Assessment of feeding, ruminating and locomotion behaviors in dairy cows around calving – a retrospective clinical study to early detect spontaneous disease appearance

Abstract

The study aims to verify the usefulness of new intervals-based algorithms for clinical interpretation of animal behavior in dairy cows around calving period. Thirteen activities associated with feeding-ruminating-locomotion-behaviors of 42 adult Holstein-Friesian cows were continuously monitored for the week (wk) -2, wk -1 and wk +1 relative to calving (overall 30’340 min/animal). Soon after, animals were retrospectively assigned to group-S (at least one spontaneous diseases; n = 24) and group-H (healthy; n = 18). The average activities performed by the groups, recorded by RumiWatch® halter and pedometer, were compared at the different weekly intervals. The average activities on the day of clinical diagnosis (dd0), as well as one (dd-1) and two days before (dd-2) were also assessed. Differences of dd0 vs. dd-1 (ΔD1), dd0 vs. wk -1 (ΔD2), and wk +1 vs. wk -1 (Δweeks) were calculated. Variables showing significant differences between the groups were used for a univariate logistic regression, a receiver operating characteristic analysis, and a multivariate logistic regression model. At wk +1 and dd0, eating- and ruminating-time, eating- and ruminate-chews and ruminating boluses were significantly lower in group-S as compared to group-H, while other activity time was higher. For ΔD2 and Δweeks, the differences of eating- and ruminating-time, as well as of eating-and ruminate-chews were significantly lower in group-S as compared to group-H. Concerning the locomotion behaviors, the lying time was significantly higher in group-S vs. group-H at wk +1 and dd-2. The number of strides was significantly lower in group-S compared to group-H at wk +1. The model including eating-chews, ruminate-chews and other activity time reached the highest accuracy in detecting sick cows in wk +1 (area under the curve: 81%; sensitivity: 73.7%; specificity: 82.4%). Some of the new algorithms for the clinical interpretation of cow behaviour as described in this study may contribute to monitoring animals’ health around calving.

Cardiovascular changes, laboratory findings and pain scores in calves undergoing ultrasonography-guided bilateral rectus sheath block before herniorrhaphy: a prospective randomized clinical trial

“…As suggested by previous studies [ 7 ], the use of a digital Holter for scientific purposes has several advantages in this regard: (i) it provides continuous monitoring of HR and cardiac rhythm, leaving the patient in its environment; (ii) it allows the animal to behave spontaneously; (iii) it rules out the possible effects due to investigators presence during the recording. As widely known, pain stimulus is often associated with physiological, behavioral, and neuroendocrine changes [ 12 , 14 , 20 ]. Indeed, after the release of pro-inflammatory cytokines and the consequent activation of the hypothalamus-pituitary-adrenal axis, the sympathetic nervous system causes the release of ACTH and catecholamines [ 12 ].…”

“…Finally, the UNESP-Botucatu pain scale can be used to evaluate acute postoperative pain and to define the degree of analgesia in livestock, with demonstrated reliability and excellent internal consistency [ 11 – 13 ]. This is especially important in cattle field medicine, where other diagnostic methods may be impractical due to long processing time, specific skills, and high economic costs (e.g., precision farming devices) [ 14 , 15 ]. The diagnostic merits of each system are well documented; therefore, a simultaneous multiparametric-based approach should represent a superior strategy to quantify discomfort and pain in ruminants [ 16 ].…”

Metabolic Changes Associated with Different Levels of Energy Deficits in Mediterranean Buffaloes during the Early Lactation Stage: Type and Role of the Main Lipid Fractions Involved

“…The MBs selected were individually confined to a trimming chute and submitted to a complete clinical examination to exclude coexisting diseases (e.g., metritis, gastrointestinal disease, foot disorders, etc. ), as performed in a previous study [13]. The four areas, including ribs, spine, hips, and tail base, where animals usually store adipose tissue were used to estimate the body condition score using a 9-point scoring system [14].…”

Self-Powered Cattle Behavior Monitoring System Using 915 MHz Radio Frequency Energy Harvesting

“…The physical behavior of dairy cattle indicates their well-being, health status, and productivity [3]. Abnormal behaviors, such as reduced feed intake, prolonged lying time, and decreased locomotion, can be early signs of diseases, discomfort, or environmental stress [4]. Timely detection and intervention can lead to improved cow welfare, increased milk production, and reduced veterinary costs [5].…”