Dairy Science Group, School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Camden, NSW 2567, Australia.
NSW Department of Primary Industries, Menangle, NSW 2568, Australia.
J Dairy Sci. 2020 Sep;103(9):8231-8240. doi: 10.3168/jds.2020-18317. Epub 2020 Jun 26.
Automatic milking systems (AMS) have the potential to increase dairy farm productivity and profitability; however, adoption rates, particularly in pasture-based systems, have been lower than expected. The objectives of this study were to compare the physical and economic performance of pasture-based AMS with conventional milking systems (CMS) and to identify gaps for improving AMS productivity and profitability. We used data from 14 AMS and 100 CMS located in the main Australian dairy regions and collected over 3 yr (2015-2016, 2016-2017, 2017-2018). Farms within similar regions and herd sizes were compared. Results showed that all the main physical performance indicators evaluated such as milk production per cow, milk production per hectare, pasture grazed per hectare, or milk solids per full-time equivalent were similar between systems. The AMS farms had higher overhead costs such as depreciation and repairs and maintenance; however, no differences in total labor costs were observed between systems. Profitability, measured as earnings before interest and tax, operating profit margin, and return on total assets, was not significantly different between AMS and CMS. Opportunities for improving pasture utilization, labor efficiency, and robot utilization in AMS farms were identified. Improving efficiency in these areas could improve productivity and profitability of these systems, and therefore increase the interest of this technology.
自动挤奶系统 (AMS) 有可能提高奶牛场的生产力和盈利能力;然而,其采用率,特别是在基于牧场的系统中,一直低于预期。本研究的目的是比较基于牧场的 AMS 与传统挤奶系统 (CMS) 的物理和经济性能,并确定提高 AMS 生产力和盈利能力的差距。我们使用了来自澳大利亚主要奶牛养殖区的 14 个 AMS 和 100 个 CMS 的数据,这些数据是在 3 年期间(2015-2016、2016-2017、2017-2018)收集的。对具有类似地区和牛群规模的农场进行了比较。结果表明,评估的所有主要物理性能指标,如每头牛的产奶量、每公顷的产奶量、每公顷牧场的放牧量或每全职当量的奶固体,在系统之间都是相似的。AMS 农场的折旧和维修等间接费用较高;然而,系统之间的总劳动力成本没有差异。以税前收益、营业利润率和总资产回报率衡量的盈利能力在 AMS 和 CMS 之间没有显著差异。确定了提高 AMS 农场牧草利用率、劳动力效率和机器人利用率的机会。提高这些领域的效率可以提高这些系统的生产力和盈利能力,从而提高对这项技术的兴趣。