IDSS) for Dairy Farming: A Discussion on How to Improve Their Sustained Adoption. Animals. 2021;11(7):2025. doi:10.3390/ani11072025
  65. Ogola PA, Ngesa F, Makanji DL. Influence of access to extension services on milk productivity among smallholder dairy farmers in Njoro Sub-County, Nakuru County, Kenya. Heliyon. 2023;9(9):e20210. doi:10.1016/j.heliyon.2023.e20210
  66. Stevenson JS. Impact of Reproductive Technologies on Dairy Food Production in the Dairy Industry. Advances in Experimental Medicine and Biology. 2013:115-129. doi:10.1007/978-1-4614-8887-3_6
  67. Nengovhela NB, Mugwabana TJ, Nephawe KA, Nedambale TL. Accessibility to Reproductive Technologies by Low-Income Beef Farmers in South Africa. Frontiers in Veterinary Science. 2021;8. doi:10.3389/fvets.2021.611182
  68. Hansen PJ. Current and Future Assisted Reproductive Technologies for Mammalian Farm Animals. Advances in Experimental Medicine and Biology. 2013:1-22. doi:10.1007/978-1-4614-8887-3_1
  69. Tizard M, Hallerman E, Fahrenkrug S, Newell-McGloughlin M, Gibson J, de Loos F, et al. Strategies to enable the adoption of animal biotechnology to sustainably improve global food safety and security. Transgenic Research. 2016;25(5):575-595. doi:10.1007/s11248-016-9965-1
  70. S. Mahato and S. Neethirajan, “Integrating Artificial Intelligence in Dairy Farm Management-Biometric Facial Recognition for Cows,” 2024, Elsevier. [Online]. Available: www.preprints.org
  71. M. Yousuf, A. Yusuf, and I. Mohammed, “Review on Current Animal Breeding and Genetic Technologies to Increase Production and Productivity of Cattle,” J. Anim. Sci. Res., vol. 12, no. 1, pp. 19–36, 2024, [Online]. Available: http://www.gjasr.com/index.php/GJASR/article/view/191
  72. R. Green, P. Amer, and P. Fennessy, “The role of AI in genetic progress-new opportunities from new technologies and new approaches,” 2013.
  73. White RR, Brady M, Capper JL, McNamara JP, Johnson KA. Cow–calf reproductive, genetic, and nutritional management to improve the sustainability of whole beef production systems. Journal of Animal Science. 2015;93(6):3197-3211. doi:10.2527/jas.2014-8800
  74. J. Daar, The new eugenics: Selective breeding in an era of reproductive technologies. books.google.com, 2017. [Online]. Available: https://books.google.com/books?hl=en&lr=&id=gtsCDgAAQBAJ&oi=fnd&pg=PP1&dq=adoption+barriers+reproductive+technologies+dairy+cows&ots=w-f2qEKwdu&sig=DjGi1MDdOac9f7TsUccmKMFuCfU
  75. Harrison J, Knowlton K, James B, Hanigan MD, Stallings C, Whitefield E. CASE STUDY: National survey of barriers related to precision phosphorus feeding. The Professional Animal Scientist. 2012;28(5):564-568. doi:10.15232/s1080-7446(15)30406-x
  76. D. Fleming et al., Synthesis report: Barriers to adoption of no-cost agricultural mitigation practices, no. May. motu.nz, 2019. [Online]. Available: https://www.motu.nz/assets/Documents/our-work/environment-and-agriculture/agricultural-economics/no-cost-barriers/No-Cost-Mitigation-Synthesis.pdf
  77. Mutua E, de Haan N, Tumusiime D, Jost C, Bett B. A Qualitative Study on Gendered Barriers to Livestock Vaccine Uptake in Kenya and Uganda and Their Implications on Rift Valley Fever Control. Vaccines. 2019;7(3):86. doi:10.3390/vaccines7030086
  78. I. Jumper, Identifying Barriers to Data Use on US Beef Cow-Calf Operations and Developing Solutions to Improve Cow-Calf Record-Keeping. search.proquest.com, 2023. [Online]. Available: https://search.proquest.com/openview/18ddca1dcbba35eb7ca0a17217a9b7d9/1?pq-origsite=gscholar&cbl=18750&diss=y
  79. Barrier AC, Haskell MJ. Calving difficulty in dairy cows has a longer effect on saleable milk yield than on estimated milk production. Journal of Dairy Science. 2011;94(4):1804-1812. doi:10.3168/jds.2010-3641
  80. Butler ST, Crowe AD, Moore SG, Lonergan P. Review: Use of assisted reproduction in seasonal-calving dairy herds. animal. 2023;17:100775. doi:10.1016/j.animal.2023.100775
  81. Groher T, Heitkämper K, Umstätter C. Digital technology adoption in livestock production with a special focus on ruminant farming. Animal. 2020;14(11):2404-2413. doi:10.1017/s1751731120001391
  82. X. Chen and S. Huang, “Optimization of Reproductive Technologies in Water Buffalo: A Review of Current Practices,” 2024, animalscipublisher.com. [Online]. Available: https://animalscipublisher.com/index.php/ijmz/article/download/3867/2971
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