TY - JOUR
T1 - Multivariate dynamic linear models for estimating the effect of experimental interventions in an evolutionary operations setup in dairy herds
AU - Stygar, Anna Helena
AU - Krogh, Mogens Agerbo
AU - Kristensen, Troels
AU - Østergaard, Søren
AU - Kristensen, Anders Ringgaard
PY - 2017/7
Y1 - 2017/7
N2 - Evolutionary operations is a method to exploit the association of often small changes in process variables, planned during systematic experimentation and occurring during the normal production flow, to production characteristics to find a way to alter the production process to be more efficient. The objective of this study was to construct a tool to assess the intervention effect on milk production in an evolutionary operations setup. The method used for this purpose was a dynamic linear model (DLM) with Kalman filtering. The DLM consisted of parameters describing milk yield in a herd, individual cows from a herd, and an intervention effect on a given day. The model was constructed to handle any number of cows, experimental interventions, different data sources, or presence of control groups. In this study, data from 2 commercial Danish herds were used. In herd 1, data on 98,046 and 12,133 milkings registered from an automatic milking system (AMS) were used for model building and testing, respectively. In herd 2, data on 3,689 milkings on test days were used for estimating the initial model parameters. For model testing, data from both bulk tank milk yield (85 observations) and test-day milkings (1,471) were used. In herd 1, the manager wanted to explore the possibility of reducing the amount of concentrate provided to the cows in an AMS. In herd 2, the manager wanted to know if the milk yield could be increased by elevating the energy level provided to the cows in a total mixed ration. The experiment conducted in herd 1 was designed with a treatment and a control group, whereas in herd 2 we used a pretest/posttest design. The constructed tool provided estimates (mean and confidence intervals) for each of 3 interventions carried out in both herds. In herd 1, we concluded that the reduction in concentrate amount provided in the AMS had no negative influence on milk yield. For herd 2, the increased level of energy had a significant positive effect on milk yield but only for the first intervention. In this herd, the effect of intervention was also evaluated for cows in the first lactation and without bulk tank records. The presented model proved to be a flexible and dynamic tool, and it was successfully applied for systematic experimentation in dairy herds. The model can serve as a decision support tool for on-farm process optimization exploiting planned changes in process variables and the response of production characteristics.
AB - Evolutionary operations is a method to exploit the association of often small changes in process variables, planned during systematic experimentation and occurring during the normal production flow, to production characteristics to find a way to alter the production process to be more efficient. The objective of this study was to construct a tool to assess the intervention effect on milk production in an evolutionary operations setup. The method used for this purpose was a dynamic linear model (DLM) with Kalman filtering. The DLM consisted of parameters describing milk yield in a herd, individual cows from a herd, and an intervention effect on a given day. The model was constructed to handle any number of cows, experimental interventions, different data sources, or presence of control groups. In this study, data from 2 commercial Danish herds were used. In herd 1, data on 98,046 and 12,133 milkings registered from an automatic milking system (AMS) were used for model building and testing, respectively. In herd 2, data on 3,689 milkings on test days were used for estimating the initial model parameters. For model testing, data from both bulk tank milk yield (85 observations) and test-day milkings (1,471) were used. In herd 1, the manager wanted to explore the possibility of reducing the amount of concentrate provided to the cows in an AMS. In herd 2, the manager wanted to know if the milk yield could be increased by elevating the energy level provided to the cows in a total mixed ration. The experiment conducted in herd 1 was designed with a treatment and a control group, whereas in herd 2 we used a pretest/posttest design. The constructed tool provided estimates (mean and confidence intervals) for each of 3 interventions carried out in both herds. In herd 1, we concluded that the reduction in concentrate amount provided in the AMS had no negative influence on milk yield. For herd 2, the increased level of energy had a significant positive effect on milk yield but only for the first intervention. In this herd, the effect of intervention was also evaluated for cows in the first lactation and without bulk tank records. The presented model proved to be a flexible and dynamic tool, and it was successfully applied for systematic experimentation in dairy herds. The model can serve as a decision support tool for on-farm process optimization exploiting planned changes in process variables and the response of production characteristics.
U2 - 10.3168/jds.2016-12251
DO - 10.3168/jds.2016-12251
M3 - Journal article
C2 - 28456406
SN - 0022-0302
VL - 100
SP - 5758
EP - 5773
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 7
ER -