The pressure distribution under the bovine claw while walking was measured to test the hypotheses that the vertical ground reaction force is unevenly distributed and makes some (regions of the) claws more prone to injuries due to overloading than others. Each limb of nine recently trimmed Holstein Friesian cows was measured five times while walking over a Footscan pressure plate firmly embedded on a Kistler force plate. The pressure plate had a spatial resolution of 2.6 sensors/cm2 and was sampled simultaneously with the force plate with a temporal resolution of 250 measurements/s. Five moments during the stance phase were selected on basis of the force plate recording for the analysis of the pressure distribution: heel strike, maximum braking, midstance, maximum propulsion, and push off. At the forelimbs, the vertical ground reaction force was equally distributed between medial and lateral claw. At the hind limbs at heel strike, the force was exerted almost completely to the lateral claw. During the rest of the stance phase the load shifted towards the medial claw, until, at push off, it was more or less equally divided between both claws. The average pressures determined were 50 to 80 N/cm2. Maximum pressures increased from 90 to 110 N/cm2 at heel strike to 180 to 200 N/cm2 at push off. It was concluded that at the hind limb these pressures constitute a major threat to overloading particularly for the softer parts of the lateral claw, e.g., the sole and bulb area.

Claw disorders and lameness in dairy cattle are an increasing problem of the modern dairy industry. To prevent claw disorders from evolving from the subclinical to the clinical stage, trimming is the management practice most routinely applied. The goal of preventive trimming (Toussaint-Raven method) is to promote natural loading by increasing the weight-bearing contact area of the claws and improving the balance between the medial and lateral claw. The biomechanical effect of preventive claw trimming was investigated with the aid of pressure distribution and ground reaction force recordings of the standing cow sampled simultaneously at 250 Hz. It appeared that preventive trimming of the hind limbs (n = 10) brought the claws slightly more in balance. Before trimming, 80% of the total force is taken up by the lateral claw and 20% by the medial claw. After trimming, this becomes 70 to 30%, respectively. Thereby, a significant increase in the weight-bearing contact area from 27.5 to 40.0 cm2 was achieved, resulting in a significant decrease in average pressure. However, the claws remained subjected to unaltered, high maximum pressures after trimming. The suggestion was made that the main focus of claw trimming should not be force balance; instead, a reduction of local maximum pressures at the contact area should be targeted in such a way that the strongest parts of the claw capsule (i.e., the wall) will be subjected to the highest pressures.

The distribution pattern of pressure over the bovine claw was investigated to test the hypothesis that the ground reaction force is unevenly distributed and makes some regions of the claw more prone to overloading and injury than others. In eight recently trimmed Holstein Friesian cows, the distribution of vertical pressure was measured during square standing with a spatial resolution of 2.6 sensors/cm2 and a temporal resolution of 313 measurements/s. In each animal, the localization of maximum pressure per foot and per claw was determined during five trials. In the front limb, maximum pressures were normally found on the medial claw; in the hindlimb they were located on the lateral claw. In both claws, the highest pressures were found on the sole of the foot and not on the wall. In the front limbs, maximum pressures were located in the posterior portion of the sole; in the hind limb in the anterior portion. There was no difference in the location of the maximum pressure between the medial and lateral claw in either limb. The regions in which these maximum pressures occur are known to be relatively susceptible to injuries. This could indicate a causal relation between the location of pressure concentrations and claw diseases found in clinical observations.

Most free-stall housing systems in the Netherlands are equipped with slatted or solid concrete floors with manure scrapers. A slipping incident occurs when the required coefficient of friction (RCOF) exceeds the coefficient of friction (COF) at the claw-floor interface. An experiment was conducted to measure ground reaction forces (GRF) of dairy cows (n = 9) performing various locomotory behaviors on a nonslippery rubber-covered concrete floor. The RCOF was determined as the ratio of the horizontal and vertical components of the GRF. It was shown that during straight walking and walking-a-curve, the RCOF reached values up to the COF, whereas for sudden stop-and-start responses, the RCOF reached values beyond the maximum COF that concrete floors can provide. Our results indicate that concrete floors do not provide enough friction to allow natural locomotory behavior and suggest that tractional properties of floors should be main design criteria in the development of better flooring surfaces for cattle.

International environmental agreements have led to the need to reduce methane emission by dairy cows. Reduction could be achieved through selective breeding. The aim of this study was to quantify the genetic variation of methane emission by Dutch Holstein Friesian cows measured using infrared sensors installed in automatic milking systems (AMS). Measurements of CH and CO on 1,508 Dutch Holstein Friesian cows located on 11 commercial dairy farms were available. Phenotypes per AMS visit were the mean of CH, mean of CO, mean of CH divided by mean of CO, and their log-transformations. The repeatabilities of the log-transformated methane phenotypes were 0.27 for CH, 0.31 for CO, and 0.14 for the ratio. The log-transformated heritabilities of these phenotypes were 0.11 for CH, 0.12 for CO, and 0.03 for the ratio. These results indicate that measurements taken using infrared sensors in AMS are repeatable and heritable and, thus, could be used for selection for lower CH emission. Furthermore, it is important to account for farm, AMS, day of measurement, time of day, and lactation stage when estimating genetic parameters for methane phenotypes. Selection based on log-transformated CH instead of the ratio would be expected to give a greater reduction of CH emission by dairy cows.

The aim was to investigate whether on-line somatic cell count (SCC) assessment, when combined with electrical conductivity (EC), should be implemented at the udder quarter or at the cow level. Data were collected from 3 farms with automatic milking systems, resulting in 3,191 quarter milkings used in the analyses. Visual observations of foremilk and quarter milk samples for laboratory SCC analysis were used to define 2 gold standards. One was based on visual observation only and the other was based on a combination of visual observation and SCC (using a reference value of 500,000 cells/mL), which means that a quarter milking must have visually abnormal milk as well as an increased SCC to be categorized positive. On-line SCC assessment took place at the quarter level during the first part of the milking. Composite cow level samples were used for laboratory SCC analysis and to compare the performance of SCC assessment at quarter and cow levels. The EC at the quarter level was measured by in-line sensors of the automatic milking system. Alerts for SCC indicators were calculated based on straightforward reference values. Alerts for EC were based on straightforward reference values, or on interquarter ratios. The latter was calculated by dividing the value of a given quarter by the average value of the 2 lowest quarters of that milking. The EC and SCC indicators were combined with either a Boolean "and" or "or" function. Receiver operating characteristic curves were used to visually present results using different threshold values. Sensitivity, specificity, and success rate at the quarter level and false alert rate per 1,000 cow milkings were used to compare indicators at given sensitivity or specificity levels. Quarter level SCC assessment was superior to cow level assessment (transformed partial area under the curve = 0.70 vs. 0.62) when combined with EC measurement at quarter level. When aiming for the same sensitivity level (e.g., 50%) with all visual abnormal milk as the gold standard, more false alerts were generated with cow level assessment (137 per 1,000 cow milkings) compared with quarter level SCC assessment (75 per 1,000 cow milkings). As a comparison, using EC alone resulted in 292 false alerts per 1,000 cow milkings in the same situation. Therefore, it is concluded that quarter level SCC assessment was superior to cow level assessment when combined with EC measurement at quarter level.

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure.

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