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SmartCow: an integrated infrastructure for increased research capability and innovation in the European cattle sector

Periodic Reporting for period 3 - SmartCow (SmartCow: an integrated infrastructure for increased research capability and innovation in the European cattle sector)

Reporting period: 2021-02-01 to 2022-04-30

Livestock production is vitally important for Europe’s future (€168 billion annually to the EU economy - 45% of the agricultural sector, employment for nearly 30 million people), with a projected 70% increase in the worldwide demand for meat and dairy products by 2050. However, the need to improve resource use efficiency, reduce GHG emissions and improve animal health and welfare has been highlighted by the EU, Animal Task Force, FAO and GRA GHG. There is also a major challenge for the EU cattle research community to maintain its international scientific leadership. In this context, coordination, harmonisation and accessibility of European Research Infrastructures (RIs) are essential to support research and innovation for cattle, and to contribute to a sustainable, smart and competitive Europe.
SmartCow was the first successful attempt to integrate key European cattle RIs. Covering all the relevant scientific fields and the diversity of cattle types and production systems, SmartCow networked RIs, improved research methods and reinforced ethical principles in cattle research, and provided academic and private research communities with easy access to high quality services and resources.
Networking activities have created a portal to key European cattle RIs. Mapping of cattle infrastructures has allowed RIs to be readily identifiable on an interactive map on the SmartCow website ( This map represents both consortium (18 facilities) and non-consortium members (41 facilities) together with information about each facility. A database was developed to allow SmartCow members to gain a more in-depth knowledge about each RIs infrastructure, database management systems, and equipment available. We continue to gather more information on non-consortium RIs.
The Transnational Access (TNA) programme has provided access to leading cattle research facilities for 24 projects (9,482 experimental cow-weeks) from 47 proposals submitted in cattle production, nutrition, physiology and smart farming technologies. The projects came from 11 European countries (DE, CH, AT, FR, GB, DK, SP, IE, NO, MK, BG), 9 were led by academic research groups and 15 by industry; there was an even gender balance amongst project leads and it was pleasing to extend provision to two teams based in eastern Europe.
The book “Methods in cattle physiology and behaviour research – Recommendations from the SmartCow consortium” was published online in open access ( Twenty-one chapters provide guidelines for improvement of ethics in cattle experiments and measurement of anatomic, digestive, metabolic, and behavioural traits. To improve data management according to FAIR principles, a cloud-based data platform and data catalogue allow upload, sharing and control of historical data and all data produced during the project. To standardize the vocabulary and link measurements made in the RIs, animal trait and environmental ontologies were extended with the addition of 190 and 40 new traits, respectively.
Joint research activities developed and validated less-invasive methods and high-throughput phenotyping. Meta-analysis of existing measurements of N balance and methane emission showed that N balance measurements were subject to significant variance associated with research site, but methane measurements were more comparable across facilities. New equipment for conducting trials that improved animal and staff welfare were developed. Sources of variation in measurements of digestion, N balance, and methane emission were identified at each SmartCow facility and addressed. The importance of staff and student training and adherence to protocols was highlighted.
A large database, built between SmartCow partners and non-partners, of individual phenotypes of feed efficiency, emissions and proxies from easily accessible matrices (milk, faeces, blood, breath gas, urine) allowed significant progress for high throughput phenotyping: 1) 15N abundance in animal proteins to discriminate dietary treatments and individual variation in feed efficiency of beef cattle and nitrogen use efficiency of dairy cattle, 2) faecal near-infrared spectra (NIRS) showed potential for estimating methane emissions of non-lactating animals, 3) milk mid-infrared spectra (MIRS) models to predict enteric methane emissions in dairy cows were validated.
Sensors are now commonly used to characterise animal behaviour. For SmartCow data, feeding behaviour explained 27% of the feed efficiency of cows. The slower the cow eats and the more variable its feeding frequency, the more efficient the cow is. Behaviour before calving can predict 38% of the variability in health disorders: The more a cow shows cyclic patterns of activity before calving, the better its health after calving. Finally, machine learning allows to discriminate cow states (oestrus, calving, mastitis, lameness, stress) from their behaviour: The results open possibilities for refining animal selection and supporting farm management.
The dissemination and exploitation of project results combined: i) active website and presence on social media; ii) publication of 8 e-newsletters and 3 press releases; iii) 4 meetings of the European Stakeholder Platform, and 5 stakeholders’ workshops; iv) 5 peer reviewed publications (plus 1 accepted for publication) and 21 chapters in the book of methods; v) 43 oral communications and 22 poster presentations in international conferences; vi) 2 face to face training courses and 11 webinars; and vii) involvement in the Common Dissemination Booster “Fitter Livestock Farming”, with 5 other H2020 projects.
To sustain the SmartCow consortium after the H2020 project a consortium agreement to constitute the SmartCow European Research Group (ERG) was signed and the SmartCow consortium is part of the INFRA-SERV project AgroServ.
Networking of cattle RIs was developed for the first time at European scale. The mapping of RIs and the published “Book of Methods” will help operators of related facilities to develop synergies and complementary capabilities, leading to improved and harmonised services. They will also promote the use of ethical principles to guide the design of animal experimentations.
The involvement of industry organisations in the stakeholder platform (19 organisations at the last meeting) and in the TNA projects (including 6 SMEs) fosters innovation through a reinforced partnership with research organisations.
The success of the training courses (more than 100 attendees face-to-face and 200 to the webinars) and the involvement of 11 PhD and post-doc researchers in TNA projects and in JRA educated a new generation of researchers to exploit optimally all the essential tools for their research.
Closer interactions between researchers in SmartCow RIs, new collaborations with other research organisations or networks (e.g. GRA FNN, Agroscope in Switzerland, Luke in Finland) and with TNA beneficiaries has facilitated cross-disciplinary exchanges and a wider sharing of information.
Refined reference methods, consolidated and new proxies, and descriptors of activity from sensors will improve phenotyping capabilities of RIs. This will help the cattle sector to develop innovative and ethical solutions for efficient use of animal and feed resources that promote animal welfare and healthy livestock, as well as sustainable competitiveness.
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