5 citations · 6 across the 4 of their papers we have counts for
4 papers
Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
Szymon Urbas, Pierre Lovera, Robert Daly +3
High-dimensional spectral data -- routinely generated in dairy production -- are used to predict a range of traits in milk products. Partial least squares (PLS) regression is ubiqu…
Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows
Cathal Ryan, Christophe Guéret, Donagh Berry +3
Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance. The use of AI techniques to identify the early onset of this…
Can We Detect Mastitis earlier than Farmers?
Cathal Ryan, Christophe Guéret, Donagh Berry +1
The aim of this study was to build a modelling framework that would allow us to be able to detect mastitis infections before they would normally be found by farmers through the int…
Block Chain and Internet of Nano-Things for Optimizing Chemical Sensing in Smart Farming
Dixon Vimalajeewa, Subhasis Thakur, John Breslin +2
The use of Internet of Things (IoT) with the Internet of Nano Things (IoNT) can further expand decision making systems (DMS) to improve reliability as it provides a new spectrum of…