Prendergast Ryan, Murphy Michael D, Buckley Fergal, Browne Martin, Upton John
Teagasc Livestock Systems Department, Animal & Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork P61 P302, Ireland; Department of Process, Energy and Transport Engineering, Munster Technological University, Co. Cork T12 P928, Ireland.
Department of Process, Energy and Transport Engineering, Munster Technological University, Co. Cork T12 P928, Ireland.
J Dairy Sci. 2024 Dec;107(12):11036-11051. doi: 10.3168/jds.2024-24796. Epub 2024 Aug 31.
International trends of increasing dairy herd sizes coupled with scarcity of labor have necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data were used from 592 milkings across 26 farms (16 herringbones and 10 rotaries). The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator), and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACR), feeders, entry gates, rapid exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine variations in infrastructure, automations, and management practices. Fourth quartile (Q4) herringbones based on cows/h per operator values averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. The Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on first quartile parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size were likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACR significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested that lower CT values (i.e., rotation speed) resulted in increased milking efficiency. Overall, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors.
国际上奶牛养殖规模不断扩大且劳动力短缺的趋势,使得提高奶牛生产系统的劳动效率成为必要。本研究量化了基础设施、自动化和管理实践对爱尔兰牧场型农场使用的鱼骨式和转盘式挤奶厅的挤奶及操作人员效率的影响。数据来自26个农场的592次挤奶(16个鱼骨式和10个转盘式)。每小时挤奶的奶牛数量(头/小时)、每个操作人员每小时挤奶的奶牛数量(头/小时·操作人员)以及每小时收获的牛奶升数(升/小时)等指标描述了挤奶效率。每头奶牛的总处理时间(TPT,秒/头)、每头奶牛的牛奶处理时间(MPT,秒/头)、工作常规时间(WRT,秒/头)、奶杯组时间(CT,秒/奶杯组)以及每头奶牛的附着时间(ATC,秒/头)等指标描述了操作人员效率。所研究的自动化设备包括后挡板门、奶杯组冲洗、设备清洗、奶杯组移除器(ACR)、喂料器、入口门、快速出口和乳头喷雾。还研究了挤奶时额外操作人员的情况。根据每个操作人员每小时挤奶的奶牛数量,将鱼骨式和转盘式挤奶厅分为四分位数,以研究基础设施、自动化和管理实践的差异。基于每个操作人员每小时挤奶的奶牛数量处于第四四分位数(Q4)的鱼骨式挤奶厅,平均每个操作人员每小时挤奶93头奶牛,平均系统规模为24个奶杯组,有5种挤奶厅自动化设备。Q4的转盘式挤奶厅平均每个操作人员每小时挤奶164头奶牛,平均系统规模为47个奶杯组,平均CT为13秒/奶杯组。Q4的鱼骨式和转盘式挤奶厅每个操作人员每小时挤奶的奶牛数量分别比第一四分位数挤奶厅高出82%和54%,表明提高效率有很大潜力。为了确定挤奶时的基础设施、自动化设备或额外操作人员是否显著影响操作人员效率,建立了一般线性混合模型。对于挤奶厅基础设施,额外的奶杯组对鱼骨式挤奶厅的操作人员效率(MPT)有更大影响(-1.3秒/头),而对转盘式挤奶厅的影响较小(-0.2秒/头)。因此,系统规模的增加可能会提高鱼骨式挤奶厅的效率,但对转盘式挤奶厅的效果较小。对于自动化设备,ACR分别使鱼骨式挤奶厅的TPT、CT和WRT值显著降低13.3秒/头、18.9秒/奶杯组和32.6秒/头,而快速出口使CT显著降低18.6秒/奶杯组。我们发现使用自动乳头喷雾器对转盘式挤奶厅的TPT、MPT、CT或WRT值没有显著影响。挤奶时额外的操作人员显著降低了鱼骨式挤奶厅的TPT,但对MPT或CT没有影响。对于转盘式挤奶厅,第二名操作人员对TPT、MPT、CT或WRT值没有显著影响。我们记录了鱼骨式(-0.91,-0.84)和转盘式(-0.98,-0.89)挤奶厅操作人员效率(TPT,MPT)与挤奶效率(头/小时)之间的强负相关。鱼骨式挤奶厅自动化设备数量与TPT(-0.80)、MPT(-0.72)和CT(-0.75)之间的强负相关表明,高度自动化的挤奶厅可能比自动化程度较低的挤奶厅实现更高的操作人员效率。转盘式挤奶效率(头/小时)与CT之间的强负相关(-0.81)表明,较低的CT值(即旋转速度)会提高挤奶效率。总体而言,我们的研究量化了挤奶厅基础设施、自动化和管理实践对鱼骨式和转盘式挤奶厅挤奶及操作人员效率的影响。