Visits were made to 205 dairy farms in England and Wales between October 2006 and May 2007 by 1 or more of 4 researchers. At each visit, all milking cows were locomotion scored (lameness scored) using a 4-point scale (0=sound locomotion, 1=imperfect locomotion, 2=lame, 3=severely lame). The mean prevalence of lameness (scores 2 and 3) across the study farms was 36.8% (range=0-79.2%). On each farm, the presence within the housing and grazing environments of commonly reported risks for increased lameness was recorded. Each farmer was interviewed to gauge the ability of the farm staff to detect and treat lameness. A multivariable linear regression model was fitted. Risk factors for increased lameness were the presence of damaged concrete in yards, cows pushing each other or turning sharply near the parlor entrance or exit, cattle grazing pasture also grazed by sheep, the use of automatic scrapers, not treating lame cows within 48h of detection, and cows being housed for 61 d or longer at the time they were locomotion scored by the visiting researcher. Having a herd consisting entirely of a breed or breeds other than Holstein-Friesian was associated with a reduction in lameness prevalence compared with having a herd consisting entirely of Holstein-Friesians.

The preliminary findings from an investigation into the health and welfare of goats on commercial dairy goat farms in the UK are described. An assessment protocol involving direct observations of the goats was developed in order to assess their welfare. Twenty-four dairy goat farms in England and Wales were visited and assessed during the period autumn 2004 to summer 2005. The main welfare issues identified were lameness and claw overgrowth, udder and teat lesions, skin lesions and pruritus.

Background: Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results: Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines.

Lameness is one of the most significant endemic disease problems facing the dairy industry. Claw horn lesions (principally sole hemorrhage, sole ulcer, and white line disease) are some of the most prevalent conditions. Despite the fact that thousands of animals are treated for these conditions every year, experimental evidence is limited on the most effective treatment protocols. A randomized, positively controlled clinical trial was conducted to test the recovery of newly lame cows with claw horn lesions. Animals on 5 farms were locomotion scored every 2wk. Cows were eligible for recruitment if they had 2 nonlame scores followed by a lame score and had a claw horn lesion on a single claw of a single foot. Following a therapeutic trim, enrolled cows were randomly allocated to 1 of 4 treatments: treatment 1-no further treatment (positive control; TRM), treatment 2-trim plus a block on the sound claw (TB), treatment 3-trim plus a 3-d course of the nonsteroidal anti-inflammatory drug (NSAID) ketoprofen (TN), treatment 4-trim plus a block plus ketoprofen (TBN). The primary outcome measure was locomotion score 35d after treatment, by an observer blind to treatment group. Descriptive statistics suggested that treatment groups were balanced at the time of enrollment, that is, randomization was successful. Based on a sound locomotion score (score 0) 35d after treatment, the number of cures was 11 of 45 (24.4%) for TRM, 14 of 39 (35.9%) for TB, 12 of 42 (28.6%) for TN, and 23 of 41 (56.1%) for TBN. The difference between TBN and TRM was significant. To test for confounding imbalances between treatment groups, logistic regression models were built with 2 outcomes, either sound (score 0) or nonlame (score 0 or 1) 35d after treatment. Compared with TRM, animals that received TBN were significantly more likely to cure to a sound outcome. Farm, treatment season, lesion diagnosis, limb affected, treatment operator, and stage of lactation were included in the final models. Our work suggests that lameness cure is maximized with NSAID treatment in addition to the common practices of therapeutic trimming and elevation of the diseased claw using a block when cows are newly and predominantly mildly lame.

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