Machine-learning algorithms for predicting on-farm direct water and electricity consumption on pasture based dairy farms P Shine, MD Murphy, J Upton, T Scully Computers and electronics in agriculture 150, 74-87, 2018 | 80 | 2018 |
Energy consumption on dairy farms: A review of monitoring, prediction modelling, and analyses P Shine, J Upton, P Sefeedpari, MD Murphy Energies 13 (5), 1288, 2020 | 66 | 2020 |
Multiple linear regression modelling of on-farm direct water and electricity consumption on pasture based dairy farms P Shine, T Scully, J Upton, MD Murphy Computers and electronics in agriculture 148, 337-346, 2018 | 58 | 2018 |
Technical, environmental and cost-benefit assessment of manure management chain: A case study of large scale dairy farming P Sefeedpari, T Vellinga, S Rafiee, M Sharifi, P Shine, ... Journal of cleaner production 233, 857-868, 2019 | 50 | 2019 |
Electricity & direct water consumption on Irish pasture based dairy farms: A statistical analysis P Shine, T Scully, J Upton, L Shalloo, MD Murphy Applied Energy 210, 529-537, 2018 | 42 | 2018 |
Annual electricity consumption prediction and future expansion analysis on dairy farms using a support vector machine P Shine, T Scully, J Upton, MD Murphy Applied energy 250, 1110-1119, 2019 | 41 | 2019 |
Over 20 years of machine learning applications on dairy farms: A comprehensive mapping study P Shine, MD Murphy Sensors 22 (1), 52, 2021 | 24 | 2021 |
Integration of life cycle assessment, artificial neural networks, and metaheuristic optimization algorithms for optimization of tomato-based cropping systems in Iran SH Pishgar-Komleh, A Akram, A Keyhani, P Sefeedpari, P Shine, ... The International Journal of Life Cycle Assessment 25, 620-632, 2020 | 22 | 2020 |
Effect of introducing weather parameters on the accuracy of milk production forecast models F Zhang, J Upton, L Shalloo, P Shine, MD Murphy Information Processing in Agriculture 7 (1), 120-138, 2020 | 19 | 2020 |
Utilising grassland management and climate data for more accurate prediction of herbage mass using the rising plate meter DJ Murphy, P Shine, BO Brien, MO Donovan, MD Murphy Precision Agriculture 22, 1189-1216, 2021 | 17 | 2021 |
Global dairy sector: trends, prospects, and challenges R Bhat, J Di Pasquale, FI Bánkuti, TTS Siqueira, P Shine, MD Murphy Sustainability 14 (7), 4193, 2022 | 15 | 2022 |
A global review of monitoring, modeling, and analyses of water demand in dairy farming P Shine, MD Murphy, J Upton Sustainability 12 (17), 7201, 2020 | 13 | 2020 |
A Review of Milk Production Forecasting Models: Past & Future Methods F Zhang, P Shine, J Upton, L Shaloo, MD Murphy ResearchGate, 2018 | 5 | 2018 |
Comparing multiple linear regression and support vector machine models for predicting electricity consumption on pasture based dairy farms P Shine, J Upton, T Scully, L Shalloo, MD Murphy 2018 ASABE Annual International Meeting, 1, 2018 | 4 | 2018 |
DSSED: decision support system for energy use in dairy production MD Murphy, P Shine, M Breen, J Upton | 3 | 2021 |
Energy Consumption on Dairy Farms: A Review of Monitoring, Prediction Modelling, and Analyses. Energies 2020, 13, 1288 P Shine, J Upton, P Sefeedpari, MD Murphy | 3 | |
A decision support and optimization platform for energy technology investments on dairy farms P Shine, M Breen, J Upton, A O’Donovan, MD Murphy 2019 ASABE Annual International Meeting, 1, 2019 | 2 | 2019 |
A decision support system for energy use on dairy farms P Shine, M Breen, J Upton, A O’Donovan, MD Murphy Proceedings of the Precision Livestock Farming’19 Conference, 45-52, 2019 | 2 | 2019 |
Global Dairy Sector: Trends, Prospects, and Challenges. Sustainability. 2022; 14 4193 R Bhat, J Di Pasquale, FI Bánkuti, SP SiqueiraTTdS, MD Murphy s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | 1 | 2022 |
The development of a national-level energy assessment tool for the dairy industry P Shine, J Upton, MD Murphy 2022 ASABE Annual International Meeting, 1, 2022 | 1 | 2022 |