ICT in large and small dairy systems
Project information
ICT in large and small dairy systemsCall: ICT and Automation for a Greener Agriculture
Id: 14306
Acronym: DairyICT
Consortium:
No | Partner | Contact | Country | Total 1000€ | Funded 1000€ | Funder |
---|---|---|---|---|---|---|
1 Coord. | Department of Veterinary Clinical and Animal Sciences Department of Large Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen | Chris Knight | Denmark | 86.0 | 15.0 | Danish AgriFish Agency Ministry of Food, Agriculture and Fisheries |
2 | Department of Animal Science Aarhus University | Klaus L. Ingvartsen | Denmark | 270.0 | 142.0 | Danish AgriFish Agency Ministry of Food, Agriculture and Fisheries |
3 | Veterinary Physiology Vetsuisse Faculty Department of Engineering and Information Technology University of Bern | Rupert Bruckmaier | Switzerland | 120.0 | 70.0 | Federal Office for Agriculture - Bundesamt für Landwirtschaft |
4 | Newcastle University School of Agriculture Food and Rural Development | Ilias Kyriazakis | United Kingdom | 11.0 | 0.0 | Department for Environment, Food and Rural Affairs |
5 | Centre for Intelligent Dynamic Communications (CIDCOM) Department of Electronic and Electrical Engineering University of Strathclyde | Ivan Andonovic | United Kingdom | 13.0 | 0.0 | Department for Environment, Food and Rural Affairs |
6 | INRA Research Unit Systemic Modelling applied to Ruminants INRA - Joint research unit on Dairy Production INRA | Nicolas Friggens | France | 289.0 | 202.0 | French National Research Agency |
7 | Department of Animal Medicine, Production and Health, University of Padua | Paolo Berzaghi | Italy | 21.0 | 5.0 | Ministry of Agriculture Food, Forestry & Tourism Policies |
8 | SAC | David Roberts | United Kingdom | 14.0 | 0.0 | Department for Environment, Food and Rural Affairs |
9 | Fermoy Research Directorate Moorepark Dairy Production Research TEAGASC - Agriculture and Food Development Authority | Riona Sayers | Ireland | 150.0 | 5.0 | TEAGASC - Agriculture and Food Development Authority |
This multidisciplinary project seeks to integrate and extend existing state of the art technologies to ensure sustainable and responsible management of dairy units, with focus on cow health, milk quality and reduced emissions. We shall focus on milk metabolomic methods for determination of metabolic health, biomarker technologies for assessment of systemic health and accelerometer collars for measuring various activities including feeding behaviour, and hence intake. We shall also have access to NIR technology for feed quality assessment and rumen-bolus technology for measurment of rumen pH. We have advanced teleonomic technologies that will enable us to integrate these input data into decision support tools. Our technologies will monitor animals and environment, detect deviations from the normal state and either respond automatically to restore the normal state or issue an alert to husbandry staff. We have access to a range of dairy units for evaluation of the technologies.
Partially derived from the outputs obtained from the DairyICT project, the start-up company Silent Herdsman from the University of Strathclyde, Glasgow, was created. Silent Herdsman is an internet of things (IoT)- inspired decision support platform that supports the optimisation of animal husbandry within dairy farms and in turn maximises productivity (milk production, milk quality, health) and welfare. Silent Herdsman developed a tracking system consisting of a neck-mounted collar, which is very accurate, and highly scalable. In 2016, the company Afimilk Ltd (a global leader in farm management software and milk analysis tools for dairy operations in 50 countries) acquired the neck collar developed by Silent Herdsman. The collar allows the tracking of each cow individually and provides alerts related to changes associated with the onset of heat and/or the health of the animal in real time. By analysing the time spent eating and ruminating behaviour patterns for individual animals, Silent Herdsman also provides early indications of illness. The deployment of the collars has proven to decrease the calving index (CI) from 40 days (for poorly performing farms) to 20 days (for high-performing farms). For example, on a UK farm, collar deployment has yielded a 40-day improvement in the CI for a 500-cow herd, which translates to >£100k additional revenue and represents a return on investment within seven months.
- Establishment of a COST Action in Dairy Animal Health and Welfare: FA1308 DairyCare www.dairycareaction.org
- Identification of milk-borne biomarkers indicative of rumen dysfunction
- Demonstration of the potential utility of stress biomarker determination in multiple matrices for assessment of acute and chronic stress
- Development of multi-sensor based predictive models linking lameness, feeding behaviour and rumination time
- Dairy
- Sensing
- Data integration
- Smart systems