PRECISION LIVESTOCK FARMING: INNOVATIONS IN FEED MANAGEMENT AND ANIMAL HEALTH FOR OPTIMIZED PRODUCTION EFFICIENCY
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Animal Health Monitoring, Feed Management, Precision Livestock Farming, Production Efficiency, Smart Agriculture
Abstract
Precision Livestock Farming (PLF) has emerged as a strategic approach to address efficiency, sustainability, and animal welfare challenges in modern livestock systems. Advances in sensor technologies, data analytics, and automated decision-support tools have enabled real-time monitoring of feed intake, animal behavior, and health status, yet empirical evidence on their integrated impacts remains fragmented. This study aims to evaluate how innovations in precision feed management and animal health monitoring contribute to optimized production efficiency in intensive livestock systems. The research employed a quantitative experimental design combined with farm-level monitoring, involving sensor-based feed delivery systems, wearable health sensors, and automated data analytics across selected commercial livestock farms. Performance indicators included feed conversion ratio, growth or productivity rates, health incidence, and resource-use efficiency. The results demonstrate that precision-managed feeding significantly reduced feed waste while improving feed conversion efficiency, whereas continuous health monitoring enabled early disease detection and reduced morbidity rates. Integrated PLF systems produced measurable gains in overall productivity and operational efficiency compared to conventional management practices. The study concludes that the synergistic application of precision feed management and animal health technologies enhances production efficiency while supporting animal welfare and resource sustainability. These findings highlight the potential of PLF as a transformative pathway for resilient and data-driven livestock production systems.
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References
Ahmed, N., & Shakoor, N. (2025). Advancing agriculture through IoT, Big Data, and AI: A review of smart technologies enabling sustainability. Smart Agricultural Technology, 10, 100848. https://doi.org/10.1016/j.atech.2025.100848
Albayrak, A. (2026). A multi-layered digital twin framework for smart agriculture and livestock: System architecture and implementation challenges. Information and Software Technology, 195, 108139. https://doi.org/10.1016/j.infsof.2026.108139
Alshehri, Dr. M. (2023). Blockchain-assisted internet of things framework in smart livestock farming. Internet of Things, 22, 100739. https://doi.org/10.1016/j.iot.2023.100739
Ammann, J., Mack, G., El Benni, N., & Saleh, R. (2025). Understanding public perceptions of smart farming technologies. Food Quality and Preference, 133, 105618. https://doi.org/10.1016/j.foodqual.2025.105618
Apollon, W., Jean-Baptiste, Y., Maheshwari, S., Ghosh, S., Ghosh, S., Ariste, A., Joseph, R., Kamaraj, S.-K., & Bedair, H. (2026). Smart agriculture for greenhouse gas mitigation: Integrating digital tools, engineering metrics, and policy instruments—A review. Next Research, 7, 101445. https://doi.org/10.1016/j.nexres.2026.101445
Assan, N. (2026). Chapter 3—Climate-smart approaches to livestock production for food security and sustainability. In S. Mondal (Ed.), Genetic and Reproductive Approaches for Sustainable Livestock Production (pp. 37–68). Academic Press. https://doi.org/10.1016/B978-0-443-24812-2.00010-5
Awais, M., Wang, X., & Ashraf, M. U. (2026). Mitigation and adaptation strategies in climate-smart agriculture: A review for sustainable production. Climate Smart Agriculture, 3(1), 100097. https://doi.org/10.1016/j.csag.2026.100097
Bazza, H., Bimonte, S., Rizzi, S., & Badir, H. (2025). Data management and processing for IoT & robotics in smart farming: A survey. Journal of Computer Languages, 85, 101355. https://doi.org/10.1016/j.cola.2025.101355
Bonfanti, M., Selvaggi, R., Pappalardo, G., Bellia, C., Pecorino, B., & Porto, S. M. C. (2025). On the market appeal of smart pedometer-based services within dairy cow farms. Environmental and Sustainability Indicators, 27, 100798. https://doi.org/10.1016/j.indic.2025.100798
Bustamante, E. B., Capote, C. B., González, F. J. N., De-Pablos-Heredero, C., & Martínez, A. G. (2026). Identifying Digitalisation patterns in Spanish livestock farming through open data use. A proposal of best practice management. Smart Agricultural Technology, 13, 101806. https://doi.org/10.1016/j.atech.2026.101806
Chen, W.-E., Lin, S.-C., & Cho, H.-H. (2026). Generative data augmentation for AIoT-based smart pig farming: The PigTalk 2.0 system. Computers and Electronics in Agriculture, 244, 111442. https://doi.org/10.1016/j.compag.2026.111442
Dawkins, M. S. (2025). Smart farming and Artificial Intelligence (AI): How can we ensure that animal welfare is a priority? Applied Animal Behaviour Science, 283, 106519. https://doi.org/10.1016/j.applanim.2025.106519
Dawkins, M. S., Ellwood, S., Roberts, S., Weathers, K. B., & Donnelly, C. A. (2025). The benefits of smart farming: Broiler chicken welfare is indicated earlier and more accurately with automated measurements of flock behaviour. Smart Agricultural Technology, 12, 101500. https://doi.org/10.1016/j.atech.2025.101500
Diao, Z., Chen, L., Yang, Y., Liu, Y., Yan, J., He, S., & Zhang, B. (2025). Localization technologies for smart agriculture and precision farming: A review. Computers and Electronics in Agriculture, 236, 110464. https://doi.org/10.1016/j.compag.2025.110464
Ecer, F., Yaran Ögel, ?., Dinçer, H., & Yüksel, S. (2024). Assessment of Metaverse wearable technologies for smart livestock farming through a neuro quantum spherical fuzzy decision-making model. Expert Systems with Applications, 255, 124722. https://doi.org/10.1016/j.eswa.2024.124722
Erekalo, K. T., Pedersen, S. M., Christensen, T., Denver, S., Gemtou, M., Fountas, S., & Isakhanyan, G. (2024). Review on the contribution of farming practices and technologies towards climate-smart agricultural outcomes in a European context. Smart Agricultural Technology, 7, 100413. https://doi.org/10.1016/j.atech.2024.100413
Eyasin, M. S. H., Sobhani, M. E., Nasrin, S., Al Rafi, A. S., & Muzahidul Islam, A. K. M. (2026). CropSynergy: Harnessing IoT solutions for smart and efficient crop management. Crop Design, 5(1), 100127. https://doi.org/10.1016/j.cropd.2025.100127
Ghavi Hossein-Zadeh, N. (2026). Advancing climate-resilient livestock systems: Next-generation emission mitigation strategies and integrated technological innovations. Veterinary and Animal Science, 31, 100588. https://doi.org/10.1016/j.vas.2026.100588
Jhilta, A., Jadhav, K., Singh, R., Negi, S., kaur, S., Sharma, N., & Verma, R. K. (2026). Advanced precision veterinary technologies and smart boluses: Innovations in drug delivery, health monitoring, and future perspectives. Journal of Drug Delivery Science and Technology, 115, 107563. https://doi.org/10.1016/j.jddst.2025.107563
Jiang, D., Zhang, M., Yu, J., Zhao, Q., Bakaric, M. B., Chen, K., & Zhang, X. (2025). Ai-driven advanced flexible pressure sensor arrays for smart animal husbandry: Response characteristics, optimization strategies, innovative applications. Computers and Electronics in Agriculture, 239, 110988. https://doi.org/10.1016/j.compag.2025.110988
Jiang, W., Hao, H., Wang, H., & Wang, L. (2025). Possible application of agricultural robotics in rabbit farming under smart animal husbandry. Journal of Cleaner Production, 501, 145301. https://doi.org/10.1016/j.jclepro.2025.145301
K?rba?, ?. (2025). Artificial intelligence-enhanced walk-over-weighing system for real-time livestock weight monitoring: A novel approach for precision farming. Preventive Veterinary Medicine, 245, 106673. https://doi.org/10.1016/j.prevetmed.2025.106673
Lagua, E. B., Mun, H.-S., Sharifuzzaman, M., Hasan, M. K., Mehtab, A., Kang, J.-G., Kim, Y.-H., & Yang, C.-J. (2026). Integration of computer vision-based behavioral monitoring and machine learning to enhance precision in health and welfare monitoring systems in pig farming. Smart Agricultural Technology, 13, 101876. https://doi.org/10.1016/j.atech.2026.101876
Liang, J., Yuan, Z., Luo, X., Qu, J., Qi, Y., & Wang, C. (2025). Application of non-invasive monitoring technology in intensive sheep farming: A review. Smart Agricultural Technology, 12, 101215. https://doi.org/10.1016/j.atech.2025.101215
Lin, X., Chen, S., Yan, N., Pi, J., Zhu, T., & Xu, L. (2026). Knowledge distillation for smart agriculture: Methods, applications, and future directions. Smart Agricultural Technology, 14, 102019. https://doi.org/10.1016/j.atech.2026.102019
Shafi, F. B., Ahamed, Md. F., Nabi, Md. F., Khandakar, A., Rohouma, W., Ayari, M. A., Thomas, K., Rahman, A., Reaz, M. B. I., Haq, F., & Refaat, S. S. (2025). Review of sensor technologies, DC-DC converters, and power electronics for sustainable monitoring in precision livestock farming. Results in Engineering, 28, 107975. https://doi.org/10.1016/j.rineng.2025.107975
Silvestri, A., Parlato, M. C. M., Ruchay, A., Guo, H., Iussig, G., & Pezzuolo, A. (2026). Tech-driven evolution of animal housing: An in-depth analysis of the impact of digital technologies, AI, and GenAI in the Era of precision livestock farming. Computers and Electronics in Agriculture, 246, 111602. https://doi.org/10.1016/j.compag.2026.111602
Stoll, E., Keßler, S., Leimbrock-Rosch, L., Bohn, T., Reckinger, R., Schader, C., Herzig, C., & Zimmer, S. (2025). Using the SMART-Farm Tool to identify linchpin farming practices for the improvement of the atmosphere-related sustainability performance of the Luxembourgish agriculture sector. Journal of Environmental Management, 394, 127426. https://doi.org/10.1016/j.jenvman.2025.127426
Subeesh, A., & Chauhan, N. (2026). Agricultural digital twin for smart farming: A review. Green Technologies and Sustainability, 4(2), 100299. https://doi.org/10.1016/j.grets.2025.100299
Surekha, R., Sampath, S., Dhinakaran, M., Kumar, B., & Jebastin, P. (2026). Chapter 31—Integrating sustainable practices in climate-smart agriculture and adaptation strategies. In T. Sarkar & S. Smaoui (Eds.), Health, Nutrition and Sustainability (pp. 695–713). Academic Press. https://doi.org/10.1016/B978-0-443-32920-3.00033-1
Tariq, M., Singh, Y., Kanekar, T., Aamir, M., Madan, A., Jain, D., & Rawat, S. (2026). Chapter 11—Introduction to technological advancements in smart farming practices. In G. W. Vuister, A. Kumar, N. Chaturvedi, & G. Santoyo (Eds.), Emerging Omics Technologies for Sustainable Agriculture (pp. 257–279). Academic Press. https://doi.org/10.1016/B978-0-443-40316-3.00011-4
Thilakarathne, N. N., Abu Bakar, M. S., Abas, P. E., & Yassin, H. (2025). Internet of things enabled smart agriculture: Current status, latest advancements, challenges and countermeasures. Heliyon, 11(3), e42136. https://doi.org/10.1016/j.heliyon.2025.e42136
Yin, M., Ma, R., Luo, H., Li, J., Zhao, Q., & Zhang, M. (2023). Non-contact sensing technology enables precision livestock farming in smart farms. Computers and Electronics in Agriculture, 212, 108171. https://doi.org/10.1016/j.compag.2023.108171
Zhang, M., Wang, X., Feng, H., Huang, Q., Xiao, X., & Zhang, X. (2021). Wearable Internet of Things enabled precision livestock farming in smart farms: A review of technical solutions for precise perception, biocompatibility, and sustainability monitoring. Journal of Cleaner Production, 312, 127712. https://doi.org/10.1016/j.jclepro.2021.127712
Zhu, L., Yang, X., Xian, Y., Jiang, W., Pu, X., Wang, S., Cheng, J., Niu, L., Zhao, Y., Chen, L., Zhou, X., Wang, Y., Gan, M., Zhu, L., & Shen, L. (2025). Empowering precision livestock farming: Artificial intelligence applications in animal genomic breeding and multi-dimensional phenotypic measurement. Smart Agricultural Technology, 12, 101655. https://doi.org/10.1016/j.atech.2025.101655
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Copyright (c) 2026 Sarah Williams, Jessica Green, Michael Turner
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