Body Condition Score Change throughout Lactation Utilizing an Automated BCS System: A Descriptive Study

Body condition scoring (BCS) is a traditional visual technique often using a five-point scale to non-invasively assess fat reserves in cattle. However, recent studies have highlighted the potential in automating body condition scoring using imaging technology. Therefore, the objective was to implement a commercially available automated body condition scoring (ABCS) camera system to collect data for developing a predictive equation of body condition dynamics throughout the lactation period. Holstein cows (n = 2343, parity = 2.1 ± 1.1, calving BCS = 3.42 ± 0.24), up to 300 days in milk (DIM), were scored daily using two ABCS cameras mounted on sort-gates at the milk parlor exits. Scores were reported on a 1 to 5 scale in 0.1 increments. Lactation number, DIM, disease status, and 305d-predicted-milk-yield (305PMY) were used to create a multivariate prediction model for body condition scores throughout lactation. The equation derived from the model was: ABCSijk = 1.4838 − 0.00452 × DIMi − 0.03851 × Lactation numberj + 0.5970 × Calving ABCSk + 0.02998 × Disease Status(neg)l − 1.52 × 10−6 × 305PMYm + eijklm. We identified factors which are significant for predicting the BCS curve during lactation. These could be used to monitor deviations or benchmark ABCS in lactating dairy cows. The advantage of BCS automation is that it may provide objective, frequent, and accurate BCS with a higher degree of sensitivity compared with more sporadic and subjective manual BCS. Applying ABCS technology in future studies on commercial dairies may assist in providing improved dairy management protocols based on more available BCS

Validation of a Commercial Automated Body Condition Scoring System on a Commercial Dairy Farm

Body condition scoring (BCS) is the management practice of assessing body reserves of individual animals by visual or tactile estimation of subcutaneous fat and muscle. Both high and low BCS can negatively impact milk production, disease, and reproduction. Visual or tactile estimation of subcutaneous fat reserves in dairy cattle relies on their body shape or thickness of fat layers and muscle on key areas of the body. Although manual BCS has proven beneficial, consistent qualitative scoring can be difficult to implement. The desirable BCS range for dairy cows varies within lactation and should be monitored at multiple time points throughout lactation for the most impact, a practice that can be hard to implement. However, a commercial automatic BCS camera is currently available for dairy cattle (DeLaval Body Condition Scoring, BCS DeLaval International AB, Tumba, Sweden). The objective of this study was to validate the implementation of an automated BCS system in a commercial setting and compare agreement of the automated body condition scores with conventional manual scoring. The study was conducted on a commercial farm in Indiana, USA, in April 2017. Three trained staff members scored 343 cows manually using a 1 to 5 BCS scale, with 0.25 increments. Pearson’s correlations (0.85, scorer 1 vs. 2; 0.87, scorer 2 vs. 3; and 0.86, scorer 1 vs. 3) and Cohen’s Kappa coefficients (0.62, scorer 1 vs. 2; 0.66, scorer 2 vs. 3; and 0.66, scorer 1 vs. 3) were calculated to assess interobserver reliability, with the correlations being 0.85, 0.87, and 0.86. The automated camera BCS scores were compared with the averaged manual scores. The mean BCS were 3.39 ± 0.32 and 3.27 ± 0.27 (mean ± SD) for manual and automatic camera scores, respectively. We found that the automated body condition scoring technology was strongly correlated with the manual scores, with a correlation of 0.78. The automated BCS camera system accuracy was equivalent to manual scoring, with a mean error of −0.1 BCS and within the acceptable manual error threshold of 0.25 BCS between BCS (3.00 to 3.75) but was less accurate for cows with high (\u3e 3.75) or low (\u3c 3.00) BCS scores compared to manual scorers. A Bland–Altman plot was constructed which demonstrated a bias in the high and low automated BCS scoring. The initial findings show that the BCS camera system provides accurate BCS between 3.00 to 3.75 but tends to be inaccurate at determining the magnitude of low and high BCS scores. However, the results are promising, as an automated system may encourage more producers to adopt BCS into their practices to detect early signs of BCS change for individual cattle. Future algorithm and software development is likely to increase the accuracy in automated BCS scoring

On-farm pig dispatch methods employed in Brazil and stockpeople attitudes on their use

This study surveyed the on-farm dispatching methods used at pig farms, the characteristics of stockpeople operating them, in terms of training and management, and their opinions and attitudes about the efficiency and safety of the applied procedures. Independently of the pig type, the most used dispatching methods at the surveyed Brazilian farms were concussion (90%) and electrocution (5%). Both methods were reported as being efficient and safe for on-farm pig dispatching by most stockpeople (83%). However, 33% of all stockpeople reported they would prefer to use alternative methods, i.e., anesthetics (23%) or electrocution (32%). Only 7% of the stockpeople received training resulting in a more efficient application of the method (P < 0.05). Most stockpeople (96%) declared to feel uncomfortable with the dispatching procedure they use. This discomfort lasted for half a day or longer in 22% of them. The results of this survey suggest that the application of dispatching methods at pig farms may result in animal welfare issues related to the effectiveness of the methods and the attitudes of stockpeople

No Evidence for Emotional Empathy in Chickens Observing Familiar Adult Conspecifics

The capacity of animals to empathise is of high potential relevance to the welfare of group-housed domestic animals. Emotional empathy is a multifaceted and multilayered phenomenon which ranges from relatively simple processes such as emotional matching behaviour to more complex processes involving interaction between emotional and cognitive perspective taking systems. Our previous research has demonstrated that hens show clear behavioural and physiological responses to the mild distress of their chicks. To investigate whether this capacity exists outside the mother/offspring bond, we conducted a similar experiment in which domestic hens were exposed to the mild distress of unrelated, but familiar adult conspecifics. Each observer hen was exposed to two replicates of four conditions, in counterbalanced order; control (C); control with noise of air puff (CN); air puff to conspecific hen (APC); air puff to observer hen (APH). During each test, the observer hens' behaviour and physiology were measured throughout a 10 min pre-treatment and a 10 min treatment period. Despite showing signs of distress in response to an aversive stimulus directed at themselves (APH), and using methodology sufficiently sensitive to detect empathy-like responses previously, observer hens showed no behavioural or physiological responses to the mild distress of a familiar adult conspecific. The lack of behavioural and physiological response indicates that hens show no basis for emotional empathy in this context

Body Condition Score Change throughout Lactation Utilizing an Automated BCS System: A Descriptive Study

Body condition scoring (BCS) is a traditional visual technique often using a five-point scale to non-invasively assess fat reserves in cattle. However, recent studies have highlighted the potential in automating body condition scoring using imaging technology. Therefore, the objective was to implement a commercially available automated body condition scoring (ABCS) camera system to collect data for developing a predictive equation of body condition dynamics throughout the lactation period. Holstein cows (n = 2343, parity = 2.1 &plusmn; 1.1, calving BCS = 3.42 &plusmn; 0.24), up to 300 days in milk (DIM), were scored daily using two ABCS cameras mounted on sort-gates at the milk parlor exits. Scores were reported on a 1 to 5 scale in 0.1 increments. Lactation number, DIM, disease status, and 305d-predicted-milk-yield (305PMY) were used to create a multivariate prediction model for body condition scores throughout lactation. The equation derived from the model was: ABCSijk = 1.4838 &minus; 0.00452 &times; DIMi &minus; 0.03851 &times; Lactation numberj + 0.5970 &times; Calving ABCSk + 0.02998 &times; Disease Status(neg)l &minus; 1.52 &times; 10&minus;6 &times; 305PMYm + eijklm. We identified factors which are significant for predicting the BCS curve during lactation. These could be used to monitor deviations or benchmark ABCS in lactating dairy cows. The advantage of BCS automation is that it may provide objective, frequent, and accurate BCS with a higher degree of sensitivity compared with more sporadic and subjective manual BCS. Applying ABCS technology in future studies on commercial dairies may assist in providing improved dairy management protocols based on more available BCS

Rubber mat placement in a farrowing and lactation facility: tips and techniques

Sow lameness may result in severe economic consequences to the producer, as lameness has been associated with increases in involuntary culling, poor reproductive performance, and suboptimal sow longevity. Lameness prevalence and severity are impacted by facility design, with a particular focus on hard concrete surfaces. Use of rubber mats has been previously investigated for its ability to increase sow comfort, prevent lameness development, and mitigate lameness severity. However, limited recommendations or guidelines are available to producers and veterinarians to successfully implement on-farm mat use. This production tool provides guidelines and techniques for selecting, installing, and maintaining rubber mats in farrowing stalls for multiparous sows

Rubber mat placement in a farrowing and lactation facility: tips and techniques

Sow lameness may result in severe economic consequences to the producer, as lameness has been associated with increases in involuntary culling, poor reproductive performance, and suboptimal sow longevity. Lameness prevalence and severity are impacted by facility design, with a particular focus on hard concrete surfaces. Use of rubber mats has been previously investigated for its ability to increase sow comfort, prevent lameness development, and mitigate lameness severity. However, limited recommendations or guidelines are available to producers and veterinarians to successfully implement on-farm mat use. This production tool provides guidelines and techniques for selecting, installing, and maintaining rubber mats in farrowing stalls for multiparous sows.This is an article from Campler, Magnus, Monique Pairis-Garcia, Kenneth J. Stalder, and Anna K. Johnson. "Rubber mat placement in a farrowing and lactation facility: tips and techniques." Journal of Swine Health and Production 24, no. 3 (2016): 142-146. Posted with permission.</p