Farmanagers®: end-to-end data automation and carbon footprint modeling for dairy sheep and goat farms

The integration of digital technologies in livestock management, commonly referred to as Precision Livestock Farming (PLF), aims to improve productivity, animal welfare, and environmental sustainability through real-time monitoring and data-driven decision support [cite relevant literature]. This paper presents Farmanagers®, a platform developed for the dairy sheep and goat sector. The system comprises a suite of custom-designed Internet of Things (IoT) sensors and a dedicated Farm Management Information System (FMIS) designed to centralize and analyze farm data. Farmanagers® automates data acquisition through IoT sensors that record individual animal weight and milk yield at each milking session (twice daily). Animals are identified using radio frequency identification (RFID) tags and readers equipped with large-area coverage antennas. In addition to automated data, the FMIS allows manual entry of records pertaining to individual diets, breed, sex, date of birth, pedigree, reproduction events, vaccination and medication history, and farm energy consumption by task. Communication between hardware components and the central software platform is established via Internet Protocol (IP), a prerequisite for system deployment. Data are accessible to the user through a web-based application. A distinguishing feature of Farmanagers® is its capacity to calculate the farm's carbon footprint. The system estimates CO₂-equivalent greenhouse gas (GHG) emissions for both pure livestock farms that purchase external feed and mixed farms cultivating their own pasture. These calculations are performed in full compliance with the 2019 guidelines of the Intergovernmental Panel on Climate Change (IPCC), providing a methodological framework consistent with certification requirements. Following laboratory validation, Farmanagers® was evaluated over a 12-month period on a mixed dairy farm in Northwestern Greece with a flock of 1,200 sheep and goats. The objectives of the evaluation were to assess system reliability, quantify GHG emissions, and monitor animal-level production metrics. The RFID system achieved 100% identification accuracy across all measurement points throughout the trial period. The platform successfully tracked annual milk yield and weight gain for each individual animal. Production data obtained from the system were used to inform dietary adjustments. Following a mid-trial modification of the ration, mean milk yield increased by approximately 10%. The system also generated a comprehensive estimate of the farm's CO₂-equivalent GHG emissions, demonstrating its utility as a tool for environmental accounting. Such quantified emissions data may support the development of reduction strategies and could potentially be used within frameworks such as the European Union Emissions Trading System (EU ETS). The field evaluation confirms the technical reliability of Farmanagers® in a commercial farming environment. The observed increase in milk yield following data-driven dietary adjustments illustrates the potential of the platform to support management decisions that enhance productivity. Furthermore, its compliance with IPCC guidelines positions it as a practical tool for GHG accounting, aligning with evolving regulatory and market demands for sustainability in livestock production.