Changes of ruminal pH, rumination activity and feeding behaviour during early lactation as affected by different energy and fibre concentrations of roughage in pluriparous dairy cows

Validation of a methodology for characterization of rumination, lying, standing, and performing non-nutritive oral behaviors and behavioral patterns in Holstein dairy calves

Calf behavior is closely related to its early growth, production performance, and health performance. Continuous behavior recording is the most accurate but also time-consuming method used for monitoring animal behaviors, so the instantaneous sampling method is often adopted to minimize the time required to quantify behavioral observations in animal studies. Moreover, the optimal sampling intervals required to yield accurate information for estimating Holstein dairy calves' behaviors are still unknown. Our primary objective was to determine the most optimal sampling intervals for monitoring behaviors of Holstein dairy calves during preweaning and weaning periods to improve efficiency while maintaining reliability. The secondary objective was to describe their behavioral patterns. Rumination, lying, standing, and non-nutritive oral behavior (NNOB) data of 18 calves (observation time: 360 h/calf, 6,480 h in total) were continuously recorded for 15 d (3 d at 1, 3, 6, 9, and 12 wk of age). The continuous behavioral data were compared with instantaneous sampling at 5 s, 10 s, 15 s, 30 s,1 min, 3 min, 5 min, 10 min, 15 min, 30 min, and 60 min intervals. Sampling intervals were considered accurate if they met 4 criteria: coefficient of determination ≥0.90 (i.e., strongly related to true values), slope = 1, intercept = 0 (i.e., they did not over- or underestimate true values), and relative error <10%. The most optimal sampling interval was considered the highest sampling interval among the 11 sampling intervals that meet the criteria for accurate monitoring. As expected, the strength of the linear relationship between the continuous recording and instantaneous sampling decreased as the sampling intervals increased. The results varied across the different behaviors, with rumination, lying, standing, and NNOB being reliable at instantaneous recordings of 3 min, 10 min, 10 min, and 1 min for the preweaning period (1, 3, and 6 wk of age) and 10 min, 10 min, 15 min, and 3 min for the postweaning period (9 and 12 wk of age). In terms of behavioral patterns, lying time decreased, whereas rumination, standing, and NNOB time increased with age. After weaning, no significant changes in time spent performing these behaviors. Additionally, the rumination behavioral pattern becomes stable after wk 6 with decreasing after the morning feeding and occurring mainly in the morning. In conclusion, instantaneous sampling is a reliable method for monitoring the behaviors of dairy calves, but the optimal sampling intervals should be selected based on different ages and management conditions.

The Relationship between Reticuloruminal Temperature, Reticuloruminal pH, Cow Activity, and Clinical Mastitis in Dairy Cows

We hypothesized that reticuloruminal temperature, pH as well as cow activity can be used as parameters for the early diagnosis of clinical mastitis in dairy cows. Therefore, we aimed to detect the relationship between these factors and the disease. We randomly selected cows with clinical mastitis and clinically healthy cows (HG) out of 600 milking cows. We recorded the following parameters during the experiment: reticulorumen temperature (RR temp.), reticulorumen pH (RR pH), and cow activity. We used smaXtec boluses (smaXtec animal care technology^®, Graz, Austria). In this investigation, reticulorumen data obtained seven days before diagnosis were compared to HG data from the same time period. CM cows were observed on the same days as the healthy cows. The healthy group's RR pH was 7.32% higher than that of cows with CM. Reticulorumen temperature was also 1.25% higher in the CM group than in the control group. The healthy group had a higher average value for walking activity, which was 17.37% higher than the CM group. The data of reticulorumen pH changes during 24 h showed that during the day, the pH changed from 5.53 to 5.83 in the CM group. By contrast, pH changed from 6.05 to 6.31 in the control group. The lowest reticulorumen pH in the CM group was detected on the third day before diagnosis, which was 15.76% lower than the highest reticulorumen pH detected on the sixth day before diagnosis. The lowest reticulorumen pH in CM cows was detected at 0 and 1 days before diagnosis and it was 1.45% lower than the highest reticulorumen pH detected on the second day before diagnosis. The lowest walking activity in the CM group was detected 0 days before diagnosis, which was 50.60% lower than on the fifth day before diagnosis. Overall, the results confirmed our hypothesis that reticuloruminal temperature, reticuloruminal pH, and cow activity could be used as parameters for the early diagnosis of clinical mastitis in dairy cows.

Using rumination time to manage health and reproduction in dairy cattle: a review

Early detection of disease is the key to successful management of the dairy cattle which leads to timely treatment and prevention of costs associated with prolonged treatment and reduced milk yield. Electronic systems that allow for monitoring of physiological parameters like rumination, are now commercially available. This review paper discusses different aspects of rumination time that could be used to monitor the health and reproduction of dairy cattle. This review paper explored different areas where rumination time could be utilized in monitoring dairy cattle at calving, during the estrus period, during heat stressed conditions, and to detect diseases and transition cow disorders. In conclusion, rumination time could be used as an indicator of the health status in dairy cattle.

Relationship between milk constituents from milk testing and health, feeding, and metabolic data of dairy cows

A new evaluation scheme to assess the nutritional status of dairy cows on the basis of milk constituents was derived from 7.37 million German records of milk testing. The aim of this work was to validate this new scheme. Two data sets with fertility and health information (data set A) and with measured energy and nutrient intake and metabolic characteristics (data set B) were analyzed. Data set A included 32 commercial dairy farms in northeast Germany, with 72,982 records of 43,863 German Holstein cows; data set B included 12 German experimental farms, with 49,275 records of 1,650 German Holstein, Simmental, and Brown Swiss cows. Milk traits were linked to health disorders and metabolic and feeding characteristics. Frequently used limits of milk constituents were compared with ranges of the new "Dummerstorf feeding evaluation." To distinguish an optimal from a deficient energy supply, a milk protein content ≥3.20% (previously used) and a milk fat:protein ratio (FPR) ≤1.4 (new scheme) were chosen and compared with feed energy intake in relation to demand. Energy status was more often correctly assigned by FPR than by milk protein content (80.7 and 68.7%, respectively). Over all data, the new optimum range of milk urea between 150 and 250 mg/L was better suited to dietary crude protein intake in relation to demand than the previously used range of 150 to 300 mg/L (42.4 and 38.0%, respectively). Ketosis or blood values associated with ketosis such as β-hydroxybutyrate >1.2 mmol/L or nonesterified fatty acids >1,000 µmol/L, as well as strong mobilization of body weight ≥1.5 kg/d, loss of back fat thickness ≥10 mm, and loss of body condition score ≥1 unit in first 60 days in milk were compared with different milk trait thresholds. For the updated scheme FPR >1.4 was used in combination with either milk protein content below the individual statistical lower limit of milk protein content, or milk fat content greater than the individual statistical upper limit of milk fat content; FPR >1.5 was taken as a frequently used threshold. For these ketosis indicators, the new scheme had higher sensitivities. Energy oversupply or the risk of overconditioning could not be identified by milk constituents alone. Urinary acid-base content was not related to milk content. Similarly, milk testing data did not allow a clear distinction to be made between the diagnoses of acidosis and, for example, ketosis. Essential requirements for good herd management are the continuous observation of milk testing data in combination with other established instruments of feeding and animal monitoring.

Review: Rumen sensors: data and interpretation for key rumen metabolic processes

Rumen sensors provide specific information to help understand rumen functioning in relation to health disorders and to assist in decision-making for farm management. This review focuses on the use of rumen sensors to measure ruminal pH and discusses variation in pH in both time and location, pH-associated disorders and data analysis methods to summarize and interpret rumen pH data. Discussion on the use of rumen sensors to measure redox potential as an indication of the fermentation processes is also included. Acids may accumulate and reduce ruminal pH if acid removal from the rumen and rumen buffering cannot keep pace with their production. The complexity of the factors involved, combined with the interactions between the rumen and the host that ultimately determine ruminal pH, results in large variation among animals in their pH response to dietary or other changes. Although ruminal pH and pH dynamics only partially explain the typical symptoms of acidosis, it remains a main indicator and may assist to optimize rumen function. Rumen pH sensors allow continuous monitoring of pH and of diurnal variation in pH in individual animals. Substantial drift of non-retrievable rumen pH sensors, and the difficulty to calibrate these sensors, limits their application. Significant within-day variation in ruminal pH is frequently observed, and large distinct differences in pH between locations in the rumen occur. The magnitude of pH differences between locations appears to be diet dependent. Universal application of fixed conversion factors to correct for absolute pH differences between locations should be avoided. Rumen sensors provide high-resolution kinetics of pH and a vast amount of data. Commonly reported pH characteristics include mean and minimum pH, but these do not properly reflect severity of pH depression. The area under the pH × time curve integrates both duration and extent of pH depression. The use of this characteristic, as well as summarizing parameters obtained from fitting equations to cumulative pH data, is recommended to identify pH variation in relation to acidosis. Some rumen sensors can also measure the redox potential. This measurement helps to understand rumen functioning, as the redox potential of rumen fluid directly reflects the microbial intracellular redox balance status and impacts fermentative activity of rumen microorganisms. Taken together, proper assessment and interpretation of data generated by rumen sensors requires consideration of their limitations under various conditions.

Inline Reticulorumen pH as an Indicator of Cows Reproduction and Health Status

Our study hypothesis is that the interline registered pH of the cow reticulum can be used as an indicator of health and reproductive status. The main objective of this study was to examine the relationship of pH, using the indicators of the automatic milking system (AMS), with some parameters of cow blood components. The following four main groups were used to classify cow health status: 15-30 d postpartum, 1-34 d after insemination, 35 d after insemination (not pregnant), and 35 d (pregnant). Using the reticulum pH assay, the animals were categorized as pH < 6.22 (5.3% of cows), pH 6.22-6.42 (42.1% of cows), pH 2.6-6.62 (21.1% of cows), and pH > 6.62 (10.5% of cows). Using milking robots, milk yield, fat protein, lactose level, somatic cell count, and electron conductivity were registered. Other parameters assessed included the temperature and pH of the contents of reticulorumens. Assessment of the aforementioned parameters was done using specific smaX-tec boluses. Blood gas parameters were assessed using a blood gas analyzer (EPOC (Siemens Healthcare GmbH, Erlangen, Germany). The study findings indicated that pregnant cows have a higher pH during insemination than that of non-pregnant ones. It was also noted that cows with a low fat/protein ratio, lactose level, and high SCC had low reticulorumen pH. They also had the lowest blood pH. It was also noted that, with the increase of reticulorumen pH, there was an increased level of blood potassium, a high hematocrit, and low sodium and carbon dioxide saturation.

Effects of Different Concentrate Feed Proportions on Ruminal Ph Parameters, Duodenal Nutrient Flows and Efficiency of Microbial Crude Protein Synthesis in Dairy Cows During Early Lactation

The aim of the study was to examine different pH parameters, such as variations throughout the day, depending on differing concentrate feed proportions. Moreover, special attention was payed to individual variation in microbial efficiencies (microbial crude protein/fermented organic matter) and their relation to ruminal pH, nutrient flows and digestibilities. For this, cows were grouped according to microbial efficiency (more, n = 5, vs. less efficient cows, n = 4). After calving, thirteen ruminally cannulated pluriparous cows, including nine duodenally cannulated animals, were divided into groups offered rations with a lower (35% on dry matter basis, n = 7) or a higher (60% on dry matter basis, n = 6) concentrate feed proportion. Ruminal pH parameters were assessed continuously by using intraruminal probes. Nutrient flows, nutrient digestibility and microbial efficiency were determined for duodenally cannulated cows. For most ruminal pH parameters it seemed that individual variability was higher than the treatment effect. However, a positive relationship between actual concentrate intake and diurnal pH fluctuations was found. Besides, the effect of individually different microbial efficiencies was assessed. Again, there were no group differences for pH parameters. However, nutrient flows were significantly higher in more efficient cows, whereas digestibilities were lower in in more efficient cows.