Predicting CO2 production of lactating dairy cows from animal, dietary, and production traits using an international dataset.

Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called "Sniffer-technique") and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4 emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore develop different models to be used for different scenarios, depending on available data. An international data set with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk and days pregnant, was compiled to constitute the training data set. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber (RC) or GreenFeed (GF)) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training data set: Model 1 ("Best Model"), where all significant traits were included, Model 2 ("On-Farm Model"), where DMI was excluded, and Model 3 ("Reduced On-Farm Model"), where both DMI and BW were excluded. Evaluation on test data sets either with RC data (n = 103), GF data without additives (n = 478) or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic over-prediction and under-prediction of CO2 production when the models were evaluated on the GF and the RC test data set, respectively. To address this bias, the 3 models were evaluated on a modified test data set, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test data sets. By this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.

Influence of dietary fiber content and horn status on thermoregulatory responses of Brown Swiss dairy cows under thermoneutral and short-term heat stress conditions.

In the present experiment, 10 horned and 10 disbudded mid-lactating Brown Swiss cows were included in a crossover feeding trial with a hay or hay and concentrate diet. The effects of dietary neutral detergent fiber (NDF) content and horn status on thermoregulatory responses under thermoneutral and short-term heat stress conditions were studied, as both are considered to ease the cow's thermoregulation under an environmental heat load. Cows received either ad libitum hay and alfalfa pellets (85:15, C-, NDF content: 41.0%) or restricted amounts of hay and concentrate (70:30, C+, NDF content: 34.5%). The level of restriction applied with the C+ diet was determined from pre-experimental ad libitum intakes, ensuring that both diets provided the same intake of net energy for lactation (NEL). For data collection, cows were housed in respiration chambers for 5 d. The climatic conditions were 10°C and 60% relative humidity (RH), considered thermoneutral (TN) conditions (temperature-humidity index (THI): 52) for d 1 and 2, and 25°C and 70% RH, considered heat stress (HS) conditions (THI: 74), for d 4 and 5. On d 3, the temperature and RH were increased gradually. Compared with TN, HS conditions increased the water intake, skin temperature, respiration and heart rates, and endogenous heat production. They did not affect body temperature, feed intake, or milk production. Lowering dietary fiber content via concentrate supplementation lowered methane and increased carbon dioxide production. It did not mitigate physiological responses to HS. Although the responses of horned and disbudded cows were generally similar, the slower respiration rates of horned cows under HS conditions indicate a possible, albeit minor, role of the horn in thermoregulation. In conclusion, future investigations on nutritional strategies must be conducted to mitigate mild heat stress.

Influence of lactation stage on heat production and macronutrient oxidation in dairy cows during a 24-hour fasting period.

Understanding nutrient utilization and partitioning is essential for advancing the efficiency of dairy cattle. Our objective was to determine if dairy cows exposed to a 24-h fasting period differ in heat production (HP) and macronutrient oxidation at different stages of lactation. Twelve primiparous, lactating German Holstein dairy cows were used in a longitudinal study design spanning from 2013 to 2014. Dairy cows were housed in respiration chambers during 3 stages of the lactation cycle: early (mean ± SD; 28.8 ± 6.42 d), mid- (89.4 ± 4.52 d), and late (293 ± 7.76 d) lactation. Individual CO2, O2, and CH4 gas exchanges were measured every 6 min for two 24-h periods, an ad libitum period and fasting period (RES). Blood was sampled at the start and end of the RES period. Gas measurements were used to calculate HP, net carbohydrate oxidation (COX), and net fat oxidation (FOX). Measurements were corrected with metabolic BW (kg of BW0.75; cBW). The RES period for each stage of lactation was further subdivided into the start (RESstart) and end (RESend) by averaging the first and last 2 h of the RES period. The net change was calculated as RESend - RESstart. All energy variables differed among lactation stage within the RES period except for HP/cBW. As expected, COX, COX/cBW, COX/HP, HP, and HP/cBW, were greater at the RESstart compared with RESend, whereas FOX, FOX/cBW, and FOX/HP were greater at the RESend except for FOX and FOX/cBW during mid lactation, which was only a tendency for a difference. The net change for COX, COX/cBW, HP, HP/cBW, and FOX/cBW did not differ among stages of lactation. Despite detecting a tendency for a difference among stage of lactation for FOX, pairwise analysis revealed no differences. Plasma triglyceride, urea, and nonesterified fatty acid concentrations were greater at RESend than RESstart. The net change for plasma glucose, urea, ß-hydroxybutyrate, and nonesterified fatty acid concentrations were greater in early than late lactation. Our results demonstrate that despite differences in absolute measurements of energy variables and plasma metabolites, the change in whole-body macronutrient oxidation and HP as cows' transition from a fed-like state to a starvation-like state during a 24-h fasting period is consistent throughout lactation.

Enteric methane emission factors, total emissions and intensities from Germany's livestock in the late 19th century: A comparison with the today's emission rates and intensities.

In its climate protection law, Germany pursues the aim of achieving greenhouse gas neutrality by 2045. To approach this aim, the emissions from all sectors shall be reduced by 65 % by 2030 relative to 1990 and this includes mitigation of enteric methane (CH4) emissions from livestock. The enteric CH4 emission rate must be reduced to 853 kt CH4 by 2030, but if this target rate reaches the level of the pre-agroindustrial era remains to be evaluated. The present study aimed to determine enteric CH4 emission factors, emission rates and intensities for Germany in the 19th century. Historical data about animal numbers in the German Empire were normalized to Germany's current territory. Body weight and performance data of livestock were available for 1883 and 1892. By using Tier 1 and Tier 2 approaches we found that oxen and bulls had the greatest emission factors, followed by dairy cows and young cattle. The annual enteric CH4 emissions from livestock amounted to 898 kt in 1883 and 1061 kt in 1892. Thus, the 2030-emission target is set 45 kt below the emission level of 1883, and livestock in Germany has been emitting comparable amounts or less enteric CH4 since 2003 relative to 1892. Animal performance increased, and while CH4 emission intensities for meat and milk production decreased from 1883 to 1892, these values were higher than values from 1991 to 2020. Although the human population of Germany's current territory more than doubled in the last 130 years, increased gain in animal performance allowed for the reduction in the numbers of ruminants at least during the last 35 years, resulting in declining CH4 emissions. Such a strategy may also be applied by other countries with steadily increasing human populations to balance CH4 emissions and food production from livestock.

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis.

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

Dietary fiber and its role in performance, welfare, and health of pigs.

Dietary fiber (DF) is receiving increasing attention, and its importance in pig nutrition is now acknowledged. Although DF for pigs was frowned upon for a long time because of reductions in energy intake and digestibility of other nutrients, it has become clear that feeding DF to pigs can affect their well-being and health. This review aims to summarize the state of knowledge of studies on DF in pigs, with an emphasis on the underlying mode of action, by considering research using DF in sows as well as suckling and weaned piglets, and fattening pigs. These studies indicate that DF can benefit the digestive tracts and the health of pigs, if certain conditions or restrictions are considered, such as concentration in the feed and fermentability. Besides the chemical composition and the impact on energy and nutrient digestibility, it is also necessary to evaluate the possible physical and physiologic effects on intestinal function and intestinal microbiota, to better understand the relation of DF to animal health and welfare. Future research should be designed to provide a better mechanistic understanding of the physiologic effects of DF in pigs.

Differences in net fat oxidation, heat production, and liver mitochondrial DNA copy numbers between high and low feed-efficient dairy cows.

Improving feed utilization efficiency in dairy cattle could have positive economic and environmental effects that would support the sustainability of the dairy industry. Identifying key differences in metabolism between high and low feed-efficient animals is vital to enhancing feed conversion efficiency. Therefore, our objectives were (1) to determine whether cows grouped by either high or low feed efficiency have measurable differences in net fat and carbohydrate metabolism that account for differences in heat production (HP), and if so, whether these differences also exists under conditions of feed withdrawal when the effect of feeding on HP is minimized, and (2) to determine whether the abundance of mitochondria in the liver can be related to the high or low feed-efficient groups. Ten dairy cows from a herd of 15 (parity = 2) were retrospectively grouped into either a high (H) or a low (L) feed-efficient group (n = 5 per group) based on weekly energy-corrected milk (ECM) divided by dry mater intake (DMI) from wk 4 through 30 of lactation. Livers were biopsied at wk -4, 2, and 12, and blood was sampled weekly from wk -3 to 12 relative to parturition. Blood was subset to be analyzed for the transition period (wk -3 to 3) and from wk 4 to 12. In wk 5.70 ± 0.82 (mean ± SD) postpartum (PP), cows spent 2 d in respiration chambers (RC), in which CO2, O2, and CH4 gases were measured every 6 min for 24 h. Fatty acid oxidation (FOX), carbohydrate oxidation (COX), metabolic respiratory quotient (RQ), and HP were calculated from gas measurements for 23 h. Cows were fed ad libitum (AD-LIB) on d 1 and had feed withdrawn (RES, restricted diet) on d 2. Additional blood samples were taken at the end of the AD-LIB and RES feeding periods in the RC. During wk 4 to 30 PP, H had greater DMI/kg of metabolic body weight (BW0.75), ECM per kilogram of BW0.75 yield, and ECM/DMI ratio, compared with L, but a lower body condition score between wk 4 and 12 PP. In the RC period, we detected no differences in BW, DMI, or milk yield between groups. We also detected no significant group or group by feeding period interactions for plasma metabolites except for Revised Quantitative Insulin Sensitivity Check Index, which tended to have a group by feeding period interaction. The H group had lower HP and HP per kilogram of BW0.75 compared with L. Additionally, H had lower FOX and FOX per kilogram of BW0.75 compared with L during the AD-LIB period. Methane, CH4 per kilogram of BW0.75, and CH4 per kilogram of milk yield were lower in H compared with L, but, when adjusted for DMI, CH4/DMI did not differ between groups, nor did HP/DMI. Relative mitochondrial DNA copy numbers in the liver were lower in the L than in the H group. These results suggest that lower feed efficiency in dairy cows may result from fewer mitochondria per liver cell as well as a greater whole-body HP, which likely partially results from higher net fat oxidation.

Review: Pro-inflammatory cytokines and hypothalamic inflammation: implications for insufficient feed intake of transition dairy cows.

Improvements in feed intake of dairy cows entering the early lactation period potentially decrease the risk of metabolic disorders, but before developing approaches targeting the intake level, mechanisms controlling and dysregulating energy balance and feed intake need to be understood. This review focuses on different inflammatory pathways interfering with the neuroendocrine system regulating feed intake of periparturient dairy cows. Subacute inflammation in various peripheral organs often occurs shortly before or after calving and is associated with increased pro-inflammatory cytokine levels. These cytokines are released into the circulation and sensed by neurons located in the hypothalamus, the key brain region regulating energy balance, to signal reduction in feed intake. Besides these peripheral humoral signals, glia cells in the brain may produce pro-inflammatory cytokines independent of peripheral inflammation. Preliminary results show intensive microglia activation in early lactation, suggesting their involvement in hypothalamic inflammation and the control of feed intake of dairy cows. On the other hand, pro-inflammatory cytokine-induced activation of the vagus nerve transmits signalling to the brain, but this pathway seems not exclusively necessary to signal feed intake reduction. Yet, less studied in dairy cows so far, the endocannabinoid system links inflammation and the hypothalamic control of feed intake. Distinct endocannabinoids exert anti-inflammatory action but also stimulate the posttranslational cleavage of neuronal proopiomelanocortin towards ß-endorphin, an orexigen promoting feed intake. Plasma endocannabinoid concentrations and hypothalamic ß-endorphin levels increase from late pregnancy to early lactation, but less is known about the regulation of the hypothalamic endocannabinoid system during the periparturient period of dairy cows. Dietary fatty acids may modulate the formation of endocannabinoids, which opens new avenues to improve metabolic health and immune status of dairy cows.

Circulating adiponectin concentrations during the transition from pregnancy to lactation in high-yielding dairy cows: testing the effects of farm, parity, and dietary energy level in large animal numbers.

Dairy cows experience a negative energy balance due to increasing energy demands and insufficient voluntary feed intake in the transition from late pregnancy to early lactation. For supplying sufficient energy toward the conceptus and the mammary gland, insulin sensitivity in peripheral tissues is reduced leading to adipose tissue mobilization. Adiponectin, an insulin-sensitizing adipokine, is presumably related to energy metabolism and could play an important role in these metabolic adaptations. We hypothesize (1) that primiparous cows would differ from pluriparous cows in their circulating adiponectin concentrations during the transition from late pregnancy to early lactation and (2) that feeding different energy levels would affect the adiponectin concentrations during early lactation in dairy cows. For the first hypothesis, we examined 201 primiparous and 456 pluriparous Holstein dairy cows on three experimental farms. Ante partum, primiparous cows had lower adiponectin and greater NEFA concentrations than pluriparous cows, but vice versa post partum. Hence, adiponectin might be involved in the energy partitioning in primiparous cows (conceptus and lactation vs other still growing body tissues) with changing priorities from pregnancy to lactation. For the second hypothesis, 110 primiparous and 558 pluriparous Holstein and Simmental dairy cows in six experimental farms received either roughage with 6.1 or 6.5 MJ NEl/kg dry matter (adjusted with different amounts of wheat straw) ad libitum, combined with either 150 or 250 g concentrates/kg energy corrected milk. Greater amounts of concentrate lead to greater milk yield, but did not affect the blood variables. The higher energy level in the roughage led to greater glucose and IGF-1 but lower adiponectin in pluriparous cows. Further studies are needed to elucidate the mechanisms behind the roughage effect and its metabolic consequences.

Comparative analyses of estimated and calorimetrically determined energy balance in high-yielding dairy cows.

Our aim was to compare the energy balance estimated (EBest) according to equations published by various energy feeding systems (German Society for Nutrition Physiology, French National Institute for Agricultural Research, and US National Research Council) and the EB calculated by use of calorimetrically measured heat production (EBhp) of 20 high-yielding (≥10,000 kg/305 d) German Holstein cows at -4 (pregnant, nonlactating) and 2 wk (early lactation) relative to parturition. In addition to heat production, feed and water intake, physical activity (including standing-lying behavior), body weight, body condition score, body temperature, plasma concentrations of fatty acids and ß-hydroxybutyrate, milk yield, and milk composition were measured to characterize the metabolic status. The EBhp was balanced [2.74 ± 4.09 MJ of metabolizable energy (ME)/d; ±standard error] before calving, but strongly negative (-84.7 ± 7.48 MJ of ME/d) at wk 2 of lactation. At both time points, EBhp and EBest differed significantly. On average, the equations overestimated the antepartum EB by 33 MJ of ME/d and underestimated the postpartum negative EB by 67 MJ of ME/d, respectively. Because the same ME intake and energy-corrected milk values were used for calculation of EBest and EBhp in our study, we considered that the factors (0.488 to 0.534 MJ of ME/kg0.75) currently used to calculate the ME requirements for maintenance probably underestimate the needs of high-yielding dairy cows, particularly during early lactation. In accord, heat production values determined under standard conditions of thermoneutrality and locomotion restriction amounted to 0.76 ± 0.02 MJ of ME/kg0.75 (4 wk antepartum) and 1.02 ± 0.02 MJ of ME/kg0.75 (2 wk postpartum), respectively. The expected positive correlation between EBhp and DMI was observed in pregnant cows only; however, a bias of 26 MJ of ME/d between mean actual energy intake and ME intake predicted according to German Society for Nutrition Physiology was found in cows at wk 4 antepartum. At both investigated time points, mobilization of tissue energy reserves (reflected by plasma fatty acid concentration) was related to EBhp. In early lactating cows, metabolic body weight (kg0.75) and the percentage of milk fat showed the strongest correlation (correlation coefficient = -0.70 and -0.73) to EBhp. Our findings must be taken into account when experimental data are interpreted because the true energy status might be significantly overestimated when EBest is used.

Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers.

Evaluation and mitigation of enteric methane (CH4) emissions from ruminant livestock, in particular from dairy cows, have acquired global importance for sustainable, climate-smart cattle production. Based on CH4 reference measurements obtained with the SF6 tracer technique to determine ruminal CH4 production, a current equation permits evaluation of individual daily CH4 emissions of dairy cows based on milk Fourier transform mid-infrared (FT-MIR) spectra. However, the respiration chamber (RC) technique is considered to be more accurate than SF6 to measure CH4 production from cattle. This study aimed to develop an equation that allows estimating CH4 emissions of lactating cows recorded in an RC from corresponding milk FT-MIR spectra and to challenge its robustness and relevance through validation processes and its application on a milk spectral database. This would permit confirming the conclusions drawn with the existing equation based on SF6 reference measurements regarding the potential to estimate daily CH4 emissions of dairy cows from milk FT-MIR spectra. A total of 584 RC reference CH4 measurements (mean ± standard deviation of 400 ± 72 g of CH4/d) and corresponding standardized milk mid-infrared spectra were obtained from 148 individual lactating cows between 7 and 321 d in milk in 5 European countries (Germany, Switzerland, Denmark, France, and Northern Ireland). The developed equation based on RC measurements showed calibration and cross-validation coefficients of determination of 0.65 and 0.57, respectively, which is lower than those obtained earlier by the equation based on 532 SF6 measurements (0.74 and 0.70, respectively). This means that the RC-based model is unable to explain the variability observed in the corresponding reference data as well as the SF6-based model. The standard errors of calibration and cross-validation were lower for the RC model (43 and 47 g/d vs. 66 and 70 g/d for the SF6 version, respectively), indicating that the model based on RC data was closer to actual values. The root mean squared error (RMSE) of calibration of 42 g/d represents only 10% of the overall daily CH4 production, which is 23 g/d lower than the RMSE for the SF6-based equation. During the external validation step an RMSE of 62 g/d was observed. When the RC equation was applied to a standardized spectral database of milk recordings collected in the Walloon region of Belgium between January 2012 and December 2017 (1,515,137 spectra from 132,658 lactating cows in 1,176 different herds), an average ± standard deviation of 446 ± 51 g of CH4/d was estimated, which is consistent with the range of the values measured using both RC and SF6 techniques. This study confirmed that milk FT-MIR spectra could be used as a potential proxy to estimate daily CH4 emissions from dairy cows provided that the variability to predict is covered by the model.

Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models.

Ruminant production systems are important contributors to anthropogenic methane (CH4) emissions, but there are large uncertainties in national and global livestock CH4 inventories. Sources of uncertainty in enteric CH4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH4 emission factors. There is also significant uncertainty associated with enteric CH4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF6) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes.

Indices of heart rate variability as potential early markers of metabolic stress and compromised regulatory capacity in dried-off high-yielding dairy cows.

High performing dairy cows experience distinct metabolic stress during periods of negative energy balance. Subclinical disorders of the cow's energy metabolism facilitate failure of adaptational responses resulting in health problems and reduced performance. The autonomic nervous system (ANS) with its sympathetic and parasympathetic branches plays a predominant role in adaption to inadequate energy and/or fuel availability and mediation of the stress response. Therefore, we hypothesize that indices of heart rate variability (HRV) that reflect ANS activity and sympatho-vagal balance could be early markers of metabolic stress, and possibly useful to predict cows with compromised regulatory capacity. In this study we analysed the autonomic regulation and stress level of 10 pregnant dried-off German Holstein cows before, during and after a 10-h fasting period by using a wide range of HRV parameters. In addition heat production (HP), energy balance, feed intake, rumen fermentative activity, physical activity, non-esterified fatty acids, ß-hydroxybutyric acid, cortisol and total ghrelin plasma concentrations, and body temperature (BT) were measured. In all cows fasting induced immediate regulatory adjustments including increased lipolysis (84%) and total ghrelin levels (179%), reduction of HP (-16%), standing time (-38%) and heart rate (-15%). However, by analysing frequency domain parameters of HRV (high-frequency (HF) and low-frequency (LF) components, ratio LF/HF) cows could be retrospectively assigned to groups reacting to food removal with increased or decreased activity of the parasympathetic branch of the ANS. Regression analysis reveals that under control conditions (feeding ad libitum) group differences were best predicted by the nonlinear domain HRV component Maxline (L MAX, R 2=0.76, threshold; TS=258). Compared with cows having L MAX values above TS (>L MAX: 348±17), those with L MAX values below TS (L MAX cows (18.5±0.4 and 47.3 kg/day). From the present study, it seems conceivable that L MAX can be used as a predictive marker to discover alterations in central autonomic regulation that might precede metabolic disturbances.

Rapid Communication: Ranking dairy cows for methane emissions measured using respiration chamber or GreenFeed techniques during early, peak, and late lactation.

Our objective was to compare the ranking of dairy cows according to their methane (CH) emissions as measured by a respiration chamber (RC) technique and the GreenFeed (GF) technique during 3 periods in second lactation. Two-day CH measurements in a RC performed in wk 3, 14, and 42 of lactation were flanked by GF measurements for 20 (period 1 [P1]), 35 (period 2 [P2]), and 35 (period 3 [P3]) days, respectively, before and after RC measurement. This gave the total duration of CH measurements using the GF system of 40, 70, and 70 d for P1, P2, and P3, respectively. Mean daily CH production (g/d) of the 8 dairy cows was 346, 439, and 430 using the RC technique and 338, 378, and 416 using the GF system during P1, P2, and P3, respectively. Average daily CH production determined by the GF technique was 2.4, 13.8, and 3.2% lower in P1, P2, and P3, respectively. Methane normalized to DMI continuously increased from P1 to P3 when measured in a RC, whereas it was lowest during P2 when measured by the GF method. Ranking of the cows according to CH production, CH/energy-corrected milk yield (ECM; CH/ECM), and CH/DMI differed between periods no matter which method was used. Cluster analysis including all 3 periods, however, identified the same cows with the highest and lowest CH production determined either by the RC technique or the GF system. In conclusion, multiple CH measurements at different stages of lactation are necessary for reliable discrimination of highest and lowest CH emitting cows and the GF system may be used to discriminate the extremes.

Short communication: Free fatty acid receptors FFAR1 and FFAR2 during the peripartal period in liver of dairy cows grouped by their postpartum plasma ß-hydroxybutyrate concentrations.

Free fatty acid receptors (FFAR) play significant roles in various physiological processes, including energy metabolism, through interaction with their ligands, fatty acids. To determine whether the receptors FFAR1 and FFAR2 are involved in the regulation of liver metabolism during the peripartal period, we selected 13 German Holstein multiparous dairy cows and grouped them as high ß-hydroxybutyrate (H-BHB; n = 8) or low ß-hydroxybutyrate (L-BHB; n = 5) according to their individual maximum plasma BHB concentration observed within wk 2 or 3 postpartum (H-BHB: >1 mmol/L and L-BHB: <0.77 mmol/L). The selected cows had a milk yield of more than 10,000 kg/305 d during a previous lactation. The cows were fed a total mixed ration according to their requirements during the far-off dry period [5.9 MJ of net energy for lactation (NEL)/kg of dry matter (DM), crude protein (CP) 126 g/kg of DM], close-up dry period (6.5 MJ of NEL/kg of DM, CP 137 g/kg of DM), and lactation (7 MJ of NEL/kg of DM, CP 163 g/kg of DM). Blood samples were taken weekly, from d -34 to d 40 relative to parturition. Liver biopsies were taken on d -34, -17, 3, 18, and 30 relative to parturition and at slaughter (d 40). The protein abundance of FFAR1 was lower during the whole peripartal period in the H-BHB group. The abundance of FFAR2 increased over time and tended to be higher in H-BHB cows. The abundance of FFAR1 might be associated with imbalances of liver metabolism in peripartal dairy cows.

Variable liver fat concentration as a proxy for body fat mobilization postpartum has minor effects on insulin-induced changes in hepatic gene expression related to energy metabolism in dairy cows.

The liver plays a central role in adaptation for energy requirements around calving, and changes in the effects of insulin on hepatic energy metabolism contribute to metabolic adaptation in dairy cows. Hepatic insulin effects may depend on body fat mobilization. The objective of this study was to investigate the effects of insulin on the hepatic gene expression of enzymes involved in energy metabolism and factors related to nutrition partitioning in cows with high and low total liver fat concentration (LFC) after calving. Holstein cows were retrospectively grouped according to their LFC after calving as a proxy for body fat mobilization. Cows were classified as low (LLFC; LFC <24% fat/dry matter; n = 9) and high (HLFC; LFC >24.4% fat/dry matter; n = 10) fat-mobilizing after calving. Euglycemic-hyperinsulinemic clamps [6 mU/(kg × min) of insulin for 6 h] were performed in wk 5 antepartum (ap) and wk 3 postpartum (pp). Before and at the end of the euglycemic-hyperinsulinemic clamps, liver biopsies were taken to measure the mRNA abundance of enzymes involved in carbohydrate and lipid metabolism, expression related to the somatotropic axis, and adrenergic and glucocorticoid receptors. The mRNA abundance of pyruvate carboxylase, cytosolic phosphoenolpyruvate carboxykinase (PEPCK; PCK1), acyl-CoA-dehydrogenase very long chain (ACADVL), and hydroxyl-methyl-glutaryl-CoA-synthase 1 increased, but the mRNA abundance of solute carrier family 2 (SLC2A2 and SLC2A4), growth hormone receptor 1A (GHR1A), insulin-like growth factor 1 (IGF1), sterol regulatory element binding factor 1, adrenoceptor α 1A, and glucocorticoid receptor decreased from ap to pp. Insulin treatment was associated with decreased PCK1, mitochondrial PEPCK, glucose-6-phosphatase, propionyl-CoA-carboxylase α, carnitine-palmitoyl-transferase 1A, ACADVL, and insulin receptor mRNA, but increased IGF1 and SLC2A4 mRNA ap and pp and GHR1A mRNA pp. The mRNA abundance of SLC2A4 was greater, and the mRNA abundance of GHR1A and IGF1 tended to be lower in LLFC than in HLFC. Administration of insulin, albeit at a supraphysiological dose, was associated with inhibition of gene expression related to glucose production and ß-oxidation, but we observed variable effects in the degree of insulin depression of individual genes. Insulin status is important for regulation of nutrient partitioning, but different LFC pp had very little influence on changes in hepatic gene expression following administration of insulin.

Technical note: Analytical refinements of the methane indicator archaeol in bovine feces, rumen fluid, and feedstuffs.

Archaeol (1,2-di-O-phytanyl-sn-glycerol) is a cell membrane lipid component of methanogens that has the potential to be used as a biomarker for methane production in ruminants. However, its analysis via gas chromatography-mass spectrometry (GC-MS) is challenging because of its molecular size and structure. In this study, 2 different sample preparation methods were tested, Soxhlet and sonication-aided extraction, and the methods were compared for extraction efficiency using the internal standard (IS; 1,2-di-o-hexadecyl-rac-glycerol). The extraction efficiency of the Soxhlet method for fecal archaeol was twice that of sonication. With the use of a high-temperature GC column, the retention times of IS and archaeol were 17.6 and 19.4 min, respectively, with a total run time of only 25 min. The molecule ions m/z 611.4 (IS) and m/z 725.8 (archaeol), or alternatively the fragment ion of the glycerol moiety m/z 130.0, were used for identification and quantification via GC-MS in positive chemical ionization mode. The intra-assay coefficients of variation for fecal archaeol measurements were 1.3% (m/z 725.8) and 2.1% (m/z 130.0) (n=3), respectively. Fecal archaeol quantifications did not differ between the use of the molecule or glycerol moiety ions (paired t-test, n=156). Archaeol concentrations tended to be 3.3% greater in samples stored at -20°C before drying compared with samples that were immediately dried after collection (paired t-test, n=5). The detection limit of archaeol was 0.5 µg/g of fecal dry matter (DM); no archaeol could be detected in feed samples. In different fractions of rumen fluid, archaeol levels ranged from 1.9 to 24.0 µg/g of DM. In 10 cows fed the same grass and corn silage/hay-based ration, diurnal variations of fecal archaeol levels (5 time points over 2 d) were cow dependent and ranged from 26.2 to 77.2 µg/g of DM (mean 48.4 µg/g of DM). Thus, within-animal variation in cows on the same diet was between 4 and 27%. We suggest that this finding is related to the amount and time of the latest feed intake event before the fecal sampling. Feeding pattern can determine the passage rate of digesta through the alimentary tract and thus the duration of contact time of archaea with their substrate.