Department of Animal Science, University of Minnesota, St. Paul 55108.
University of Minnesota Extension, St. Cloud 56301.
J Dairy Sci. 2018 Sep;101(9):8327-8334. doi: 10.3168/jds.2017-14297. Epub 2018 Jun 13.
The objective of this study was to identify housing and management factors associated with productivity on automatic milking system (AMS) dairy farms measured as daily milk yield/AMS and daily milk yield/cow. Management, housing, and lameness prevalence data were collected from 33 AMS farms in Minnesota and Wisconsin during a farm visit. All farms in the study used free-flow cow traffic. Mixed model analysis of cross-sectional data showed that farms with automatic feed push-up via a robot produced more milk per AMS/day and per cow/day than farms where feed was pushed up manually. New versus retrofitted facility, freestall surface, manure removal system, and the number of AMS units/pen were not associated with daily milk yield per AMS or per cow. Cow comfort index (calculated as number of cows lying down in stalls divided by total number of cows touching a stall) was positively associated with daily milk yield/cow. Prevalence of lameness and severe lameness, number of cows per full-time employee, depth of the area in front of the AMS milking station, and length of the exit lane from the AMS milking station were not associated with daily milk yield per AMS or per cow. Multivariable mixed model analysis of longitudinal AMS software data collected daily over approximately an 18-mo period from 32 of the farms found a positive association between daily milk yield/AMS and average age of the cows, cow milking frequency, cow milking speed, number of cows/AMS, and daily amount of concentrate feed offered/cow in the AMS. Factors negatively associated with daily milk yield/AMS were number of failed and refused cow visits to the AMS, treatment time (the time spent preparing the udder before milking and applying a teat disinfectant after milking), and amount of residual concentrate feed/cow. Similar results were also found for daily milk yield on a per cow basis; however, as it would be expected, average days in milk of the herd were also negatively associated with daily milk yield/cow. These findings indicate that several management and cow factors must be managed well to optimize AMS productivity.
本研究旨在确定与自动挤奶系统 (AMS) 奶牛场生产力相关的住房和管理因素，以 AMS 日产奶量/头和 AMS 日产奶量/头来衡量。在农场访问期间，从明尼苏达州和威斯康星州的 33 个 AMS 农场收集了管理、住房和跛行流行率数据。研究中的所有农场都使用了自由流动的奶牛流量。横断面数据的混合模型分析表明，通过机器人自动推送饲料的农场比手动推送饲料的农场 AMS 日产量和日产奶量更高。新设施与改造设施、卧床表面、粪便清除系统以及 AMS 单元/栏的数量与 AMS 日产量或日产奶量无关。奶牛舒适度指数（根据卧床中躺下的奶牛数量与接触卧床的奶牛总数之比计算）与奶牛日产奶量呈正相关。跛行和严重跛行的流行率、每全职员工的奶牛数量、AMS 挤奶站前方区域的深度以及 AMS 挤奶站出口车道的长度与 AMS 日产量或日产奶量无关。从 32 个农场中每天收集的大约 18 个月的 AMS 软件纵向数据的多变量混合模型分析发现，AMS 日产量与奶牛的平均年龄、奶牛挤奶频率、奶牛挤奶速度、奶牛/AMS 数量以及 AMS 中提供的每日浓缩饲料量呈正相关。与 AMS 日产量呈负相关的因素是 AMS 奶牛访问失败和拒绝的次数、挤奶前准备乳房的时间（挤奶前准备乳房和挤奶后应用乳头消毒剂的时间）以及奶牛残留浓缩饲料的量。基于每头奶牛的日产奶量也得出了类似的结果；然而，正如预期的那样，牛群的平均泌乳天数也与奶牛日产奶量呈负相关。这些发现表明，必须很好地管理几个管理和奶牛因素，以优化 AMS 的生产力。
