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Digital Transition as a Driver for Sustainable Tailor-Made Farm Management: An Up-to-Date Overview on Precision Livestock Farming

Author

Listed:
  • Caterina Losacco

    (Department of Precision and Regenerative Medicine and Jonian Area, Section of Veterinary Science and Animal Production, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

  • Gianluca Pugliese

    (Department of Precision and Regenerative Medicine and Jonian Area, Section of Veterinary Science and Animal Production, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

  • Lucrezia Forte

    (Department of Veterinary Medicine, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

  • Vincenzo Tufarelli

    (Department of Precision and Regenerative Medicine and Jonian Area, Section of Veterinary Science and Animal Production, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

  • Aristide Maggiolino

    (Department of Veterinary Medicine, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

  • Pasquale De Palo

    (Department of Veterinary Medicine, University of Bari Aldo Moro, Valenzano, 70010 Bari, Italy)

Abstract

The increasing integration of sensing devices with smart technologies, deep learning algorithms, and robotics is profoundly transforming the agricultural sector in the context of Farming 4.0. These technological advancements constitute critical enablers for the development of customized, data-driven farming systems, offering potential solutions to the challenges of agricultural intensification while addressing societal concerns associated with the emerging paradigm of “farming by numbers”. The Precision Livestock Farming (PLF) systems enable the continuous, real-time, and individual sensing of livestock in order to detect subtle change in animals’ status and permit timely corrective actions. In addition, smart technology implementation within the housing environment leads the whole farming sector towards enhanced business rentability and food security as well as increased animal health and welfare conditions. Looking to the future, the collection, processing, and analysis of data with advanced statistic methods provide valuable information useful to design predictive models and foster the insight on animal welfare, environmental sustainability, farming productivity, and profitability. This review highlights the significant potential of implementing advanced sensing systems in livestock farming, examining the scientific foundations of PLF and analyzing the main technological applications driving the transition from traditional practices to more modern and efficient farming models.

Suggested Citation

  • Caterina Losacco & Gianluca Pugliese & Lucrezia Forte & Vincenzo Tufarelli & Aristide Maggiolino & Pasquale De Palo, 2025. "Digital Transition as a Driver for Sustainable Tailor-Made Farm Management: An Up-to-Date Overview on Precision Livestock Farming," Agriculture, MDPI, vol. 15(13), pages 1-36, June.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:13:p:1383-:d:1689414
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    References listed on IDEAS

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