The project relied on stakeholder engagement to ensure relevant outcomes to the industry. At each major step, stakeholders have been asked for their feedback. Across the 9 countries, 8 series of workshops have been organised, with over 1350 stakeholders participating. A consumer perception survey towards welfare issues in SR systems and their behaviour towards welfare certified dairy and meat products was conducted across 13 countries and attracted 2,863 respondents.
An inventory of the welfare issues relevant to the systems studied in the project was developed, resulting in a list of 80 potential welfare issues per species. Stakeholders prioritised welfare issues relevant to them. 13 welfare issues for meat and dairy sheep, 8 for lambs and 9 for dairy goats were ranked. Welfare assessment protocols were developed for meat sheep, dairy sheep, dairy goats and lambs covering the animal-based measures (ABMs) required to assess the prioritised welfare issues previously identified. 4 broad categories of indicators based on those welfare issues have been subsequently defined.
In parallel, a review of existing PLF tools and DT was conducted, with 12 promising digital tools that could measure/inform any of the 4 categories of welfare indicators being selected.
7 pilot farms tested a selection of the 12 DT for validation, collecting welfare and data to develop early warning systems (EWS). 56 large-scale study farms were identified in 5 countries, to further test 4 out of the 12 technologies: weather stations and indoors environmental sensors, RFID readers and automatic weigh-crates, individual milk meters, milk tank weighing scales, alongside welfare assessments using a tailored app. Feedback from the farmers has been sought, and guidelines on how to use those tools have been developed for further dissemination.
Other trials, conducted under more controlled conditions, focused on prototyping and/or adaptation of some promising PLF tools and approaches (e.g. Bluetooth, GPS collars, Walk-over-Weigh).
Data exchange and analysis to build algorithms led to three main EWS being investigated:
1) Milk yield (can be reduced by undernutrition, heat stress, disease, poor environmental conditions – measured with milk meters/daily tank weight) and milking parlour order (changes indicative of lameness/disease - recorded with RFID tags or milking counters)
2) THI/Thermal stress (risk factors of heat/cold stress, respiratory diseases – measured by indoor sensors in shed and from outdoor weather stations) – leading to the THIcare App development.
3) Liveweight change (slower growth due to disease, poor maternal relationship, parasitism, nutrition – measured with weigh-crates and RFID antennas).
These algorithms and datasets collected during the project are available on a GitLab platform. Work on transport to market or abattoir (adult sheep on boats and kid/lambs on trailers) has also been undertaken.
Business models around the 4 tested technologies on large-scale identified both the subscription and freemium models as relevant approaches.
For a productive dissemination, communication and exploitation of results, a TechCare platform has been created (www.techcare-project.eu) with social media accounts, alongside a zenodo site (www.zenodo.org/communities/techcare) and EUFarmbook site. 40 practice abstracts are uploaded on EUCAP network, 16 newsletters have been distributed. Over 130 presentations were done at conferences, workshops and webinars. Collaboration with other EU projects during conferences and webinars was also sought after. A final conference has been organised in Brussels in 2025, with videos of the presentations and panel discussions available on YouTube (TechCare project - YouTube). Popular articles, podcasts and 14 scientific publications have also been published or submitted. Over 8000 people participated to various open days and on-site visits showcasing the project’s results.
