Energy Consumption on Dairy Farms: A Review of Monitoring, Prediction Modelling, and Analyses

Philip Shine, John Upton, Paria Sefeedpari and Michael D. Murphy
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Philip Shine: Department of Process, Energy and Transport Engineering, Cork Institute of Technology, Cork T12 P928, Ireland
John Upton: Animal and Grassland Research and Innovation Centre, Teagasc Moorepark Fermoy, Cork P61 C996, Ireland
Paria Sefeedpari: Wageningen Livestock Research, Wageningen University and Research, 6708 WD Wageningen, The Netherlands
Michael D. Murphy: Department of Process, Energy and Transport Engineering, Cork Institute of Technology, Cork T12 P928, Ireland

Energies, 2020, vol. 13, issue 5, 1-25

Abstract: The global consumption of dairy produce is forecasted to increase by 19% per person by 2050. However, milk production is an intense energy consuming process. Coupled with concerns related to global greenhouse gas emissions from agriculture, increasing the production of milk must be met with the sustainable use of energy resources, to ensure the future monetary and environmental sustainability of the dairy industry. This body of work focused on summarizing and reviewing dairy energy research from the monitoring, prediction modelling and analyses point of view. Total primary energy consumption values in literature ranged from 2.7 MJ kg −1 Energy Corrected Milk on organic dairy farming systems to 4.2 MJ kg −1 Energy Corrected Milk on conventional dairy farming systems. Variances in total primary energy requirements were further assessed according to whether confinement or pasture-based systems were employed. Overall, a 35% energy reduction was seen across literature due to employing a pasture-based dairy system. Compared to standard regression methods, increased prediction accuracy has been demonstrated in energy literature due to employing various machine-learning algorithms. Dairy energy prediction models have been frequently utilized throughout literature to conduct dairy energy analyses, for estimating the impact of changes to infrastructural equipment and managerial practices.

Keywords: dairy; energy; review; modelling; efficiency; sustainable agriculture; machine-learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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