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While studies have been conducted examining the stress response of dairy cattle to individual acute and chronic stressors, the results are difficult to compare due to differences in study design and analysis methods. The aim of the present study was to conduct a comparative assessment of the impact of eight common stimuli: artificial insemination (AI), embryo transfer (ET), morning milking (MM), evening milking (EM), veterinary examination (VE), ultrasound examination (US), hoof trimming (HT), and natural breeding (NB) on the hypothalamic-pituitary-adrenal axis and milk production of 24 Holstein-Friesian cattle. After random allocation into control and treatment groups, a total of five blood samples were collected 40 min (Ba1) and 20 min (Ba2) prior to stimulus application, immediately following the stimulus (St), as well as 20 min (Re1) and 40 min (Re2) post-stimulus. A comparison between the overall serum cortisol concentrations in the treatment groups showed a significant difference between HT to AI (p = 0.006), ET (p = 0.010), MM (p = 0.021), VE (p = 0.009), EM (p = 0.007), and US (p = 0.010), except for NB (p = 0.542). There is no significant difference between the control groups (p > 0.05). The stimuli HT (p < 0.001) and NB (p < 0.001) showed significant increases in cortisol following stimulus application, and the levels failed to decrease significantly by sample Re2. No significant differences in daily milk yield (kg) were measured amongst the tested stimuli (p = 0.472) nor amongst the groups ‘Control’, ‘Treatment’ and ‘no stimulus’ (p = 0.350). In conclusion, when factors such as increased physical activity, novel social interaction, sexual arousal, and a more intense restriction of movement are present, the animal’s perceived controllability and predictability might decrease, affecting the animal’s response to stress. Treatments carried out while animals are restrained in a headlock while remaining within their regular group likely result in a less intense activation of the HPA axis.

Dairy production is an important source of nutrients in the global food supply, but environmental impacts are increasingly a concern of consumers, scientists, and policy-makers. Many decisions must be integrated to support sustainable production—which can be achieved using a simulation model. We provide an example of the Ruminant Farm Systems (RuFaS) model to assess changes in the dairy system related to altered animal feed efficiency. RuFaS is a whole-system farm simulation model that simulates the individual animal life cycle, production, and environmental impacts. We added a stochastic animal-level parameter to represent individual animal feed efficiency as a result of reduced residual feed intake and compared High (intake = 94% of expected) and Very High (intake = 88% of expected) efficiency levels with a Baseline scenario (intake = 100% of expected). As expected, the simulated total feed intake was reduced by 6 and 12% for the High and Very High efficiency scenarios, and the expected impact of these improved efficiencies on the greenhouse gas emissions from enteric methane and manure storage was a decrease of 4.6 and 9.3%, respectively.

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 (>3.75) or low (