Effect of mobility score on milk yield and activity in dairy cattle

Reader, Jon; Green, Michael J.; Kaler, Jasmeet; Mason, Sarah; Green, Laura

doi:10.3168/jds.2011-4415

Cited by 79 publications

(60 citation statements)

References 18 publications

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“…Asymmetric gait was assessed using a 4-point scale adapted from DairyCo (Kenilworth, UK; Reader et al, 2011): score 1 = even, long, and fluid strides (nonlame); score 2 = uneven steps, but the limbs favored were not obvious (nonlame); score 3 = 1 or more limbs favored obviously (lame); and score 4 = very reluctant to put weight on 1 or more limbs (severely lame). The first and the second author did an agreement study in the first week of the trial, whereas all gait scores used in the models were from the first author.…”

Section: Data Collectionmentioning

confidence: 99%

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

García

Klaas²,

Amigo

et al. 2014

Journal of Dairy Science

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Lameness causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods. Eighty variables retrieved from AMS were summarized week-wise and used to predict 2 defined classes: nonlame and clinically lame cows. Variables were represented with 2 transformations of the week summarized variables, using 2-wk data blocks before gait scoring, totaling 320 variables (2 × 2 × 80). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3 or 4/4) or not lame (score 1/4). Both models achieved sensitivity and specificity values around 80%, both in calibration and cross-validation. At the optimum values in the receiver operating characteristic curve, the false-positive rate was 28% in the parity 1 model, whereas in the parity 2 model it was about half (16%), which makes it more suitable for practical application; the model error rates were, 23 and 19%, respectively. Based on data registered automatically from one AMS farm, we were able to discriminate nonlame and lame cows, where partial least squares discriminant analysis achieved similar performance to the reference method.

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Section: Data Collectionmentioning

confidence: 99%

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

García

Klaas²,

Amigo

et al. 2014

Journal of Dairy Science

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“…Yet, achieving common understanding between farmers and veterinarians has been a recurrent discussion theme among international experts, because farmers underestimate lameness prevalence and its economic effect (Whay et al, 2002;Amory et al, 2006;Borderas et al, 2008). Some studies suggest that most farmers do not assess lameness as logically, nor as consistently, experienced and inexperienced observers achieved relatively high within-observer agreement on video mobility scoring of dairy cows e. Garcia ,* † 1 K. König ,* B. H. allesen-Holm , ‡ I. C. Klaas ,* J. m. amigo , † r. Bro , † and C. enevoldsen * 4561 as a trained researcher (Reader et al, 2011). Possible explanations for this could be insufficient training of the farm personnel to detect lame cows and absence of direct financial incentives or lack of motivation to reduce lameness prevalence.…”

Section: Introductionmentioning

confidence: 99%

Experienced and inexperienced observers achieved relatively high within-observer agreement on video mobility scoring of dairy cows

García

Konig

Allesen-Holm

et al. 2015

Journal of Dairy Science

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Assessment of lameness prevalence and severity requires visual evaluation of thelocomotion of a cow. Welfare schemes including locomotion assessments are increasingly being adopted, and more farmers and their veterinarians might implement a locomotion-scoring routine together. However, high within-observer agreement is a prerequisite for obtaining valid mobility scorings, and within-observer agreement cannot be estimated in a barn, because the gait of cows is dynamic and may change between 2 occasions. The objective of this study was to estimate the within-observer agreement according to the observers' educational background and experience with cattle, based on video recordings with very diverse types of gait. Groups of farmers, bovine veterinarians, first- and fourth-year veterinary students, researchers, and cattle-inexperienced sensory assessors evaluated mobility using a 5-point mobility score system developed specifically for walking cows (n=102 observers). The evaluation sessions were similar for all groups, lasted 75 min, and were organized as follows: introduction, test A, short training session, break, and test B. In total, video recordings of 22 cows were displayed twice in a random order (11 cows in each test × 2 replicates). Data were analyzed applying kappa coefficient, logistic regression, and testing for random effects of observers. The crude estimates of 95% confidence interval for weighted kappa in test A and B ranged, respectively, from 0.76 to 0.80 and 0.70 to 0.75. When adjusting for the fixed effects of video sample and gait scoring preferences, the probability of assigning the same mobility score twice to the same cow varied from 55% (sensory assessors) to 72% (fourth-year veterinary students). The random effect of the individual observers was negligible. That is, in general observers could categorize the mobility characteristics of cows quite well. Observers who preferred to assess the attributes back arch or the overall mobility score (based on uneven gait) had the highest agreement, respectively, 69 or 68%. The training session seemed insufficient to improve agreement. Nonetheless, even novice observers were able to achieve perfect agreement up to 60% of the 22 scorings with merely the experience obtained during the study (introduction and training session). The relatively small differences between groups, together with a high agreement, demonstrate that the new system is easy to follow compared with previously described scoring systems. The mobility score achieves sufficiently high within-observer repeatability to allow between-observer agreement estimates, which are reliable compared with other more-complex scoring systems. Consequently, the new scoring scale seems feasible for on-farm applications as a tool to monitor mobility within and between cows, for communication between farmers and veterinarians with diverse educational background, and for lamenessbenchmarking of herds.

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“…Claw horn disruption lesions (CHDL: sole hemorrhage, sole ulcer, and white line disease) cause a large proportion of lameness in dairy cattle and have a high rate of recurrence (Hirst et al, 2002;Reader et al, 2011;Green et al, 2014). These diseases are prevalent in developed dairy systems worldwide (Barker et al, 2007;Dippel et al, 2009;Foditsch et al, 2016), significantly affect cow welfare and farm profitability (Booth et al, 2004;Sogstad et al, 2006;Cha et al, 2010), and have a plethora of associated risk factors (Cramer et al, 2009;Chapinal et al, 2013;Solano et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

A prospective cohort study of digital cushion and corium thickness. Part 1: Associations with body condition, lesion incidence, and proximity to calving

Newsome

Green

Bell

et al. 2017

Journal of Dairy Science

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Effect of mobility score on milk yield and activity in dairy cattle

Cited by 79 publications

References 18 publications

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

Experienced and inexperienced observers achieved relatively high within-observer agreement on video mobility scoring of dairy cows

A prospective cohort study of digital cushion and corium thickness. Part 1: Associations with body condition, lesion incidence, and proximity to calving

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