Energy Consumption on Dairy Farms: A Review of Monitoring, Prediction Modelling, and Analyses
Energy Consumption on Dairy Farms: A Review of Monitoring, Prediction Modelling, and Analyses
复制标题
奶牛场能源消耗：监测、预测建模和分析综述
作者：
P. Shine;J. Upton;P. Sefeedpari;M. D. Murphy
预计到2050年，全球乳制品消费量将人均增长19%。然而，牛奶生产是一个高能耗的过程。再加上对全球农业温室气体排放的担忧，增加牛奶产量必须与能源的可持续利用相结合，以确保乳制品行业未来的货币和环境可持续性。本文主要从监测、预测建模和分析的角度总结和回顾了乳制品能量研究。文献中的总一次能源消耗值从有机奶牛养殖系统的2.7 MJ kg−1能量校正牛奶到传统奶牛养殖系统的4.2 MJ kg−1能量校正牛奶不等。根据是否采用封闭或牧场系统，进一步评估了总的一次能源需求的差异。总体而言，由于采用基于牧场的乳制品系统，在文献中可以看到35%的能量减少。与标准回归方法相比，由于采用了各种机器学习算法，在能源文献中已经证明了预测精度的提高。乳制品能量预测模型在文献中经常用于进行乳制品能量分析，以估计基础设施设备和管理实践变化的影响。
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.