Developing a tool to assess the health-related quality of life in calves with respiratory disease: content validation.

Bovine respiratory disease (BRD) is a major welfare and productivity issue for calves. Despite the extensive negative impacts on calf welfare and performance, BRD remains challenging to detect and treat effectively. However, the clinical signs of disease are only one aspect of the disease that is experienced by the individual. The assessment of emotional experience in animals is not straightforward, but it is increasingly recognised that the quality of behaviour and demeanour of an individual is a reflection of their internal emotional state. The aim of the present study was to complete the content validation stage of the development process for a health-related quality of life (HRQOL) tool. This was based around indicators from an existing conceptual framework containing twenty-three indicators in two domains (clinical signs and behavioural expression). The content validation stage involves engaging with key stakeholders. For this study, this took the form of a survey and discussions with focus groups, which are standard methods in this field. A survey and stakeholder focus groups were conducted to assess the usefulness of each indicator and its relevance for inclusion within a HRQOL tool. In the survey, participants were asked to rate the usefulness of each of the indicators using a 4-point scale which were then dichotomised into 'useful' and 'less useful'. Based on the 'useful' result, each indicator within the domains was ranked. A similar approach was taken with the responses from the focus groups. Focus group participants were asked to select indicators that they felt were of use and the result of this was used to rank each of the indicators. The ranks of the indicators from both the survey and the focus groups along with the transcripts from the focus groups were used to determine the indicators from each domain to include within the HRQOL tool. Indicators within the clinical signs domain that were included were nasal discharge, cough, respiratory effort, ocular appearance (discharge and vibrancy), body and head posture and ear carriage. For the domain of behavioural expression, the indicators included were movement to feed, responsiveness, spatial proximity, volume of feed intake, motivation at feed and vigour. The next stage will be to validate the construction of the HRQOL tool through its use in practice. The inclusion of indicators that allow the experiential aspects of disease to be recorded in health assessments will likely increase the ability of farmers and others to detect respiratory disease in calves.

Early prediction of respiratory disease in preweaning dairy calves using feeding and activity behaviors.

Bovine respiratory disease (BRD) represents one of the major disease challenges affecting preweaning dairy-bred calves. Previous studies have shown that differences in feeding and activity behaviors exist between healthy and diseased calves affected by BRD. The aim of this study was to develop and assess the accuracy of models designed to predict BRD from feeding and activity behaviors. Feeding and activity behaviors were recorded for 100 male preweaning calves between ~8 to 42 d of age. Calves were group housed with ad libitum access to milk via automatic milk feeders, water, starter diet, and straw. Activity was monitored via a leg-mounted accelerometer. Health status of individual calves was monitored daily using an adapted version of the Wisconsin Scoring System to identify BRD. Three models were created to predict disease: (1) deviation from normal lying time based on moving averages (MA); (2) random forest (RF), a machine learning technique based on feeding and activity variables; and (3) a combination of RF and MA output. For the MA model, lying time was predicted based on behavior over previous days (3- and 7-d MA) and the expected value for the current day (based on calf age; measured using accelerometers). Data were not split into training and test data sets. Occasions when the actual lying time increased >9% of predicted lying time were classified as a deviation from normal and a disease alert was provided. Both feeding and activity behaviors were included within the RF model. Data were split into training (70%) and test (30%) data sets based on disease events. Events were classified as 2 d before, the day(s) of the disease event, and 2 d after the event. Accuracy of models was assessed using sensitivity, specificity, balanced accuracy, and Matthews correlation coefficient (MCC). If a positive disease prediction agreed with an actual disease event within a 3-d rolling window, it was classified as a true positive. Stand-alone models (RF; MA) showed high specificity (0.95; 0.97), moderate sensitivity (0.35; 0.43), balanced accuracy (0.65; 0.64), and MCC (0.25; 0.29). Combining outputs increased accuracy (specificity = 0.95, sensitivity = 0.54, balanced accuracy = 0.75, MCC = 0.36). The work presented is the first to demonstrate the use of modeling data derived from precision livestock farming techniques that monitor feeding and activity behaviors for early detection of BRD in preweaning calves, offering a significant advance in health management of youngstock.

Predicting feed intake using modelling based on feeding behaviour in finishing beef steers.

Current techniques for measuring feed intake in housed cattle are both expensive and time-consuming making them unsuitable for use on commercial farms. Estimates of individual animal intake are required for assessing production efficiency. The aim of this study was to predict individual animal intake using parameters that can be easily obtained on commercial farms including feeding behaviour, liveweight and age. In total, 80 steers were used, and each steer was allocated to one of two diets (40 per diet) which consisted of (g/kg; DM) forage to concentrate ratios of either 494:506 (MIXED) or 80:920 (CONC). Individual daily fresh weight intakes (FWI; kg/day) were recorded for each animal using 32 electronic feeders over a 56-day period, and individual DM intakes (DMI; kg/day) subsequently calculated. Individual feeding behaviour variables were calculated for each day of the measurement period from the electronic feeders and included: total number of visits to the feeder, total time spent at the feeder (TOTFEEDTIME), total time where feed was consumed (TIMEWITHFEED) and average length of time during each visit to the feeder. These feeding behaviour variables were chosen due to ease of obtaining from accelerometers. Four modelling techniques to predict individual animal intake were examined, based on (i) individual animal TOTFEEDTIME relative expressed as a proportion of the dietary group (GRP) and total GRP intake, (ii) multiple linear regression (REG) (iii) random forests (RF) and (iv) support vector regressor (SVR). Each model was used to predict CONC and MIXED diets separately, giving eight prediction models, (i) GRP_CONC, (ii) GRP_MIXED, (iii) REG_CONC, (iv) REG_MIXED, (v) RF_CONC, (vi) RF_MIXED, (vii) SVR_CONC and (viii) SVR_MIXED. Each model was tested on FWI and DMI. Model performance was assessed using repeated measures correlations (R2_RM) to capture the repeated nature of daily intakes compared with standard R2, RMSE and mean absolute error (MAE). REG, RF and SVR models predicted FWI with R2_RM = 0.1-0.36, RMSE = 1.51-2.96 kg and MAE = 1.19-2.49 kg, and DMI with R2_RM = 0.13-0.19, RMSE = 1.15-1.61 kg and MAE = 0.9-1.28 kg. The GRP models predicted FWI with R2_RM = 0.42-0.49, RMSE = 2.76-3.88 kg and MAE = 2.46-3.47 kg, and DMI with R2_RM = 0.32-0.44, RMSE = 0.32-0.44 kg, MAE = 1.55-2.22 kg. Whilst more simplistic GRP models showed higher R2_RM than regression and machine learning techniques, these models had larger errors, likely due to individual feeding patterns not being captured. Although regression and machine learning techniques produced lower errors associated with individual intakes, overall precision of prediction was too low for practical use.

Feeding behaviour and activity as early indicators of disease in pre-weaned dairy calves.

Across the industry, there is large variation in health status of dairy calves and as a result, disease incidence and antibiotic use is high. This has significant implications for animal welfare, productivity and profitability of dairy and dairy-beef production systems. Technology-based early detection systems could alleviate these issues; however, methods of early detection of disease in dairy calves have not been widely explored. This study aimed to determine whether changes in activity and feeding behaviour can be used as early warning indicators of respiratory disease in calves. In total, 100 pre-weaned male Holstein calves (age: ~8-42 days) were used. Calves were group-housed and provided with starter diet, straw bedding and ad libitum water. Calves were fed milk replacer ad libitum through an automatic calf feeder, and each calf was fitted with a leg-mounted activity monitor. Daily activity and feeding behaviour variables were calculated for each calf. Each calf was assessed daily using a modified version of the Wisconsin Scoring System to assess respiratory disease status. Calves were classed as 'Diseased', 'Intermediate' or 'Healthy' based on their cumulative health score. The peak day of the most extreme illness event was identified for each calf. Data from Diseased and Healthy calves were paired for analysis based on age and BW. Data were compared for the day of peak illness, and for the 3 days previous and post. Compared to healthy calves, diseased calves lay for longer and tended to have longer lying bouts (daily lying: 17.6 ±â€¯0.3 vs 16.7 ±â€¯0.2 h, P < 0.01; bout length: 74.8 ±â€¯10.6 vs 56.0 ±â€¯3.7 min, P = 0.09 for diseased and healthy calves, respectively). Diseased calves fed for a shorter time and had fewer feeder visits (with intake) each day compared to healthy calves (feeding time (min): 19.3 ±â€¯1.4 vs 22.8 ±â€¯1.5; P < 0.05; visits: 2.1 ±â€¯0.2 vs 3.2 ±â€¯0.4; P < 0.05). Importantly, differences between diseased and healthy calves were evident in both activity and feeding behaviour on the days prior to the peak day of disease. Lying bout length was greater in diseased calves for the 2 days prior to the peak day (P < 0.05), lying time was longer on day -1 (P < 0.05) and feeder visits with milk intake were less frequent on day -3 (P < 0.05). Thus, measurement of feeding and activity using precision technology within early detection systems could facilitate early intervention and optimized treatment.

Using animal-mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows.

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew's correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf.

Temperament and dominance relate to feeding behaviour and activity in beef cattle: implications for performance and methane emissions.

In beef cattle, feeding behaviour and activity are associated with feed efficiency and methane (CH4) emissions. This study aimed to understand the underlying traits responsible for the contribution of cattle behaviour to individual differences in feed efficiency, performance and CH4 emissions. A total of 84 steers (530±114 kg BW) of two different breeds (crossbreed Charolais and Luing) were used. The experiment was a 2×2×3 factorial design with breed, basal diets (concentrate v. mixed) and dietary treatments (no additive, calcium nitrate or rapeseed cake) as the main factors. The individual dry matter intake (DMI; kg) was recorded daily and the BW was measured weekly over a 56-day period. Ultrasound fat depth was measured on day 56. Based on the previous data, the indexes average daily gain, food conversion and residual feed intake (RFI) were calculated. The frequency of meals, the duration per visit and the time spent feeding per day were taken as feeding behaviour measures. Daily activity was measured using the number of steps, the number of standing bouts and the time standing per day. Agonistic interactions (including the number of contacts, aggressive interactions, and displacements per day) between steers at the feeders were assessed as indicators of dominance. Temperament was assessed using the crush score test (which measures restlessness when restrained) and the flight speed on release from restraint. Statistical analysis was performed using multivariate regression models. Steers that spent more time eating showed better feed efficiency (P=0.039), which can be due to greater secretion of saliva. Feeding time was longer with the mixed diet (P<0.001), Luings (P=0.009) and dominant steers (P=0.032). Higher activity (more steps) in the pen was associated with poorer RFI, possibly because of higher energy expenditure for muscle activity. Frequent meals contributed to a reduction in CH4 emissions per kg DMI. The meal frequency was higher with a mixed diet (P<0.001) and increased in more temperamental (P=0.003) and dominant (P=0.017) steers. In addition, feed intake was lower (P=0.032) in more temperamental steers. This study reveals that efficiency increases with a longer feeding time and CH4 emissions decrease with more frequent meals. As dominant steers eat more frequently and for longer, a reduction in competition at the feeder would improve both feed efficiency and CH4 emissions. Feed efficiency can also be improved through a reduction in activity. Selection for calmer cattle would reduce activity and increase feed intake, which may improve feed efficiency and promote growth, respectively.

The effect of dietary addition of nitrate or increase in lipid concentrations, alone or in combination, on performance and methane emissions of beef cattle.

Adding nitrate to or increasing the concentration of lipid in the diet are established strategies for reducing enteric methane (CH4) emissions, but their effectiveness when used in combination has been largely unexplored. This study investigated the effect of dietary nitrate and increased lipid included alone or together on CH4 emissions and performance traits of finishing beef cattle. The experiment was a 2×4 factorial design comprising two breeds (cross-bred Aberdeen Angus (AAx) and cross-bred Limousin (LIMx) steers) and four dietary treatments (each based on 550 g forage : 450 g concentrate/kg dry matter (DM)). The four dietary treatments were assigned according to a 2×2 factorial design where the control treatment contained rapeseed meal as the main protein source, which was replaced either with nitrate (21.5 g nitrate/kg DM); maize distillers dark grains (MDDG, which increased diet ether extract from 24 to 37 g/kg DM) or both nitrate and MDDG. Steers (n=20/dietary treatment) were allocated to each of the four treatments in equal numbers of each breed with feed offered ad libitum. After 28 days adaptation to dietary treatments, individual animal intake, performance and feed efficiency were recorded for 56 days. Thereafter, CH4 emissions were measured over 13 weeks (six steers/week). Increasing dietary lipid did not adversely affect animal performance and showed no interactions with dietary nitrate. In contrast, addition of nitrate to diets resulted in poorer live-weight gain (P<0.01) and increased feed conversion ratio (P<0.05) compared with diets not containing nitrate. Daily CH4 output was lower (P<0.001) on nitrate-containing diets but increasing dietary lipid resulted in only a non-significant reduction in CH4. There were no interactions associated with CH4 emissions between dietary nitrate and lipid. Cross-bred Aberdeen Angus steers achieved greater live-weight gains (P<0.01), but had greater DM intakes (P<0.001), greater fat depth (P<0.01) and poorer residual feed intakes (P<0.01) than LIMx steers. Cross-bred Aberdeen Angus steers had higher daily CH4 outputs (P<0.001) but emitted less CH4 per kilogram DM intake than LIMx steers (P<0.05). In conclusion, inclusion of nitrate reduced CH4 emissions in growing beef cattle although the efficacy of nitrate was less than in previous work. When increased dietary lipid and nitrate inclusion were combined there was no evidence of an interaction between treatments and therefore combining different nutritional treatments to mitigate CH4 emissions could be a useful means of achieving reductions in CH4 while minimising any adverse effects.

The impact of divergent breed types and diets on methane emissions, rumen characteristics and performance of finishing beef cattle.

This study was undertaken to further develop our understanding of the links between breed, diet and the rumen microbial community and determine their effect on production characteristics and methane (CH4) emissions from beef cattle. The experiment was of a 2×2 factorial design, comprising two breeds (crossbred Charolais (CHX); purebred Luing (LU)) and two diets (concentrate-straw or silage-based). In total, 80 steers were used and balanced for sire within each breed, farm of origin and BW across diets. The diets (fed as total mixed rations) consisted of (g/kg dry matter (DM)) forage to concentrate ratios of either 500 : 500 (Mixed) or 79 : 921 (Concentrate). Steers were adapted to the diets over a 4-week period and performance and feed efficiency were then measured over a 56-day test period. Directly after the 56-day test, CH4 and carbon dioxide (CO2) emissions were measured (six steers/week) over a 13-week period. Compared with LU steers, CHX steers had greater average daily gain (ADG; P<0.05) and significantly (P<0.001) lower residual feed intake. Crossbred Charolais steers had superior conformation and fatness scores (P<0.001) than LU steers. Although steers consumed, on a DM basis, more Concentrate than Mixed diet (P<0.01), there were no differences between diets in either ADG or feed efficiency during the 56-day test. At slaughter, however, Concentrate-fed steers were heavier (P<0.05) and had greater carcass weights than Mixed-fed steers (P<0.001). Breed of steer did not influence CH4 production, but it was substantially lower when the Concentrate rather than Mixed diet was fed (P<0.001). Rumen fluid from Concentrate-fed steers contained greater proportions of propionic acid (P<0.001) and lower proportions of acetic acid (P<0.001), fewer archaea (P<0.01) and protozoa (P=0.09), but more Clostridium Cluster XIVa (P<0.01) and Bacteroides plus Prevotella (P<0.001) than Mixed-fed steers. When the CH4 to CO2 molar ratio was considered as a proxy method for CH4 production (g/kg DM intake), only weak relationships were found within diets. In conclusion, although feeding Concentrate and Mixed diets produced substantial differences in CH4 emissions and rumen characteristics, differences in performance were influenced more markedly by breed.

Impact of adding nitrate or increasing the lipid content of two contrasting diets on blood methaemoglobin and performance of two breeds of finishing beef steers.

Adding nitrate to the diet or increasing the concentration of dietary lipid are effective strategies for reducing enteric methane emissions. This study investigated their effect on health and performance of finishing beef cattle. The experiment was a two×two×three factorial design comprising two breeds (CHX, crossbred Charolais; LU, Luing); two basal diets consisting of (g/kg dry matter (DM), forage to concentrate ratios) 520 : 480 (Mixed) or 84 : 916 (Concentrate); and three treatments: (i) control with rapeseed meal as the main protein source replaced with either (ii) calcium nitrate (18 g nitrate/kg diet DM) or (iii) rapeseed cake (RSC, increasing acid hydrolysed ether extract from 25 to 48 g/kg diet DM). Steers (n=84) were allocated to each of the six basal diet×treatments in equal numbers of each breed with feed offered ad libitum. Blood methaemoglobin (MetHb) concentrations (marker for nitrate poisoning) were monitored throughout the study in steers receiving nitrate. After dietary adaptation over 28 days, individual animal intake, performance and feed efficiency were recorded for a test period of 56 days. Blood MetHb concentrations were low and similar up to 14 g nitrate/kg diet DM but increased when nitrate increased to 18 g nitrate/kg diet DM (P0.05). Neither basal diet nor treatment affected carcass quality (P>0.05), but CHX steers achieved a greater killing out proportion (P<0.001) than LU steers. Thus, adding nitrate to the diet or increasing the level of dietary lipid through the use of cold-pressed RSC, did not adversely affect health or performance of finishing beef steers when used within the diets studied.

The effects on cow performance and calf birth and weaning weight of replacing grass silage with brewers grains in a barley straw diet offered to pregnant beef cows of two different breeds.

The effects on cow and calf performance of replacing grass silage with brewers grains in diets based on barley straw and fed to pregnant beef cows are reported. Using a 2 × 2 factorial arrangement of breed and diet, cows pregnant by artificial insemination (n = 34) of two breeds (cross-bred Limousin, n = 19 and pure-bred Luing, n = 15) were fed diets ad libitum which consisted of either (g/kg dry matter) barley straw (664) and grass silage (325; GS) or barley straw (783) and brewers grains (206, BG) and offered as total mixed rations. From gestation day (GD) 168 until 266, individual daily feed intakes were recorded and cow body weight (BW) and body condition score (BCS) measured weekly. Calving date, calf sex, birth and weaning BW, and calf age at weaning were also recorded. Between GD 168 and 266, cross-bred Limousin cows gained more weight than Luing cows (p < 0.05) and cows offered BG gained more weight than cows offered GS (p < 0.001). Luing cows lost more BCS than cross-bred Limousin cows (p < 0.05), but diet did not affect BCS. There were no differences in dry matter intake as a result of breed or diet. Calf birth BW, however, was greater for cows fed BG than GS (44 vs. 38 kg, SEM 1.0, p < 0.001) with no difference between breeds. At weaning, calves born to BG-fed cows were heavier than those born to GS-fed cows (330 vs. 286 kg, SEM 9.3, p < 0.01). In conclusion, replacement of grass silage with brewers grains improved the performance of beef cows and increased calf birth and weaning BW. Further analysis indicated that the superior performance of cows offered the BG diet was most likely due to increases in protein supply which may have improved both energy and protein supply to the foetus.

Methane emissions from two breeds of beef cows offered diets containing barley straw with either grass silage or brewers' grains.

Increasing the concentration of dietary lipid is a promising strategy for reducing methane (CH4) emissions from ruminants. This study investigated the effect of replacing grass silage with brewers' grains on CH4 emissions of pregnant, non-lactating beef cows of two breeds. The experiment was a two×two factorial design comprising two breeds (LIMx, crossbred Limousin; and LUI, purebred Luing) and two diets consisting of (g/kg diet dry matter (DM)) barley straw (687) and grass silage (301, GS), or barley straw (763) and brewers' grains (226, BG), which were offered ad libitum. Replacing GS with BG increased the acid-hydrolysed ether extract concentration from 21 to 37 g/kg diet DM. Cows (n=48) were group-housed in equal numbers of each breed across two pens and each diet was allocated to one pen. Before measurements of CH4, individual dry matter intake (DMI), weekly BW and weekly body condition score were measured for a minimum of 3 weeks, following a 4-week period to acclimatise to the diets. CH4 emissions were subsequently measured on one occasion from each cow using individual respiration chambers. Due to occasional equipment failures, CH4 measurements were run over 9 weeks giving 10 observations for each breed×treatment combination (total n=40). There were no differences between diets for daily DMI measured in the chambers (9.92 v. 9.86 kg/day for BG and GS, respectively; P>0.05). Cows offered the BG diet produced less daily CH4 than GS-fed cows (131 v. 156 g/day: P0.05). However, when expressed as a proportion of metabolic BW (BW0.75), LUI cows had greater DMI than LIMx cows (84.5 v. 75.7 g DMI/kg BW0.75, P<0.05) and produced more CH4 per kg BW0.75 than LIMx cows (1.30 v. 1.05 g CH4/kg BW0.75; P<0.01). Molar proportions of acetate were higher (P<0.001) and propionate and butyrate lower (P<0.01) in rumen fluid samples from BG-fed compared with GS-fed cows. This study demonstrated that replacing GS with BG in barley straw-based diets can effectively reduce CH4 emissions from beef cows, with no suppression of DMI.

Effectiveness of nitrate addition and increased oil content as methane mitigation strategies for beef cattle fed two contrasting basal diets.

The objectives of this study were to investigate the effects of (1) the addition of nitrate and (2) an increase in dietary oil on methane (CH4) and hydrogen (H2) emissions from 2 breeds (cross-bred Charolais and purebred Luing) of finishing beef cattle receiving 2 contrasting basal diets consisting (grams per kilogram DM) of 500:500 (Mixed) and 80:920 (Concentrate) forage to concentrate ratios. Within each basal diet there were 3 treatments: (i) control treatments (mixed-CTL and concentrate-CTL) contained rapeseed meal as the protein source, which was replaced with either (ii) calcium nitrate (mixed-NIT and concentrate-NIT) supplying 21.5 g nitrate/kg DM, or (iii) rapeseed cake (mixed-RSC and concentrate-RSC) to increase dietary oil from 27 (CTL) to 53 g/kg DM (RSC). Following adaption to diets, CH4 and H2 emissions were measured on 1 occasion from each of the 76 steers over a 13-wk period. Dry matter intakes tended (P = 0.051) to be greater for the concentrate diet than the mixed diet; however, when expressed as grams DMI per kilogram BW, there was no difference between diets (P = 0.41). Dry matter intakes for NIT or RSC did not differ from CTL. Steers fed a concentrate diet produced less CH4 and H2 than those fed a mixed diet (P < 0.001). Molar proportions of acetate (P < 0.001) and butyrate (P < 0.01) were lower and propionate (P < 0.001) and valerate (P < 0.05) higher in the rumen fluid from steers fed the concentrate diet. For the mixed diet, CH4 yield (grams per kilogram DMI) was decreased by 17% when nitrate was added (P < 0.01), while H2 yield increased by 160% (P < 0.001). The addition of RSC to the mixed diet decreased CH4 yield by 7.5% (P = 0.18). However, for the concentrate diet neither addition of nitrate (P = 0.65) nor increasing dietary oil content (P = 0.46) decreased CH4 yield compared to concentrate-CTL. Molar proportions of acetate were higher (P < 0.001) and those of propionate lower (P < 0.01) in rumen fluid from NIT treatments compared to respective CTL treatments. Overall, reductions in CH4 emissions from adding nitrate or increasing the oil content of the mixed diet were similar to those expected from previous reports. However, the lack of an effect of these mitigation strategies when used with high concentrate diets has not been previously reported. This study shows that the effect of CH4 mitigation strategies is basal diet-dependent.

Evaluation of the laser methane detector to estimate methane emissions from ewes and steers.

The laser methane detector (LMD) has been proposed as a method to characterize enteric methane (CH4) emissions from animals in a natural environment. To validate LMD use, its CH4 outputs (LMD-CH4), were compared against CH4 measured with respiration chambers (chamber-CH4). The LMD was used to measure CH4 concentration (µL/L) in the exhaled air of 24 lactating ewes and 72 finishing steers. In ewes, LMD was used on 1 d for each ewe, for 2-min periods at 5 hourly observation periods (P1 to P5, respectively) after feeding. In steers fed either low- or high-concentrate diets, LMD was used once daily for a 4-min period for 3 d. The week after LMD-CH4 measurement, ewes or steers entered respiration chambers to quantify daily CH4 output (g/d). The LMD outputs consisted of periodic events of high CH4 concentrations superimposed on a background of oscillating lower CH4 concentrations. The high CH4 events were attributed to eructation and the lower background CH4 to respiration. After fitting a double normal distribution to the data set, a threshold of 99% of probability of the lower distribution was used to separate respiration from eructation events. The correlation between mean LMD-CH4 and chamber-CH4 was not high, and only improved correlations were observed after data were separated in 2 levels. In ewes, a model with LMD and DMI (adjusted R(2) = 0.92) improved the relationship between DMI and chamber-CH4 alone (adjusted R(2) = 0.79) and between LMD and chamber-CH4 alone (adjusted R(2) = 0.86). In both experiments, chamber-CH4 was best explained by models with length of eructation events (time) and maximum values of CH4 concentration during respiration events (µL/L; P < 0.01). Correlation between methods differed between observation periods, indicating the best results of the LMD were observed from 3 to 5 h after feeding. Given the short time and ease of use of LMD, there is potential for its commercial application and field-based studies. Although good indicators of quantity of CH4 were obtained with respiration and eructation CH4, the method needed to separate the data into high and low levels of CH4 was not simple to apply in practice. Further assessment of the LMD should be performed in relation to animal feeding behavior and physiology to validate assumptions of eructation and respiration levels, and other sources of variation should be tested (i.e., micrometeorology) to better investigate its potential application for CH4 testing in outdoor conditions.