Association between Prepartum Feeding Behavior and Periparturient Health Disorders in Dairy Cows

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

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.

Sensor based time budgets in commercial Dutch dairy herds vary over lactation cycles and within 24 hours

Cows from 8 commercial Dutch dairy farms were equipped with 2 sensors to study their complete time budgets of eating, rumination, lying, standing and walking times as derived from a neck and a leg sensor. Daily sensor data of 1074 cows with 3201 lactations was used from 1 month prepartum until 10 months postpartum. Farms provided data over a 5 year period. The final models (lactational time budget and 24h time budget) showed significant effects of parity, farm and calving season. When primiparous cows were introduced in the lactational herd, they showed a decrease in lying time of 215 min (95% CI: 187–242) and an increase in standing time of 159 min (95% CI: 138–179), walking time of 23 min (95% CI: 20–26) and rumination time of 69 min (95% CI: 57–82). Eating time in primiparous cows increased from 1 month prepartum until 9 months in lactation with 88 min (95% CI: 76–101) and then remained stable until the end of lactation. Parity 2 and parity 3+ cows decreased in eating time by 30 min (95% CI: 20–40) and 26 min (95% CI: 18–33), respectively, from 1 month before to 1 month after calving. Until month 6, eating time increased 11 min (95% CI: 1–22) for parity 2, and 24 min (95% CI: 16–32) for parity 3+. From 1 month before calving to 1 month after calving, they showed an increase in ruminating of 17 min (95% CI: 6–28) and 28 min (95% CI: 21–35), an increase in standing time of 117 min (95% CI: 100–135) and 133 min (95% CI: 121–146), while lying time decreased with 113 min (95% CI: 91–136) and 130 min (95% CI: 114–146), for parity 2 and 3+, respectively. After month 1 in milk to the end of lactation, lying time increased 67 min (95% CI: 49–85) for parity 2, and 77 min (95% CI: 53–100) for parity 3+. Lactational time budget patterns are comparable between all 8 farms, but cows on conventional milking system (CMS) farms with pasture access appear to show higher standing and walking time, and spent less time lying compared to cows on automatic milking system (AMS) farms without pasture access. Every behavioral parameter presented a 24h pattern. Cows eat, stand and walk during the day and lie down and ruminate during the night. Daily patterns in time budgets on all farms are comparable except for walking time. During the day, cows on CMS farms with pasture access spent more time walking than cows on AMS farms without pasture access. The average 24h pattern between parities is comparable, but primiparous cows spent more time walking during daytime compared to older cows. These results indicate a specific behavioral pattern per parameter from the last month prepartum until 10 months postpartum with different patterns between parities but comparable patterns across farms. Furthermore, cows appear to have a circadian rhythm with varying time budgets in the transition period and during lactation.

Prepartum behavior changes in dry Holstein cows at risk of postpartum diseases

The objective of this study was to identify changes in prepartum behavior associated with the incidence of postpartum diseases in dairy cows. Multiparous Holstein cows (n = 489) were monitored with accelerometers for 3 wk prepartum. Accelerometers measured steps, time at the feed bunk, frequency of meals, lying bouts, and lying time. Postpartum health was monitored from 0 to 30 d in milk and cases of metritis, mastitis, retained placenta, displaced abomasum (DA), ketosis, and hypocalcemia were recorded. A multivariate linear mixed model was used to assess differences in behavior between diseased and not diagnosed diseased cows. A multivariate logistic regression was used to predict the occurrence of diseases. Predictors were selected using a manual backward stepwise selection process of variables until all remaining predictors had a P < 0.10. Models were submitted to a leave-one-out cross-validation process, and sensitivity, specificity, false discovery rate, and false omission rate were calculated. On average, over the 3-wk prepartum period, cows not diagnosed diseased (n = 345) took 1,613 ± 38 steps, spent 181 ± 7.1 min at the feed bunk, had 8.3 ± 0.17 meals, had 9.8 ± 0.32 lying bouts, and spent 742 ± 11.3 min lying per day. Behavior of diseased cows (n = 144) did not differ from those not diagnosed diseased. However, differences for specific diseases were observed, being significant in the week prepartum. When considering changes in behavior for only the week before calving, cows with metritis had more lying bouts (+21%), cows with DA had fewer meals (-24%) and tended to take fewer steps (-18%), and cows with ketosis had fewer meals (-22%) and spent less time at the feed bunk (-40%). Prediction models with the best outcomes were found for DA and ketosis using data of the prepartum week only. The model for DA included time at the feed bunk. Cross-validation resulted in a 80% sensitivity, 58.1% specificity, 59.2% accuracy, 91.2% false discovery rate, and 1.7% false omission rate. The model for ketosis included time at the feed bunk and number of meals. Cross-validation resulted in 64.3% sensitivity, 59.3% specificity, 59.5% accuracy, 93.0% false discovery rate, and 2.8% false omission rate. Prepartum behavior of cows affected with metritis, DA, and ketosis was different from that of cows not diagnosed with diseases. Prediction equations were able to classify cows at high or low risk of ketosis and DA and can be used in taking management decisions, but the high false discovery rates requires further refinement.

Predicting Disease in Transition Dairy Cattle Based on Behaviors Measured Before Calving

Simple Summary

Dairy cattle often become ill after calving. We developed models designed to predict which cows are likely to become ill based upon measures of the cows’ feeding and competitive behaviors before calving. Our models had high sensitivity (73–71%), specificity (80–84%), positive predictive values (73–77%), and negative predictive values (80–80%) for both cows that had previously calved and for those calving for the first time. We conclude that behaviors at the feed bunk before calving can predict cows at risk of becoming sick in the weeks after calving.

Abstract

Dairy cattle are particularly susceptible to metritis, hyperketonemia (HYK), and mastitis in the weeks after calving. These high-prevalence transition diseases adversely affect animal welfare, milk production, and profitability. Our aim was to use prepartum behavior to predict which cows have an increased risk of developing these conditions after calving. The behavior of 213 multiparous and 105 primiparous Holsteins was recorded for approximately three weeks before calving by an electronic feeding system. Cows were also monitored for signs of metritis, HYK, and mastitis in the weeks after calving. The data were split using a stratified random method: we used 70% of our data (hereafter referred to as the “training” dataset) to develop the model and the remaining 30% of data (i.e., the “test” dataset) to assess the model’s predictive ability. Separate models were developed for primiparous and multiparous animals. The area under the receiver operating characteristic (ROC) curve using the test dataset for multiparous cows was 0.83, sensitivity and specificity were 73% and 80%, positive predictive value (PPV) was 73%, and negative predictive value (NPV) was 80%. The area under the ROC curve using the test dataset for primiparous cows was 0.86, sensitivity and specificity were 71% and 84%, PPV was 77%, and NPV was 80%. We conclude that prepartum behavior can be used to predict cows at risk of metritis, HYK, and mastitis after calving.

Chicken or the Egg: The Reciprocal Association Between Feeding Behavior and Animal Welfare and Their Impact on Productivity in Dairy Cows

Feeding behavior in dairy cattle has a significant impact on feed efficiency, which is important for increasing the profitability of livestock and, at the same time, reducing the environmental impact. Feeding behavior can be measured by feeding time, meal duration, meal frequency, feeding rate, and rumination time. Higher feed intake is related to lower feed efficiency; whereas, an increase in feeding time facilitates chewing, reduces feed particle size and increases its digestibility. More frequent and shorter meals are usually associated with a more efficient use of feed due to improvement of feed digestibility. Rumination time is positively associated with milk production. Impaired health is associated with variations in feeding behavior, which can be used to identify and predict some diseases such as ketosis, mastitis, or lameness. Changes in rumination time are also a reliable indicator of mastitis, lameness, ketosis, abomasal displacement, and the onset of calving. In addition to the cause-effect relationship between disease and changes in feeding behavior, there are also some cases in which changes in feeding behavior may lead to an increased risk of disease, as exemplified by the relationship of feeding rate with sub-acute ruminal acidosis. Feeding behavior is regulated by internal and external factors and some of them are relevant for animal welfare. The main welfare-associated factors influencing feeding behavior are social behavior and temperament, and environmental effects. Cattle are social animals and hierarchy has a notable impact on feeding behavior, especially when access to feed is limited. Competition for feed causes a reduction in the average feeding time but increases feeding rate. Excitable animals visit the feeder more often and spend less time per meal. High environmental temperature affects feeding behavior, as heat-stressed cattle change their feeding pattern by concentrating the feeding events in crepuscular hours, leading to an increased risk of sub-acute ruminal acidosis. In conclusion, feeding behavior is a determinant feature for improving efficiency, productivity and welfare of dairy cattle. Routine assessment of feeding behavior allows monitoring of health and production status of dairy cattle at the individual and farm level, which is a useful tool to optimize the management of livestock.

Study of the effects of nesfatin-1 on gastric function in obese rats

AIM

To investigate the effects of nesfatin-1 on gastric function in obese rats.

METHODS

The obese rat model was induced by a high-fat diet. The gastric emptying rate and gastric acid secretory capacity of the rats were determined after treatment with different drug concentrations of nesfatin-1 and administration routes. Based on this, the expression of H+/K+-ATPase was measured using RT-PCR and western blot to preliminarily explore the mechanism of gastric acid secretion changes.

RESULTS

Body weight, body length, and Lee’s index of the rats significantly increased in the high-fat diet-induced obese rat model. Two hours after lateral intracerebroventricular injection of nesfatin-1, the gastric emptying rate and gastric acid secretory capacity of rats decreased. Four hours after injection, both were restored to normal levels. In addition, the expression of H+/K+-ATPase decreased and moved in line with changes in gastric acid secretory capacity. This in vivo experiment revealed that intracerebroventricular injection of nesfatin-1, rather than intravenous injection, could suppress gastric function in obese rats. Moreover, its effect on the gastric emptying and gastric acid secretory capacity of rats is dose-dependent within a certain period of time.

CONCLUSION

Through this research, we provide a theoretical basis for further studies on nesfatin-1, a potential anti-obesity drug.