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

• Main Authors: Philip Shine, John Upton, Paria Sefeedpari, Michael D. Murphy
• Format: Article
• Language: English
• Published: MDPI AG 2020-03-01
• Series: Energies
• Subjects: dairy; energy; review; modelling; efficiency; sustainable agriculture; machine-learning
• Online Access: https://www.mdpi.com/1996-1073/13/5/1288

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.