Risk factors influencing lameness and claw disorders in dairy cows

Bielfeldt, J. C.; Badertscher, René; Tölle, K.-H.; Krieter, Joachim

doi:10.1016/j.livprodsci.2004.12.005

Cited by 45 publications

(72 citation statements)

References 12 publications

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“…The average percentage of lame cows was only 10.5%, which is very close to the threshold (10%) suggested by EFSA (2009) and considerably lower than the percentage of about 50% observed in Italian mountain dairy farms by Battini et al (2010) using the same scoring system. This is a good result, if we consider that cows were of Holstein genetic background (that seems to be one of the more susceptible breeds to this problem; Mattiello et al 2011) and that they never had access to pasture (which is known to have a positive effect on the reduction of the incidence of lameness; Bielfeldt et al 2005;Mattiello et al 2005;Battini et al 2010). Due to the low incidence of lameness, the benchmark values for this variable were set at very high standards (e.g.…”

Section: Thresholds Of Multi-dimensional Assessmentmentioning

confidence: 99%

Multi-dimensional assessment and scoring system for dairy farms

Zucali

Battelli

Battini

et al. 2016

Italian Journal of Animal Science

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The aim of the study is to develop a scoring system for dairy farms in order to give specific information about the product and production process of milk. The scoring system, based on a multi-dimensional approach, was developed on the basis of data collected in 29 Italian dairy farms and included different aspects. For the evaluation of animal welfare, a selection of indicators set up in the European Project V R assessment protocol for cattle 2009 was used. Environmental sustainability of milk production was assessed by a cradle-to-farm-gate Life Cycle Assessment. Laboratory analyses were carried out on bulk tank milk to evaluate microbiological, nutritional and nutraceutical quality. Nineteen variables were selected and retained to define six quality aspects: animal welfare, environmental and economic sustainability of farms, microbiological, nutritional and nutraceutical quality of milk. Each farm was visited twice; each visit received, for each variable, a score between 1 and 3 based on the frequency distribution of that variable in the farm sample. The relation among farm characteristics and quality aspects showed the importance to maximise dairy efficiency to improve environmental and economic sustainability of the farms and the inclusion of hay in dairy cows' ration to enhance the nutraceutical and nutritional quality of milk. The proposed multi-dimensional scoring system is a practical tool: for the farmer, to support decisions for improving the quality of the product and the productive process; for the dairy company, as a value-added opportunity; for the consumer, who receives detailed information about nutritional characteristics and production system of dairy products. ARTICLE HISTORY

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Section: Thresholds Of Multi-dimensional Assessmentmentioning

confidence: 99%

Multi-dimensional assessment and scoring system for dairy farms

Zucali

Battelli

Battini

et al. 2016

Italian Journal of Animal Science

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“…Lameness is widely recognized as a significant welfare problem for cows in free-stalls (von Keyserlingk et al, 2012) and tie-stalls (Bielfeldt et al, 2005;Cramer et 2009) caused by numerous factors including lying comfort, cubicle design, flooring type, time away from the pen for milking, body condition score (BCS), and nutrition Espejo and Endres, 2007). Hock and knee lesions are also common in cattle kept in tie-stalls (Zurbrigg et al, 2005), are more common among lame cattle (Zaffino Heyerhoff et al, 2014) and are also a common welfare concern (Rushen et al, 2008;von Keyserlingk et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Can automated measures of lying time help assess lameness and leg lesions on tie-stall dairy farms?

Charlton

Bouffard

Gibbons

et al. 2016

Applied Animal Behaviour Science

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a b s t r a c tThe time that dairy cows spend lying down is an important measure of their comfort and lameness and injuries to hocks and knees are associated with alterations in lying time. We examined whether automated measures of lying time could identify cows and farms with problems of lameness or leg lesions. Data were collected from 40 lactating Holstein dairy cows from each of 100 tie-stall farms. The occurrence of lameness, hock and knee injuries was recorded and lying times were recorded automatically using accelerometers. There was large variation between individual cows, and between farms in all measures of lying time. At the cow level, there was no relationship (P > 0.10) between being lame and daily duration of lying time. A lower daily duration of lying time was found among cows with hock injuries (mean ± SE: non-injured = 12.79 ± 0.06 h, injured = 12.21 ± 0.06 h; P < 0.001) and cows with knee injuries (mean ± SE: non-injured = 12.54 ± 0.05 h, injured = 12.25 ± 0.06 h; P = 0.04) than those without lesions. The median daily duration of lying time on a farm was negatively correlated with the prevalence of lameness (r p = −0.27, P = 0.006), of hock injuries (r p = −0.35, P = 0.003) and of knee injuries (r p = −0.28, P = 0.004). A canonical discriminant function with canonical coefficients of 0.63 for mean daily duration of lying down, and of 0.54 for mean bout frequency could correctly identify 72% of the farms that were above the median for percent of cows with hock or knee injuries or being lame (linear discriminant function: constant = −95.10, daily duration = 11.39, bout frequency = 4.83) and 68% of the farms below the median (linear discriminant function: constant = −106.95, daily duration = 11.92, bout frequency = 5.30) (Wilks Lambda test P = 0.002). A criterion of a median lying time between 12 h and 13 h alone could identify over 60% of farms above or below the median for lameness, hock and knee lesion prevalence. Automated measures of lying time may be a useful animal-based measure to indicate farms with a high percentage of lame cows or cows with leg lesions.

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“…Cow-level risk factors include parity, trimming season, stage of lactation and breed (Bielfeldt et al, 2005;Capion et al, 2008;Barker et al, 2009). Herd-level risk factors include flooring material, bedding material, feed composition, feeding system, cubicle design, access to pasture, hygiene and claw trimming routines (Vokey et al, 2001;Bielfeldt et al, 2005;Sogstad et al, 2005;Capion et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Bielfeldt et al, 2005). In 2012 almost 75% of Finnish dairy herds were T herds (Matilda Agricultural Statistics, 2014), however, most new herds are L herds and herd size is increasing in Finland.…”

Section: Introductionmentioning

confidence: 99%