Periodic Reporting for period 3 - TechCare (Integrating innovative TECHnologies along the value Chain to improve small ruminant welfARE management)
Período documentado: 2023-09-01 hasta 2024-08-31
Although precision livestock farming (PLF) and innovative digital technologies (DT) are widely adopted in management of high-value animals, they have not yet been applied in species where animals are considered to have a lower individual value or less economic interest as is the case in small ruminants (SR). This is despite the very significant welfare and production efficiency advantages that can be achieved by applying PLF and DT in these contexts. Animal welfare is about the individual sum of suffering or pleasure that accrues to the individual over the course of its life. SR, however, are often managed as a group and only average welfare state might be considered. A PLF approach to welfare management in SR could allow the individual animal to be identified within the group, so that nutrition, health care or other welfare aspects can be individualized and managed.
Much EU legislation and research have been devoted to regulate and improve welfare of domestic animals bred for food production. The very significant welfare challenges experienced by SR in all systems are prime targets for welfare management by application of PLF and DT across the whole value chain, to the benefit of society.
The overall objective of TechCare is to explore and demonstrate innovative DT to develop early warning systems (EWS) to improve welfare management in SR farming systems.
TechCare tackles the challenge of using innovative and low-cost DT, adapted to the husbandry of SR systems across the EU. TechCare covers most stages of SR production and builds on state-of-the-art animal welfare approaches to develop and validate innovative digital tools, EWS and indicators for efficient identification of welfare issues and risks, which can be included in welfare management models.
To achieve this, TechCare will:
1. Prioritise SR welfare issues in a spectrum of systems and conditions.
2. Co-design approaches with stakeholders, to improve welfare management using innovative DT and EWS.
3. Identify, prototype and test different innovative DT for measuring prioritised welfare issues and risks and animal-based indicators.
4. Establish integrated data management approaches along the whole value chain with a focus on improved animal welfare management and design EWS.
5. Validate a set of ‘ready-to- use’ DT under large scale farm conditions in different operational environments.
6. Propose relevant and sustainable business models to boost innovative DT uptake.
7. Establish progressive communication and dissemination of project’ outputs by different channels and ensure an efficient exploitation of results.
Much EU legislation and research have been devoted to regulate and improve welfare of domestic animals bred for food production. The very significant welfare challenges experienced by SR in all systems are prime targets for welfare management by application of PLF and DT across the whole value chain, to the benefit of society.
The overall objective of TechCare is to explore and demonstrate innovative DT to develop early warning systems (EWS) to improve welfare management in SR farming systems.
TechCare tackles the challenge of using innovative and low-cost DT, adapted to the husbandry of SR systems across the EU. TechCare covers most stages of SR production and builds on state-of-the-art animal welfare approaches to develop and validate innovative digital tools, EWS and indicators for efficient identification of welfare issues and risks, which can be included in welfare management models.
To achieve this, TechCare will:
1. Prioritise SR welfare issues in a spectrum of systems and conditions.
2. Co-design approaches with stakeholders, to improve welfare management using innovative DT and EWS.
3. Identify, prototype and test different innovative DT for measuring prioritised welfare issues and risks and animal-based indicators.
4. Establish integrated data management approaches along the whole value chain with a focus on improved animal welfare management and design EWS.
5. Validate a set of ‘ready-to- use’ DT under large scale farm conditions in different operational environments.
6. Propose relevant and sustainable business models to boost innovative DT uptake.
7. Establish progressive communication and dissemination of project’ outputs by different channels and ensure an efficient exploitation of results.
The project relies on stakeholder engagement to ensure outcomes are relevant to the industry and value chain. At each major steps, stakeholders have been involved in discussions for their feedback. Across the 9 countries, 4 series of workshops have been organised so far, with 260 stakeholders participating in a first series, 150 in a second series, 299 in the third one, and 154 in the 4th one.
An inventory of the welfare issues relevant to the sheep and goat systems studied in the project was developed, resulting in a list of 80 potential welfare issues per species. Stakeholders prioritised the welfare issues relevant to them. 14 welfare issues for meat and dairy sheep, 9 for lambs and 7 for dairy goats were thus collated and ranked. 35 potential welfare assessment methods for assessing the priority welfare issues were identified and 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. At least one ABM was identified for each of the top 13 meat and dairy sheep issues, 8 lamb welfare issues and 9 goat welfare issues. 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, and a shortlist of 15 promising digital tools (DT) that could measure or inform any of the 4 categories of welfare indicators, have been selected.
The 7 pilot farms in the project have tested a selection of the 11 innovative DT for validation. This selection had been made according to a) stakeholders’ feedback and ranking in the 2nd series of workshops and b) to a short-listing of 7 DT that could be deployed on farms for large scale according to the consortium’s expert opinion. Welfare assessment methodologies, common protocols, and ethics considerations have been established, and pilot farms trials have collected data to allow the development of early warning systems (EWS). The large-scale study farms have been identified in 5 countries, with equipment bought, protocols established, and measurements ongoing. 4 technologies (validated by stakeholders in the 4th series of workshops) are being tested: 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.
Other trials have been established under more controlled conditions, to develop prototyping and/or adaptation of some promising PLF tools and approaches not yet ready to be used for welfare management.
Data exchange and analysis work has also started to build algorithms for EWS. Mapping of data, data exchange procedure, and initial pilot data analyses have been put in place. Three EWS have been retained, with ongoing analyses:
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)
3) Liveweight change (slower growth associated with disease, poor maternal relationship, parasitism, nutrition – measured with weigh-crates and RFID antennas)
Business models around the 4 tested technologies on large-scale are being investigated, and a value chain survey developed.
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). 12 newsletters have been prepared and distributed. Post-pandemic, participation to conferences, workshops and webinars have increased, with one dedicated online webinar in January 2023, and a common session with another similar EU project at a European conference in August 2023. Popular articles, podcasts and 8 scientific publications have also been completed. Onboarding on the API-Agro platform for data sharing and exploitation of results is on-going, with UK pilot data already available.
An inventory of the welfare issues relevant to the sheep and goat systems studied in the project was developed, resulting in a list of 80 potential welfare issues per species. Stakeholders prioritised the welfare issues relevant to them. 14 welfare issues for meat and dairy sheep, 9 for lambs and 7 for dairy goats were thus collated and ranked. 35 potential welfare assessment methods for assessing the priority welfare issues were identified and 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. At least one ABM was identified for each of the top 13 meat and dairy sheep issues, 8 lamb welfare issues and 9 goat welfare issues. 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, and a shortlist of 15 promising digital tools (DT) that could measure or inform any of the 4 categories of welfare indicators, have been selected.
The 7 pilot farms in the project have tested a selection of the 11 innovative DT for validation. This selection had been made according to a) stakeholders’ feedback and ranking in the 2nd series of workshops and b) to a short-listing of 7 DT that could be deployed on farms for large scale according to the consortium’s expert opinion. Welfare assessment methodologies, common protocols, and ethics considerations have been established, and pilot farms trials have collected data to allow the development of early warning systems (EWS). The large-scale study farms have been identified in 5 countries, with equipment bought, protocols established, and measurements ongoing. 4 technologies (validated by stakeholders in the 4th series of workshops) are being tested: 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.
Other trials have been established under more controlled conditions, to develop prototyping and/or adaptation of some promising PLF tools and approaches not yet ready to be used for welfare management.
Data exchange and analysis work has also started to build algorithms for EWS. Mapping of data, data exchange procedure, and initial pilot data analyses have been put in place. Three EWS have been retained, with ongoing analyses:
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)
3) Liveweight change (slower growth associated with disease, poor maternal relationship, parasitism, nutrition – measured with weigh-crates and RFID antennas)
Business models around the 4 tested technologies on large-scale are being investigated, and a value chain survey developed.
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). 12 newsletters have been prepared and distributed. Post-pandemic, participation to conferences, workshops and webinars have increased, with one dedicated online webinar in January 2023, and a common session with another similar EU project at a European conference in August 2023. Popular articles, podcasts and 8 scientific publications have also been completed. Onboarding on the API-Agro platform for data sharing and exploitation of results is on-going, with UK pilot data already available.
The outputs of the project are expected to be:
1. ready to use innovative digital solutions for SR welfare management
2. guidelines for adapted solutions not yet ready for wide adoption or deployment at larger scale.
The project expects to:
• Provide a better understanding of animal welfare and associated animal behaviour
• Offer a broader range of animal welfare management strategies and tools
• Assist in developing innovative approaches to measuring animal welfare at various stages of the production system
• Increase the sustainability of the SR sector
1. ready to use innovative digital solutions for SR welfare management
2. guidelines for adapted solutions not yet ready for wide adoption or deployment at larger scale.
The project expects to:
• Provide a better understanding of animal welfare and associated animal behaviour
• Offer a broader range of animal welfare management strategies and tools
• Assist in developing innovative approaches to measuring animal welfare at various stages of the production system
• Increase the sustainability of the SR sector