Detection model for mastitis in cows milked in an automatic milking system
Detection model for mastitis in cows milked in an automatic milking system
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DOI：
10.1016/s0167-5877(01)00176-3
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发表时间：
2001-04-13
影响因子：
2.6
通讯作者：
Ouweltjes, W
中科院分区：
文献类型：
--
作者：
de Mol, RM;Ouweltjes, W
奶牛疾病（如乳腺炎）的自动检测可能是挤奶过程中通过观察进行检测的替代方法-特别是在使用自动挤奶系统（AMS）时。给出了一个检测模型的轮廓。该检测模型包括两个变量（牛奶产量和牛奶的电导率）的时间序列模型，并对先前的值进行插值。该模型在实际使用的变量数量上是灵活的，参数值和残差方差在每次挤奶后通过线性回归更新。当残差超出给定置信区间时，发出乳腺炎警报。使用111头奶牛16个月的数据集（平均每天58头泌乳奶牛）来测试模型。根据选择的置信区间，48例临床乳腺炎中有42-44例被检测到;其余病例未被检测到，因为并非所有需要的数据都可用。这些结果优于农场通常使用的模型所获得的结果。假阳性警报的数量取决于所选择的置信区间，并且高于通常使用的模型发现的数量。(C)2001 Elsevier Science B. V.保留所有权利。
Automated detection of diseases (such as mastitis) in dairy cows might be an alternative for detection by observation during milking - especially when using an automatic milking system (AMS). An outline of a detection model is given. This detection model includes time-series models for two variables (milk yield and electrical conductivity of milk), with interpolation on previous values. The model is flexible in the number of variables actually used, Parameter values and the residual variances are updated by linear regression after each milking. Alerts for mastitis are given when the residuals fall outside given confidence intervals. A data set with 111 cows for 16 months (on average, 58 lactating cows per day) was used to test the model. Depending on the chosen confidence interval, 42-44 out of 48 cases of clinical mastitis were detected; the remaining cases were not detected because not all data needed were available. These results were better than the results obtained with the model usually used on the farm. The number of false-positive alerts depended on the chosen confidence interval and was higher than the number found with the model usually used. (C) 2001 Elsevier Science B.V. All rights reserved.