VistaMilk is, for the first time, linking the Irish Agri-Food industry with Ireland’s leading technology research institutes in a large-scale innovation ecosystem to address the complex challenges being faced by the sector. The VistaMilk Centre has the potential to nurture a burgeoning Agri–Tech industry, stimulating high technology employment in both the dairy and ICT sectors. The Centre is providing the scale and skills to deliver this agenda. The confluence of ICT and dairy industry expertise in the creation of a single coherent research agenda brings together two of the highest performing export industries in Ireland and provides a Centre where problem statements and solutions can be explored and process improvements developed and deployed.
3 THEMATIC AREAS
In addressing the three thematic areas, VistaMilk will combine biological sciences with cutting edge information communications technology (ICT) areas through its research platforms of enabling technologies.
The Platform research focuses on fundamental research and does not include industry partners.
Objective: To develop new integrated smart-sensor systems, using nanoelectrochemical /spectroscopic /MEMS devices for different modalities which will be integrated in parallel where appropriate, to provide orthogonal sensing results; ensuring more robust results by reducing false positives/negatives (e.g., electrochemical sensors combined with surface-enhanced Raman sensors will provide both quantitative data with molecular fingerprint identification).
Objective: To develop energy efficient wireless communication systems on the farms as well as animals that will enable efficient use of Internet of Things (IoT) in Agri-Tech. The platform research will also investigate new paradigms of molecular and nano communications that can be utilized in Agri-Tech, redefining IoT as the Internet of Bio-Nano Things.
Objective: Supporting the generation and analysis of omic data in the different targeted project while also advancing the state-of-the-art in the analytics underpinning an improved understanding of complex biological systems
Objective: To develop and apply machine learning and statistical modelling techniques, across the dairy supply chain, to predict optimal outcomes for pasture, for cows, and eventually for food production.
Integration and Deployment
Objective: The objective of Deployment is to deploy a range of tools and methodologies that can be used to increase the sustainability of the dairy industry
Spoke research has at least one industry partner involved. Within each Spoke there can be a number of Targeted Projects, each with at least one Research Performing Organisation (RPO) and one industry partner.
Objective: Develop an improved understanding of the rumen environment and its impact on performance as well as exploiting activity monitors to diagnose animal-level events.
Project leads: Stephen Butler & Sasi Balasubramaniam
Objective: Provide diagnostic options to support sustainable control of priority diseases in dairy herds
Project leads: Emer Kennedy & Alan O’Riordan
Objective: Deliver more accurate genomic predictions for performance in dairy cows.
Project leads: Sinead McParland & Claire Gormley
Objective: To optimise and predict the processing performance of future milk by understanding the contribution of pasture and cow-level factors to compositional variability.
Project leads: John Tobin & Derek Greene
Dairy Production Digestion
Objective: Employ in vitro, ex vivo and in vivo systems to study the (pre-)digestion of new dairy ingredients and their impact on host cells and the gut microbiota.
Project leads: Paul Cotter & Sasitharan Balasubramaniam
Objective: Quantify nutritional attributes & health benefits of dairy products for human nutrition.
Project leads: Catherine Stanton & Paul Cotter
Soil Nutrient Dynamics
Objective: Deliver more accurate predictions of soil nutrient supply to maximise grass growth and minimise losses to the environment.
Project leads: Karen Daly & James Rohan
Objective: Capture accurate real-time information on pasture production, canopy structure/quality, and herbage mineral content for grazing dairy-cows and deploy in pasture decision support tool.
Project leads: Deirdre Hennessy & Daniella Icopino
Objective: Increase the rate of genetic gain in forage breeding to enhance on-farm profitability.
Project leads: Dan Milbourne & Aonghus Lawlor