Using classification trees to detect induced sow lameness with a transient model

Abstract

Feet and legs issues are some of the main causes for sow removal in the US swine industry. More timely lameness detection among breeding herd females will allow better treatment decisions and outcomes. Producers will be able to treat lame females before the problem becomes too severe and cull females while they still have salvage value. The objective of this study was to compare the predictive abilities and accuracies of weight distribution and gait measures relative to each other and to a visual lameness detection method when detecting induced lameness among multiparous sows. Developing an objective lameness diagnosis algorithm will benefit animals, producers and scientists in timely and effective identification of lame individuals as well as aid producers in their efforts to decrease herd lameness by selecting animals that are less prone to become lame. In the early stages of lameness, weight distribution and gait are impacted. Lameness was chemically induced for a short time period in 24 multiparous sows and their weight distribution and walking gait were measured in the days following lameness induction. A linear mixed model was used to determine differences between measurements collected from day to day. Using a classification tree analysis, it was determined that the mean weight being placed on each leg was the most predictive measurement when determining whether the leg was sound or lame. The classification tree's predictive ability decreased as the number of days post-lameness induction increased. The weight distribution measurements had a greater predictive ability compared with the gait measurements. The error rates associated with the weight distribution trees were 29.2% and 31.3% at 6 days post-lameness induction for front and rear injected feet, respectively. For the gait classification trees, the error rates were 60.9% and 29.8% at 6 days post-lameness induction for front and rear injected feet, respectively. More timely lameness detection can improve sow lifetime productivity as well as animal welfare.

Measure and characterization of lameness in gestating sows using force plate, kinematic, and accelerometer methods1

“…Further research working with animals with an identified lameness problem beforehand or longitudinal studies need to be undertaken to correlate a measure from automated methods to a type of lameness and to determine its threshold value for an accurate diagnosis. This type of longitudinal research has been undertaken in induced-lame sows (Abell et al, 2014) and needs to be developed on sows with naturally occurring lameness to reflect the variety of lameness problems. Table 7.…”

Determining the Time Required to Detect Induced Sow Lameness Using an Embedded Microcomputer-Based Force Plate System

“…Records were excluded from the data set based on the following criteria: 1 (2) if individually both front legs or both rear legs of the sow weighed less than 4.5 kg; or (3) if any foot individually weighed less than 0 kg. These criteria were previously used by Abell et al (2014) to indicate that the sow's feet were not properly positioned on each quadrant of the force plate. When the feet are not positioned correctly, the measurements recorded are not an accurate representation of the sow's weight distribution.…”

“…The P95 provides a more robust value for the maximum force applied by the sow, since extreme values occurred when the sow pushed up on the feed trough or adjusted her weight. These values were also used by Abell et al (2014) to develop a lameness classification tree from sows' force distributions.…”

“…The embedded microcomputer-based force plate system developed by Sun et al (2011), hereafter referred to as force plate, was designed for placement under an electronic single space feeder or a gestation stall. Previous research demonstrated the force plate's capacity to detect induced sow lameness by measuring separately the weight she is willing to bear on each leg during 5, 15 and 30 min tests (Sun et al, 2011;Karriker et al, 2013;Pluym et al, 2013;Abell et al, 2014;Mohling et al, 2014). The average occupation time required for a sow to consume her daily feed allotment is 9.2 to 14.2 min, however, this may be across multiple feedings (Olsson et al, 2011).…”

Evaluation of diagnostic tools for naturally occurring lameness in swine

“…Abell and others compared of the predictive abilities and accuracies of weight distribution and gait measures relative to one another and to visual lameness methods on induced sow lameness. They found that weight distribution measurements had a higher predictive ability than the gait measurements (Abell et al 2014). Lastly, a study by Bertholle and colleagues investigated the use of radiographs, a visual lameness scoring scheme and a quantitative pressure-mat bases locomotion analysis system.…”