Precision Livestock Farming Technologies Reduce Greenhouse Gas Emissions on Commercial Beef Farms: A Modelling Study
Louise C. McNicol, Jenna M. Bowen, Holly J. Ferguson, Julian Bell, Carol‐Anne DuthieABSTRACT
Agriculture, particularly beef production, accounts for a significant share of global greenhouse gas (GHG) emissions, requiring substantial mitigation. Precision livestock farming (PLF) technologies offer a potential solution to indirectly reduce GHG emissions by increasing production efficiencies. Using data from 18 Scottish beef farms (nine suckler and nine finishing systems) which are representative of many European production systems, this study modelled three PLF technologies: automatic weighing platforms, fertility sensors, and health sensors. Baseline emissions were estimated using the carbon calculator Agrecalc, with assumptions informed by an extensive literature review and expert input. Automatic weighing platforms, reducing age at slaughter by 1–3 months, enabled total emissions to be reduced by 1.1%–2.76% in suckler systems and 6.10%–21.28% in finishing systems on average. Emission intensities also decreased, although to lesser extent due to reduced killing out percentage. Impacts were greater in finishing systems as they have fewer additional emission sources beyond the finishing cattle themselves. Fertility sensors enabled improvements in production efficiency that reduced total emissions by 3.69% and emission intensities by 9.18% on average in suckler systems, driven by increased calves born and lower mortality. Improvements in production efficiencies resulting from the adoption of health sensors slightly increased total emissions (7.96% in suckler systems and 8.24% in finishing systems due to increased calves born, increased DLWG and lower mortality, but delivered the greatest emission intensity reductions (12.63% in suckler herds and 8.61% in finishing systems) as output increased. Overall, the PLF technologies explored in this study show strong potential to reduce GHG emissions in beef systems, though impacts vary by system and technology. These findings could guide targeted incentives and wider adoption.