Punyapornwithaya Veerasak, Sansamur Chalutwan, Singhla Tawatchai, Vinitchaikul Paramintra
Department of Food Animal Clinic, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, 50100, Thailand.
Veterinary Public Health Centre for Asia Pacific, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, 50100, Thailand.
Vet World. 2020 Nov;13(11):2429-2435. doi: 10.14202/vetworld.2020.2429-2435. Epub 2020 Nov 13.
Consistency in producing raw milk with less variation in bulk tank milk somatic cell count (BMSCC) is important for dairy farmers as their profit is highly affected by it in the long run. Statistical process control (SPC) is widely used for monitoring and detecting variations in an industrial process. Published reports on the application of the SPC method to smallholder farm data are very limited. Thus, the purpose of this study was to assess the capability of the SPC method for monitoring the variation of BMSCC levels in milk samples collected from smallholder dairy farms.
Bulk tank milk samples (n=1302) from 31 farms were collected 3 times/month for 14 consecutive months. The samples were analyzed to determine the BMSCC levels. The SPC charts, including the individual chart (I-chart) and the moving range chart (MR-chart), were created to determine the BMSCC variations, out of control points, and process signals for each farm every month. The interpretation of the SPC charts was reported to dairy cooperative authorities and veterinarians.
Based on a set of BMSCC values as well as their variance from SPC charts, a series of BMSCC data could be classified into different scenarios, including farms with high BMSCC values but with low variations or farms with low BMSCC values and variations. Out of control points and signals or alarms corresponding to the SPC rules, such as trend and shift signals, were observed in some of the selected farms. The information from SPC charts was used by authorities and veterinarians to communicate with dairy farmers to monitor and control BMSCC for each farm.
This study showed that the SPC method can be used to monitor the variation of BMSCC in milk sampled from smallholder farms. Moreover, information obtained from the SPC charts can serve as a guideline for dairy farmers, dairy cooperative boards, and veterinarians to manage somatic cell counts in bulk tanks from smallholder dairy farms.
生产体细胞数波动较小的原料奶对于奶农而言至关重要，因为从长远来看，这会极大地影响他们的利润。统计过程控制（SPC）广泛应用于监测和检测工业生产过程中的波动。关于将SPC方法应用于小农户农场数据的已发表报告非常有限。因此，本研究的目的是评估SPC方法监测小农户奶牛场采集的牛奶样本中体细胞数水平波动的能力。
连续14个月，每月3次从31个农场采集总计1302份奶罐牛奶样本。对样本进行分析以测定体细胞数水平。创建了包括单值控制图（I图）和移动极差控制图（MR图）在内的SPC控制图，以确定每个农场每月的体细胞数波动、失控点和过程信号。SPC控制图的解读结果报告给了乳制品合作社管理部门和兽医。
根据一组体细胞数数值及其在SPC控制图中的方差，一系列体细胞数数据可分为不同情况，包括体细胞数高但波动小的农场，或体细胞数低且波动小的农场。在部分选定农场中观察到了与SPC规则相对应的失控点和信号或警报，如趋势和偏移信号。乳制品合作社管理部门和兽医利用SPC控制图中的信息与奶农沟通，以监测和控制每个农场的体细胞数。
本研究表明，SPC方法可用于监测小农户农场采集的牛奶中体细胞数的波动。此外，从SPC控制图获得的信息可为奶农、乳制品合作社委员会和兽医管理小农户奶牛场奶罐中的体细胞数提供指导。
