Effect of light intensity on behaviour, health and growth of growing-finishing pigs.

The effect of light intensity has been explored in relation to endocrine functions and reproduction in pigs, but effects on health and behaviour are scarcely documented. The objective of this study was to evaluate the effects of different light intensities on behaviour, health and growth of growing-finishing pigs. An experiment was conducted on a commercial farm equipped with light-emitting diode-based luminaires creating four light intensity treatments: low (45 lux), medium (198 lux), high (968 lux) and spatial gradient of intensity (from 71 lux to 330 lux). Per treatment, 112 pigs were studied in two batches of eight pens. Once every two weeks behaviours such as exploration, positive and negative social interactions, play and abnormal behaviours were observed. Health issues were assessed weekly and included biting lesions, skin lesions, leg and respiratory disorders. The average daily gain over the experiment was calculated and after slaughter carcasses were inspected. Generalised linear mixed models were used for the analysis of behaviours, binary health scores, carcass abnormalities, ordinal logistic regression for multilevel health scores, and linear mixed models for average daily gain. Interactions between intensity and week were found for some behaviours (i.e., exploration, negative social interactions and abnormal behaviour) and health issues (i.e., tear stains, conjunctivitis, body lesions, bursitis and tail lesions). However, none of the treatments consistently outperformed another one. Light treatments did not affect pig growth and carcass abnormalities. These variable results support studies suggesting that pigs are adaptable to light intensities, and inconsistencies over weeks might have been caused by environmental factors that could not be controlled in a commercial farm setting. To conclude, tested light intensities had no clear effects on pig behaviour, health and growth.

Erratum to "Automatic assessment of dairy cows' rumen function over time and links to feed changes and milk production" (JDS Commun. 3:126-131).

[This corrects the article DOI: 10.3168/jdsc.2021-0165.].

Automatic assessment of dairy cows' rumen function over time and links to feed changes and milk production.

A 3-dimensional (3D) vision-based system was previously designed to automatically estimate the rumen motility of individual cows. This longitudinal study aimed to explore the associations between 3D vision-based rumen function assessment and dairy cow feed changes and milk production on a commercial farm. The 3D vision system was attached to an automatic milking robot to estimate the ruminal contraction frequency and rumen fill in 42 lactating cows during each milking event for 66 d. Additionally, we collected data on milk production, milk composition, general health, and changes in feeding practices. The 3D vision system showed that half the cows displayed a drastic decrease in the estimated rumen fill when all cows began grazing. The grazing and decreased rumen fill were also associated with herd-level milk fat depression. Over the 66 d, one cow was detected with reduced milk production and suspected rumen dysfunction by the farmer. The 3D vision system, however, identified this cow as having sudden decreases in estimated ruminal contraction frequency and rumen fill 4 d before detection by the farmer. In this longitudinal study, the 3D vision-based rumen function assessment system showed potential as a useful management-supporting tool for dairy farmers. The system, however, requires further validation with more cows of various breeds and ages. We suggest validating the 3D vision system with rumen boluses, quantified adjustments in feeding practices, more cases with ruminal dysfunction, and systematic health assessments for future studies.

A Systematic Review of Automatic Health Monitoring in Calves: Glimpsing the Future From Current Practice.

Infectious diseases, particularly bovine respiratory disease (BRD) and neonatal calf diarrhea (NCD), are prevalent in calves. Efficient health-monitoring tools to identify such diseases on time are lacking. Common practice (i.e., health checks) often identifies sick calves at a late stage of disease or not at all. Sensor technology enables the automatic and continuous monitoring of calf physiology or behavior, potentially offering timely and precise detection of sick calves. A systematic overview of automated disease detection in calves is still lacking. The objectives of this literature review were hence: to investigate previously applied sensor validation methods used in the context of calf health, to identify sensors used on calves, the parameters these sensors monitor, and the statistical tools applied to identify diseases, to explore potential research gaps and to point to future research opportunities. To achieve these objectives, systematic literature searches were conducted. We defined four stages in the development of health-monitoring systems: (1) sensor technique, (2) data interpretation, (3) information integration, and (4) decision support. Fifty-four articles were included (stage one: 26; stage two: 19; stage three: 9; and stage four: 0). Common parameters that assess the performance of these systems are sensitivity, specificity, accuracy, precision, and negative predictive value. Gold standards that typically assess these parameters include manual measurement and manual health-assessment protocols. At stage one, automatic feeding stations, accelerometers, infrared thermography cameras, microphones, and 3-D cameras are accurate in screening behavior and physiology in calves. At stage two, changes in feeding behaviors, lying, activity, or body temperature corresponded to changes in health status, and point to health issues earlier than manual health checks. At stage three, accelerometers, thermometers, and automatic feeding stations have been integrated into one system that was shown to be able to successfully detect diseases in calves, including BRD and NCD. We discuss these findings, look into potentials at stage four, and touch upon the topic of resilience, whereby health-monitoring system might be used to detect low resilience (i.e., prone to disease but clinically healthy calves), promoting further improvements in calf health and welfare.

Hot topic: Automated assessment of reticulo-ruminal motility in dairy cows using 3-dimensional vision.

Reticulo-ruminal motility is a well-established indicator of gastrointestinal health in dairy cows. The currently available methods for assessing motility are labor-intensive, costly, and impractical to use regularly for all cows on a farm. We hypothesized that the reticulo-ruminal motility of dairy cows could be assessed automatically and remotely using a low-cost 3-dimensional (3D) camera. In this study, a 3D vision system was constructed and mounted on the frame of an automatic milking robot to capture the left paralumbar fossa of 20 primiparous cows. For each cow, the system recorded 3D images at 30 frames per second during milking. Each image was automatically processed to locate the left paralumbar fossa region and quantify its average concavity. Then, the average concavity values from all images of 1 cow during 1 milking process were chronologically assembled to form an undulation signal. By applying fast Fourier transformation to the signal, we identified cyclic oscillations that occurred in the same frequency range as reticulo-ruminal contractions. To validate the oscillation identification, 2 trained assessors visually identified reticulo-ruminal contractions from the same 3D image recordings on screen. The matching sensitivity between the automatically identified oscillations and the manually identified reticulo-ruminal contractions was 0.97. This 3D vision system can automate the assessment of reticulo-ruminal motility in dairy cows. It is noninvasive and can be implemented on farms without distressing the cows. It is a promising tool for farmers, giving them regular information about the gastrointestinal health of individual cows and helping them in daily farm management.

Automated body condition scoring of dairy cows using 3-dimensional feature extraction from multiple body regions.

Machine vision technology has been used in automated body condition score (BCS) classification of dairy cows. The current vision-based classifications use information acquired from a limited number of body regions of the cow. Our study aimed to improve automated BCS classification by including multiple body condition-related features extracted from 3 viewpoints in 8 body regions. The data set of this study included 44 lactating cows with their BCS evenly distributed over the scale of BCS from 1.5 to 4.5 units. The body images of these cows were recorded over 2 consecutive days using 3-dimensional cameras positioned to view the cow from the top, right side, and rear. Each image was automatically processed to identify anatomical landmarks on the body surface. Around these anatomical landmarks, the bony prominences and body surface depressions were quantified to describe 8 body condition-related features. A manual BCS of each cow was independently assigned by 2 trained assessors using the same predefined protocol. With the extracted features as inputs and manual BCS as the reference, we built a nearest-neighbor classification model to classify BCS and obtained an overall classification sensitivity of 0.72 using a 10-fold cross-validation. We conclude that the sensitivity of automated BCS classification has been improved by expanding the selection of body condition-related features extracted from multiple body regions.

Automated body weight prediction of dairy cows using 3-dimensional vision.

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.

Genetic background of methane emission by Dutch Holstein Friesian cows measured with infrared sensors in automatic milking systems.

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 CH4 and CO2 on 1,508 Dutch Holstein Friesian cows located on 11 commercial dairy farms were available. Phenotypes per AMS visit were the mean of CH4, mean of CO2, mean of CH4 divided by mean of CO2, and their log10-transformations. The repeatabilities of the log10-transformated methane phenotypes were 0.27 for CH4, 0.31 for CO2, and 0.14 for the ratio. The log10-transformated heritabilities of these phenotypes were 0.11 for CH4, 0.12 for CO2, 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 CH4 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 log10-transformated CH4 instead of the ratio would be expected to give a greater reduction of CH4 emission by dairy cows.

Somatic cell count assessment at the quarter or cow milking level.

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.

Pressure distribution at the teat-liner and teat-calf interfaces.

During milking, the teat is loaded because of a combination of vacuum and pressure of the collapsing liner. It is assumed that pressure concentrations tend to cause teat-end injuries and hyperkeratosis. The pressure distribution on the bovine teat was measured to test the hypothesis that the pressures of the collapsed liner are unevenly distributed over the teat. With the aid of a pressure-sensitive sensor (approximately 2 gauge points/cm(2)), the pressures at the teat-liner and the teat-calf interfaces were measured at 100 Hz. Pressure distribution over the surface of an artificial teat was measured with 7 different liners, 1 liner at 3 different vacuum levels, and a suckling calf. One cow was equipped with a sensor at a teat during a milking with one of the liners. Conventional round liners concentrated the load over 2 sites at the teat end. Some liners (softer material, reduced tension, smaller barrel, reduced mouthpiece depth) distributed the compressive load over a larger area of the teat. Although all liners distributed the highest pressures at the teat end, some liner designs showed a 25% reduction at the site of interest at vacuum of 44 kPa. The calf forced milk flow by a combination of suckling and overpressure in the teat cistern caused by the tongue. While the calf was swallowing, teat pressure was reduced because of a decrease in vacuum. Moreover, the calf did not load the teat end, probably because the teat canal would be closed and the milk would not flow. The method of using a pressure sensor to analyze teat loading at the teat-liner and the teat-calf interfaces showed potential and is a first step toward developing a natural milking technique.

Effects of two trimming methods of dairy cattle on concrete or rubber-covered slatted floors.

This study monitored claw health, claw conformation, locomotion, activity, and step traits of cows from a single dairy herd that were trimmed according to the standard Dutch method or with an alternative "concave" trimming method. Half of the cows were kept in a stall section with concrete slatted floors in the alleys. The other cows were kept in a pen within the same housing with an identical concrete slatted floor in the alleys, but with a rubber top layer. All experimental cows were kept in the same environment for at least 3 mo before and after trimming. It was hypothesized that trimming for more-concave soles (i.e., with 3 to 5 mm of sole dug out under the claw bone) was preferred to the standard Dutch trimming with flat sole surfaces for cows kept in stalls with soft alley floors. None of the claw health or locomotion traits differed for the trimming methods. No interactions were found between flooring and trimming method. Floor effects were significant for several traits. Cows on the rubber-topped floors had significantly fewer sole hemorrhages (prevalence of 22 vs. 48% in mo 3) and larger claws (claw length 76.1 +/- 5.0 vs. 72.5 +/- 4.9 mm; heel height 49.3 +/- 6.3 vs. 46.0 +/- 6.4 mm; claw diagonal 129 +/- 6.4 vs. 125 +/- 6.9 mm), spent more time standing in the alleys (55.4 +/- 2.8 vs. 49.6 +/- 2.8%), and had higher activity (61.0 +/- 3.7 vs. 53.0 +/- 3.7 steps/h). This suggests greater claw comfort on rubber flooring compared with concrete flooring. Kinetic patterns during claw-floor contact while walking were similar for all treatments. During the double-support (stance) phase, claw-floor contact area increased to a maximum in the first 30% of double-support phase time, remained more or less stable until 80% of double-support phase time, and sharply decreased as the animal pushed off as shown by the change in center of pressure. A gradual change of center of pressure in the medial direction during double-support phase time was shown. The research hypothesis was rejected, but soft alley floors had subtle beneficial effects.

Frictional forces required for unrestrained locomotion in dairy cattle.

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.

The effect of preventive trimming on weight bearing and force balance on the claws of dairy cattle.

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.

[Biomechanical aspects of the claw-floor interaction in dairy cattle: implications for locomotion and claw disorders]. / Biomechanische aspecten van de klauw-vloerinteractie bij melkkoeien: implicaties voor bewegen en klauwaandoeningen.

The prevalence of claw disorders is still high among cows housed on concrete floors. Concrete floors affect the locomotion of cattle, their natural behavior. Although many factors affect the development of claw disorders and locomotor problems, biomechanical aspects have hardly been analysed. In this thesis, mechanical (over)loading of the claw and its significance for claw disorders and lameness are discussed. The mechanical characteristics a floor needs to provide in order to enable unrestrained locomotory behavior. This biomechanical approach, which is a relatively new approach in cattle locomotion, has provided new insights. Despite preventive trimming, the weakest parts of the claw capsule are loaded relatively the most. Concrete floors provide too little friction to enable unrestricted cattle locomotion.

The vertical ground reaction force and the pressure distribution on the claws of dairy cows while walking on a flat substrate.

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.

The pressure distribution under the bovine claw during square standing on a flat substrate.

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.