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Objective: Portable laser methane detectors (LMDs) may be an economical means of estimating CH4 emissions from ruminants. We validated an LMD-based approach and then used that approach to evaluate CH4 emissions from indigenous dairy cows in a dryland area of Ethiopia. Methods: First, we validated our LMD-based approach in Simmental crossbred beef cattle (n = 2) housed in respiration chambers and fed either a high- or low-concentrate diet. From the results of the validation, we constructed an estimation equation to determine CH4 emissions from LMD CH4 concentrations. Next, we used our validated LMD approach to examine CH4 emissions in Fogera dairy cows grazed for 8 h/d (GG, n = 4), fed indoors on natural-grassland hay (CG1, n = 4), or fed indoors on Napier-grass (Pennisetum purpureum) hay (CG2, n = 4). All the cows were supplemented with concentrate feed. Results: The exhaled CH4 concentrations measured by LMD were linearly correlated with the CH4 emissions determined by infrared-absorption-based gas analyzer (r2 = 0.55). The estimation equation used to determine CH4 emissions (y, mg/min) from LMD CH4 concentrations (x, ppm m) was y = 0.4259x+38.61. Daily CH4 emissions of Fogera cows estimated by using the equation did not differ among the three groups; however, a numerically greater milk yield was obtained from the CG2 cows than from the GG cows, suggesting that Napiergrass hay might be better than natural-grassland hay for indoor feeding. The CG1 cows had higher CH4 emissions per feed intake than the other groups, without significant increases in milk yield and body-weight gain, suggesting that natural-grassland hay cannot be recommended for indoor-fed cows. Conclusion: These findings demonstrate the potential of using LMDs to valuate feeding regimens rapidly and economically for dairy cows in areas under financial constraint, while taking CH4 emissions into consideration.

The objective of the present study was to investigate factors related to variation in feed efficiency (FE) among cows. Data included 841 cow/period observations from 31 energy metabolism studies assembled across 3 research stations. The cows were categorized into low-, medium-, and high-FE groups according to residual feed intake (RFI), residual energy-corrected milk (RECM), and feed conversion efficiency (FCE). Mixed model regression was conducted to identify differences among the efficiency groups in animal and energy metabolism traits. Partial regression coefficients of both RFI and RECM agreed with published energy requirements more closely than cofficients derived from production experiments. Within RFI groups, efficient (Low-RFI) cows ate less, had a higher digestibility, produced less methane (CH4) and heat, and had a higher efficiency of metabolizable energy (ME) utilization for milk production. High-RECM (most efficient) cows produced 6.0 kg/d more of energy-corrected milk (ECM) than their Low-RECM (least efficient) contemporaries at the same feed intake. They had a higher digestibility, produced less CH4 and heat, and had a higher efficiency of ME utilization for milk production. The contributions of improved digestibility, reduced CH4, and reduced urinary energy losses to increased ME intake at the same feed intake were 84, 12, and 4%, respectively. For both RFI and RECM analysis, increased metabolizability contributed to approximately 35% improved FE, with the remaining 65% attributed to the greater efficiency of utilization of ME. The analysis within RECM groups suggested that the difference in ME utilization was mainly due to the higher maintenance requirement of Low-RECM cows compared with Medium- and High-RECM cows, whereas the difference between Medium- and High-RECM cows resulted mainly from the higher efficiency of ME utilization for milk production in High-RECM cows. The main difference within FCE (ECM/DMI) categories was a greater (8.2 kg/d) ECM yield at the expense of mobilization in High-FCE cows compared with Low-FCE cows. Methane intensity (CH4/ECM) was lower for efficient cows than for inefficient cows. The results indicated that RFI and RECM are different traits. We concluded that there is considerable variation in FE among cows that is not related to dilution of maintenance requirement or nutrient partitioning. Improving FE is a sustainable approach to reduce CH4 production per unit of product, and at the same time improve the economics of milk production.

Accurately predicting nitrogen (N) outputs in manure, urine and faeces from beef cattle is crucial for the realistic assessment of the environmental footprint of beef production and the development of sustainable N mitigation strategies. This study aimed to develop and validate equations for N outputs in manure, urine and faeces for animals under diets with contrasting crude protein (CP) concentrations. Measurements from individual animals (n = 570), including bodyweight, feed intake and chemical composition, and N outputs were (i) analysed as a merged database and also (ii) split into three sub-sets, according to diet CP concentration (low CP, 84–143 g/kg dry matter, n = 190; medium CP, 144–162 g/kg dry matter, n = 190; high CP, 163–217 g/kg dry matter, n = 190). Prediction equations were developed and validated using residual maximum likelihood analysis and mean prediction error (MPE), respectively. In low CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.244, 0.594 and 0.263, respectively; diet CP-specific equations improved accuracy in certain occasions, by 4.9% and 18.3% for manure N output and faeces N output respectively, while a reduction by 5.7% in the prediction accuracy for urinary N output was noticed. In medium CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.227, 0.391 and 0.394, respectively; diet CP-specific equations improved accuracy by 13.2%, 41.2% and 16.8% respectively. In high CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.120, 0.154 and 0.144, respectively; diet CP-specific equations improved accuracy in certain occasions by 5.8%, 9.1% and 6.3% respectively. This study demonstrated that for improved prediction accuracy of N outputs in manure, urine and faeces from beef cattle, the use of dietary CP concentration is essential while dietary starch, fat, and metabolisable energy concentrations can be used to further improve accuracy. In beef cattle fed low CP concentration diets, using diet CP-specific equations improves prediction accuracy when feed intake or dietary CP concentration are not known. However, in beef cattle fed medium or high CP concentration diets, using equations that have been developed from animals fed similar CP concentration diets, substantially improves the prediction accuracy of N outputs in manure, urine and faeces in most cases.

Selenium (Se) deficiency is a widespread and seasonally chronic phenomenon observed in Tibetan sheep (Ovis aries) traditionally grazed on the Qinghai–Tibet Plateau (QTP). Effects of the dietary addition of Se-enriched yeast (SeY) on the bacterial community in sheep rumen and rumen fermentation were evaluated with the aim of gaining a better understanding of the rumen prokaryotic community. Twenty-four yearling Tibetan rams [initial average body weight (BW) of 31.0 ± 0.64 kg] were randomly divided into four treatment groups, namely, control (CK), low Se (L), medium Se (M), and high Se (H). Each group comprised six rams and was fed a basic diet of fresh forage cut from the alpine meadow, to which SeY was added at prescribed dose rates. This feed trial was conducted for over 35 days. On the final day, rumen fluid was collected using a transesophageal sampler for analyzing rumen pH, NH3-N content, volatile fatty acid (VFA) level, and the rumen microbial community. Our analyses showed that NH3-N, total VFA, and propionate concentrations in the M group were significantly higher than in the other groups (P < 0.05). Both the principal coordinates analysis (PCoA) and the analysis of similarities revealed that the bacterial population structure of rumen differed among the four groups. The predominant rumen bacterial phyla were found to be Bacteroidetes and Firmicutes, and the three dominant genera in all the samples across all treatments were Christensenellaceae R7 group, Rikenellaceae RC9 gut group, and Prevotella 1. The relative abundances of Prevotella 1, Rikenellaceae RC9 gut group, Ruminococcus 2, Lachnospiraceae XPB1014 group, Carnobacterium, and Hafnia-Obesumbacterium were found to differ significantly among the four treatment groups (P < 0.05). Moreover, Tax4fun metagenome estimation revealed that gene functions and metabolic pathways associated with carbohydrate and other amino acids were overexpressed in the rumen microbiota of SeY-supplemented sheep. To conclude, SeY significantly affects the abundance of rumen bacteria and ultimately affects the rumen microbial fermentation.

Qinghai-Tibetan Plateau is a main area of selenium deficiency in the world, and local grazing livestock are affected by selenium deficiency. We conducted a metabolism trial of Tibetan sheep included adding selenium yeast at 0, 0.2, 0.4 and 0.8 mg Se/kg dry matter (DM) to the native pasture of Maqu county, Qinghai-Tibetan Plateau in 2017, to evaluated the impact of different levels of selenium addition on the selenium balance, nitrogen metabolism, nutrient digestibility and antioxidant status of native forage in Tibetan sheep. Our results showed that selenium balance, absorption and retention of Tibetan sheep were linearly affected by different selenium levels. However, the percentage of selenium retention is the highest when the selenium addition level is 0.4 mg/kg DM. The relationships between selenium addition levels and malondialdehyde (MDA), superoxide dismutase (SOD) and total antioxidant capacity (T-AOC) were quadratic. Based on the prediction equations, the most suitable selenium addition levels for MDA, SOD and T-AOC were 0.39, 0.36 and 0.47 mg/kg DM, respectively. Dietary supplementation of selenium could increase dry matter intake (DMI) and improve food conversion ratio (FCR), and the relationships between selenium addition level and DMI and FCR are both quadratic. Selenium addition could also increase apparent digestibility of NDF, ADF and EE with quadratic effects (P

Twelve Hu sheep × thin‐tail Han crossbred dry ewes with an average body weight of 32.6 ± 0.68 kg and an age of 3 years were arranged in a 3 × 3 Latin square design, with each experimental period of 24 d to evaluate the effect of substituting alfalfa hay in a portion of concentrate on nutrient intake, digestibility, N utilisation efficiency and methane emissions. The ratios of corn straw to alfalfa to concentrate for 3 diet treatments were 60:0:40, 60:15:25 and 60:30:10, respectively. Intake and digestibility were measured for each of the ewes, which were housed in individual metabolism crates for 6 d after an adaptation period of 14 d, and the feed was offered at 1.2 MEm to ensure approximately 10% orts. Methane emissions were determined in a respiration chamber for 2 consecutive d. An increase in the levels of alfalfa as a substitute for concentrate significantly increased the roughage, NSC and ADF intake and faecal N output as a proportion of N intake and manure N output. Furthermore, this increase in alfalfa input levels decreased DE, ME and N intake; nutrient digestibility; DE/GE, ME/GE and CH4 emissions per day; CH4 output expressed as a portion of the DM, OM and GE intake; and urinary N and ammonia N output, especially between extreme treatments. Alfalfa input levels had no effect on the BW, DM and GE intake; the EB or EB/GE intake; and the retained N. This study indicated that increasing alfalfa input as a substitute for concentrate could significantly decrease the digestibility, CH4 emissions and urinary N and NH4 +‐N outputs; and shift the N excretion from urine to faeces; and could sustain a similar DM intake.

Measurements of energy balance (EB) require the use of respiration chambers, which are quite expensive and laborious. The GreenFeed (GF) system (C-Lock Inc.) has been developed to offer a less expensive, user friendly alternative. In this study, we used the GF system to estimate the EB of cows in early lactation and compared it with EB predicted from energy requirements for dairy cows in the Finnish feeding standards. We also evaluated the association between milk fatty acids and the GF estimated EB. The cows were fed the same grass silage but supplemented with either cereal grain or fibrous by-product concentrate. Cows were followed from 1 to 18 wk of lactation, and measurements of energy metabolism variables were taken. Data were subjected to ANOVA using the mixed model procedure of SAS (SAS Institute Inc.). The repeatability estimates of the gaseous exchanges from the GF were moderate to high, presenting an opportunity to use it for indirect calorimetry in EB estimates. Energy metabolism variables were not different between cows fed different concentrates. However, cows fed the grain concentrate produced more methane (24.0 MJ/d or 62.9 kJ/MJ of gross energy) from increased digestibility than cows fed the by-product concentrate (21.3 MJ/d or 56.5 kJ/MJ of gross energy). Nitrogen metabolism was also not different between the diets. Milk long-chain fatty acids displayed an inverse time course with EB and de novo fatty acids. There was good concordance (0.85) between EB predicted using energy requirements derived from the Finnish feed table and EB estimated by the GF system. In conclusion, the GF can accurately estimate EB in early-lactating dairy cows. However, more data are needed to further validate the system for a wide range of dietary conditions.

Due to its extremely harsh environment, including high altitude, hypoxia, long cold season, and strong ultraviolet radiation in the Qinghai&ndash, Tibet Plateau (QTP), herbage species and nutritional value of the pasture may differ considerably from elsewhere across the world. The aim of the present study was to develop biologically relevant equations for estimating the metabolizable energy (ME) value of fresh native herbages in the QTP using digestibility variables and chemical concentrations in the herbage offered to Tibetan sheep at the maintenance level. A total of 11 digestibility trials (6 sheep/trial) were performed in different grazing seasons from 2011 to 2016. The herbage was harvested daily in the morning and offered to sheep at the maintenance feeding level. Thirty-seven equations were developed for the prediction of herbage digestible energy (DE) and ME energy values. The mean prediction error for ME was the lowest when using herbage gross energy digestibility as a sole predictor. When using other digestibility variables (e.g., dry matter and organic matter) as primary predictors, addition of herbage nutrient concentration reduced the difference between predicted and actual values. When DE was used as the primary explanatory variable, mean prediction error was reduced with the addition of ash, nitrogen (N), diethyl ether extract (EE), neutral detergent fiber (NDF), and acid detergent fiber (ADF) concentrations. The internal validation of the present equations showed lower prediction errors when compared with those of existing equations for prediction of DE and ME concentrations in the herbage. Equations developed in the current study may thus allow for an improved and accurate prediction of metabolizable energy concentrations of herbage in practice, which is critical for the development of sustainable grazing systems in the QTP.

A meta-analysis based on an individual-cow data set was conducted to investigate between-cow variations in the components and measurements of feed efficiency (FE) and to explore the associations among these components. Data were taken from 31 chamber studies, consisting of a total of 841 cow/period observations. The experimental diets were based on grass or corn silages, fresh grass, or a mixture of fresh grass and straw, with cereal grains or by-products as energy supplements, and soybean or canola meal as protein supplements. The average forage-to-concentrate ratio across all diets on a dry matter basis was 56:44. Variance component and repeatability estimates of FE measurements and components were determined using diet, period, and cow within experiment as random effects in mixed procedures of SAS (SAS Institute Inc., Cary, NC). The between-cow coefficient of variation (CV) in gross energy intake (GE; CV = 0.10) and milk energy (El) output as a proportion of GE (El/GE; CV = 0.084) were the largest among all component traits. Similarly, the highest repeatability estimates (≥0.50) were observed for these 2 components. However, the between-cow CV in digestibility (DE/GE), metabolizability [metabolizable energy (ME)/GE], methane yield (CH4E/GE), proportional urinary energy output (UE/GE), and heat production (HP/GE), as well as the efficiency of ME use for lactation (kl), were rather small. The least repeatable component of FE was UE/GE. For FE measurements, the between-cow CV in residual energy-corrected milk (RECM) was larger than for residual feed intake (RFI), suggesting a greater possibility for genetic gain in RECM than in RFI. A high DE/GE was associated with increased CH4E/GE (r = 0.24), HP/GE (r = 0.12), ME/GE (r = 0. 91), energy balance as a proportion of GE (EB/GE; r = 0.35), and kl (r = 0.10). However, no correlation between DE/GE and GE intake or UE/GE was observed. Increased proportional milk energy adjusted to zero energy balance (El(0)/GE) was associated with increases in DE/GE, ME/GE, EB/GE, and kl but decreases in UE/GE, CH4E/GE, and HP/GE, with no effect on GE intake. In conclusion, several mechanisms are involved in the observed differences in FE among dairy cows, and reducing CH4E yield (CH4E/GE) may inadvertently result in reduced GE digestibility. However, the selection of dairy cows with improved energy utilization efficiencies offers an effective approach to lower enteric CH4 emissions.

The objective was to determine whether modern Holstein-origin dairy cows, when managed within grassland-based systems, partitioned more feed nitrogen (N) into milk and excreted less in manure, in comparison to an earlier population of Holstein-origin dairy cows. Data used were collated from total diet digestibility studies undertaken in Northern Ireland from 1990 to 2002 (old dataset, n = 538) and from 2005 to 2019 (new dataset, n = 476), respectively. An analysis of variance indicated that cows in the new dataset partitioned a significantly higher proportion of consumed N into milk and excreted a lower proportion in urine and total manure, compared to cows in the old dataset. A second analysis using the linear regression revealed that in comparison to the old dataset, the new dataset had a lower slope in the relationship between N intake and N excretion in urine or total manure, while a higher slope in the relationship between N intake and milk N output. A third analysis used the combined data from both datasets to examine if there was a relationship between experimental year and N utilization efficiency. Across the period from 1990 to 2019, urine N/N intake and manure N/N intake significantly decreased, while milk N/N intake increased. These results indicate that modern Holstein-origin dairy cows utilize consumed N more efficiently than earlier populations. Thus, N excretion is likely to be overestimated if models developed from the old data are used to predict N excretion for modern dairy herds. Therefore, the final part of analysis involved using the new dataset to develop prediction models for N excretion based on N intake and farm level data (milk yield, live weight and dietary N concentration). These updated models can be used to estimate N excretion from modern Holstein-origin dairy cows within grassland-based dairy systems.

Three ruminally fistulated Xuanhan steers weighting 312.5 (±23.85) kg were used to determine the kinetics of ruminal degradation of nutrients using in situ nylon bag technique, and a modified 3-step in vitro procedure was adopted to estimate intestinal digestibility of 16-h rumen undegradable protein (RUP) of maize cob (MC), distillers grains (DG), spent mushroom substrate (SMS), starch residue of sweet potato (SRSP), citrus pulp (CPP), and rice straw (RS). Samples were incubated for 0, 2, 6, 16, 24, 36, 48 and 72 h. Additional samples were incubated for 16 h in the rumen, and the residues from these bags were transferred to the nitrogen-free polyester bags for determination of intestinal digestibility in vitro. The highest DM disappearance at 6-h incubation was in SRSP (P 0.07) on CP disappearance between DG and MC at all the time points except for 16 and 24 h. NDF and ADF disappearance for SRSP was significantly higher (P < 0.01) than other roughages at all the time points except for ADF at 72 h. The lowest NDF and ADF disappearance was in DG at all the time points (P < 0.01) except 2 and 6 h. The effective degradability (ED) of DM was the highest in CPP (P < 0.01) and the lowest in MC and RS (P < 0.01). The highest and lowest ED of CP was in DG and in RS (P < 0.01), respectively. The ED of NDF was the highest in SRSP (P < 0.01), followed by CPP and RS, and the lowest in DG (P < 0.01). The ED of ADF was the highest in SRSP and CPP (P < 0.05), and the lowest in DG (P < 0.01). For MC, DG SMS, SRSP, CPP, and RS, the intestinal digestibility of RUP was 95.28%, 37.23%, 38.72%, 48.06%, 54.49%, and 37.88%, respectively, and the content of intestinal digestible crude protein (IDCP) was 23.65, 83.63, 35.63, 15.03, 25.60, and 12.03 g/kg, respectively. Distillers grain was considered to be of good quality for the greatest content of IDCP. Although not readily degraded in rumen, CP in MC may be digested well in small intestine.

Objective This study evaluated the effects of different levels of protein concentrate supplementation on the growth performance of yak calves, and correlated the growth rate to changes occurring in the plasma- amino acids, -insulin profile, and signaling activity of mammalian target of rapamycin (mTOR) cascade to characterize the mechanism through which the protein synthesis can be improved in early weaned yaks. Methods For this study, 48 early (3 months old) weaned yak calves were selected, and assigned into four dietary treatments according to randomized complete block design. The four blocks were balanced for body weight and sex. The yaks were either grazed on natural pasture (control diet) in a single herd or the grazing yaks was supplemented with one of the three protein rich supplements containing low (17%; LP), medium (19%; MP), or high (21%; HP) levels of crude proteins for a period of 30 days. Results Results showed that the average daily gain of calves increased (0.14 vs 0.23–0.26 kg; p0.05) when the grazing calves were supplemented with protein concentrates. Compared to control diet, the insulin level of calves increased (p

Although the effect of animal and diet factors on enteric methane (CH4) emissions from confined cattle has been extensively examined, less data is available regarding CH4 emissions from grazing young cattle. A study was undertaken to evaluate the effect of the physiological state of Holstein-Friesian heifers on their enteric CH4 emissions while grazing a perennial ryegrass sward. Two experiments were conducted: Experiment 1 ran from May 2011 for 11 weeks and Experiment 2 ran from August 2011 for 10 weeks. In each experiment, Holstein-Friesian heifers were divided into three treatment groups (12 animals/group) consisting of calves, yearling heifers, and in-calf heifers (average ages: 8.5, 14.5, and 20.5 months, respectively). Methane emissions were estimated for each animal in the final week of each experiment using the sulfur hexafluoride tracer technique. Dry matter (DM) intake was estimated using the calculated metabolizable energy (ME) requirement divided by the ME concentration in the grazed grass. As expected, live weight increased with increasing animal age (P < 0.001); however, there was no difference in live weight gain among the three groups in Experiment 1, although in Experiment 2, this variable decreased with increasing animal age (P < 0.001). In Experiment 1, yearling heifers had the highest CH4 emissions (g·d−1) and in-calf heifers produced more than calves (P < 0.001). When expressed as CH4 emissions per unit of live weight, DM intake, and gross energy (GE) intake, yearling heifers had higher emission rates than calves and in-calf heifers (P < 0.001). However, the effects on CH4 emissions were different in Experiment 2, in which CH4 emissions (g·d−1) increased linearly with increasing animal age (P < 0.001), although the difference between yearling and in-calf heifers was not significant. The CH4/live weight ratio was lower in in-calf heifers than in the other two groups (P < 0.001), while CH4 energy output as a proportion of GE intake was lower in calves than in yearling and in-calf heifers (P < 0.05). All data were then pooled and used to develop prediction equations for CH4 emissions. All relationships are significant (P < 0.001), with R2 values ranging from 0.630 to 0.682. These models indicate that CH4 emissions could be increased by 0.252 g·d−1 with an increase of 1 kg live weight or by 14.9 g·d−1 with an increase of 1 kg·d−1 of DM intake; or, the CH4 energy output could be increased by 0.046 MJ·d−1 with an increase of 1 MJ·d−1 of GE intake. These results provide an alternative approach for estimating CH4 emissions from grazing dairy heifers when actual CH4 emission data are not available.

Pig and poultry production in China had experienced considerable changes from 1960 to 2010. The present study aimed to evaluate the effects of these changes on greenhouse gas emission inventories (expressed as CO2 equivalent) from these two sectors. The inventories included methane emissions from enteric fermentation, methane and nitrous oxide production from manure management. The greenhouse gas emissions from these sources in 2010 in pig sector were 17, 62 and 21%, respectively, and that in poultry sector (including chicken, duck, goose and others) were 1, 18 and 81%, respectively. Total CO2 equivalent increased from 1960 to 2010 in both pig (11 582 to 55 564 Gg yr−1) and poultry (1 497 to 14 873 Gg yr−1) sectors. Within poultry sector, emissions from chicken, duck, goose and others accounted for 74, 15, 11 and 0.01% in 2010, respectively. However, during the last 50 years, these emissions continuously reduced when related to production of 1 kg of pork (8.01 to 1.14 kg kg−1), poultry meat (1.19 to 0.37 kg kg−1) and egg (0.47 to 0.33 kg kg−1), which is mainly associated with the continuous improvement in production efficiency in all management systems. These results provide benchmark information for Chinese authorities to develop appropriate policies and mitigation strategies to reduce greenhouse gas emissions from pig and poultry sectors.

Partners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF6) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the &lsquo, true&rsquo, value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available.

The objective of the present study was to evaluate the effect of feeding levels on enteric methane (CH4) emissions and nitrogen (N) and energy utilisation efficiencies of ewe sheep offered fresh ryegrass. Twenty-four dry ewes (16 mo old and 47.6 ± 5.1 kg body weight) were used in a factorial design study, with 2 genotypes (12 ewes/genotype, Belclare vs. Lleyn) × 3 feeding levels (maintenance level vs. ad libitum vs. intermediate level (targeted level = 1.5 maintenance)). All sheep were offered fresh grass harvested daily in the morning from the second regrowth sward. All animals were housed in individual pens for 19 d and then in individual respiration chambers for further 5 d with feed intake, faeces and urine outputs and CH4 emissions measured during the final 4 d. There was no significant interaction between genotype and feeding level on any variable evaluated, except for CH4 emissions with which the interaction was significant (P

Nitrogen excretion from sheep production systems is an important source of nitrate, ammonia, and nitrous oxide responsible for groundwater pollution and global warming. The present study aimed to identify key parameters influencing N utilization efficiency and develop prediction equations for manure N, feces N, and urine N outputs in sheep. Data used were collected from 82 sheep offered fresh perennial ryegrass () as the sole diet in 6 metabolism experiments (data from non-grass-only diets were not used). Sheep were from breeds of Highlander, Texel, Scottish Blackface, and Swaledale at the age of 5 to 18 mo and weighing from 24.5 to 62.7 kg. Herbage was harvested daily from 6 swards of contrasting harvest dates (May to December), offering wide variation in feed value to cover the range that would be offered in most practical farm situations. Before the commencement of each study, the experimental sward was harvested at a residual height of 4 cm and allowed to grow for 2 to 4 wk to target an average pregrazing sward height in a range of 8 to 15 cm depending on the time of year. Sheep were housed in individual pens for 14 d and then transferred to individual metabolism crates for 4 d with feed intake and feces and urine outputs measured. Data were analyzed using the linear mixed model procedure to develop prediction equations for feces N, urine N, and manure N outputs using N intake, herbage chemical composition, and digestibility with effects of sex, breed, and experimental periods removed. Nitrogen intake was the best single predictor for N output in feces, urine, and manure, and the value for prediction of manure N output was greater than those for feces N and urine N (0.86 vs. 0.70 and 0.77, respectively; < 0.001). Animal BW and herbage DM, ether extract, NDF, ADF, water soluble carbohydrate, and DE concentrations and N digestibility were also used to predict N outputs because N intake may not be available in commercial practice. The prediction equations for N utilization efficiency indicated that increasing feeding level and ME concentration and reducing N concentration could improve N utilization efficiency and shift N excretion into feces rather than urine ( < 0.001). The equations developed in the current study provide an approach for sheep producers to quantify N excretion against production and, consequently, to develop their own mitigation strategies to reduce the environmental impact of sheep production systems.

Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

This study aimed to determine the net energy requirement of Holstein cows in mid-lactation under heat stress. Twenty-five multiparous Holstein cows were randomly allocated to five groups corresponding to five isonitrogenous total mixed rations, with net energy for lactation (NEL ) content of 6.15 (NE-6.15), 6.36 (NE-6.36), 6.64 (NE-6.64), 6.95 (NE-6.95), 7.36 (NE-7.36) MJ/kg of dry matter (DM), respectively. Throughout the experimental period the average temperature humidity index at 07.00, 14.00 and 22.00 hours was 72.1, 88.7, and 77.6, respectively. DM intake decreased significantly with the elevated dietary NEL concentration. Fat corrected milk increased quadratically, and milk fat content and milk energy (MJ/kg) reached the greatest in the NE-6.95 group with increasing dietary NEL content. Strong correlations were found between dietary NEL content and: (i) DM intake; (ii) NEL intake; (iii) milk energy (El ); (iv) El /metabolizable energy intake (MEI); (v) El /NEL intake, as well as between NEL intake and fat corrected milk yield (FCM). The suitable net energy required for dairy cows producing 1 kg FCM ranged from 5.01 to 5.03 MJ, was concluded from the above-stated regressions. Correlation between heat production (HP) and MEI could be expressed as: Log (HP) = -0.4304 + 0.2963*MEI (n = 15, R2 = 0.99, Root Mean Square Error (RMSE) = 0.18). Fasting HP was 0.3712 MJ/kg0.75 when extrapolating MEI to zero.

Seventeen non-lactating dairy-bred suckler cows (LF; Limousin×Holstein-Friesian) and 17 non-lactating beef composite breed suckler cows (ST; Stabiliser) were used to study enteric methane emissions and energy and nitrogen (N) utilization from grass silage diets. Cows were housed in cubicle accommodation for 17 days, and then moved to individual tie-stalls for an 8-day digestibility balance including a 2-day adaption followed by immediate transfer to an indirect, open-circuit, respiration calorimeters for 3 days with gaseous exchange recorded over the last two of these days. Grass silage was offered ad libitum once daily at 0900 h throughout the study. There were no significant differences (P>0.05) between the genotypes for energy intakes, energy outputs or energy use efficiency, or for methane emission rates (methane emissions per unit of dry matter intake or energy intake), or for N metabolism characteristics (N intake or N output in faeces or urine). Accordingly, the data for both cow genotypes were pooled and used to develop relationships between inputs and outputs. Regression of energy retention against ME intake (r 2=0.52; P

Simple Summary Over the past decades, European Union countries have been under increasing pressure to reduce nitrogen pollution resulting from agricultural activities and ensure compliance with environmental legislations aimed at reducing the amount of nitrogen emitted into the atmosphere. Among the various forms of nitrogen losses into the atmosphere from agriculture, losses associated with farmed livestock (particularly dairy cows) are top priority. The nitrogen losses associated with livestock originate mostly from the excreta (feces and urine), with dietary protein content as a major driver. Despite the concern about dietary protein, the feeding of diets with excess protein relative to requirements (protein overfeeding) is evident on many commercial dairy farms in Europe, with the belief that it enhances milk production and in part for purposes of providing a margin of safety. Abstract The effect of dietary crude protein (CP) level on intake, digestibility, milk production, and nitrogen (N) use efficiency was studied. Twenty-four Holstein-Friesian cows (17 multiparous and seven primiparous) were grouped by parity, days in milk, milk yield, and live weight into six blocks of four, and randomly assigned to four total mixed ration (TMR) treatments, containing 141, 151, 177, or 210 g CP/kg dry matter (DM), over 28 day experimental periods. Apparent total-tract DM and fiber digestibilities and milk fat composition were similar across treatments. Milk protein and urea-N compositions, and urinary and manure N excretion increased linearly, while milk N efficiency (MNE) decreased linearly with increasing CP. DM intake was highest with the 177 diet, while CP intake increased linearly with increasing CP, peaking at 200 g/kg DM. Milk yield increased with CP intake for the three lower CP levels, peaking at 176 g CP/kg DM. The further increase in CP level from 177 to 210 g/kg DM did not result in improved milk yield, but resulted in decreased milk N secretion and increased urinary N excretion. In summary, milk protein composition increased linearly with increasing CP, accompanied by a linear decrease in MNE, resulting in a bell-shaped relationship between milk yield and dietary CP level.

The world's annual output of rabbits is over 1.2 billion, therefore this sector is also one of the sources of greenhouse gases in livestock production. One hundred-twenty New Zealand rabbits were allocated into four treatments, five replicates in each treatment and six rabbits in each replicate to examine the effect of grinding alfalfa hay to different sizes on growth performance, methane production and cecal archaeal populations. The particle sizes of the alfalfa meal in the four treatment diets were 2500, 1000, 100 and 10 μm, while the other ingredients were ground through a 2.5 mm sieve. The average daily gain (ADG) and average daily feed intake (ADFI) increased (P

Recent developments suggest the use of other gases such as carbon dioxide (CO2) to estimate methane (CH4) emissions from livestock, yet little information is available on the relationship between these two gases for a wide range of animals. A large respiration calorimeter dataset with dairy cattle (n = 987 from 30 experiments) was used to investigate relationships between CH4 and CO2 production and oxygen (O2) consumption and to assess whether the predictive power of these relationships could be improved by taking into account some dietary variables, including forage proportion, fibre and metabolisable energy concentrations. The animals were of various physiological states (young n = 60, dry cows n = 116 and lactating cows n = 811) and breeds (Holstein-Friesian cows n = 876, Jersey × Holstein-Friesian n = 47, Norwegian n = 50 and Norwegian × Holstein-Friesian n = 14). The animals were offered forage as a sole diet or a mixture of forage and concentrate (forage proportion ranging from 10 to 100%, dry matter basis). Data were analysed using a series of mixed models. There was a strong positive linear relationship between CH4 and CO2, and observations within an experiment were very predictable (adjusted R2 = 0.93). There was no effect of breed on the relationship between CH4 and CO2. Using O2 instead of CO2 to predict CH4 production also provided a very good fit to the observed empirical data, but the relationship was weaker (adjusted R2 = 0.86). The inclusion of dietary variables to the observed CO2 emissions, in particular forage proportion and fibre concentration, provided a marginal improvement to the prediction of CH4. The observed variability in the CH4:CO2 ratio could only marginally be explained by animal physiological state (lactating vs. dry cows and young cattle) and dietary variables, and thus most likely reflected individual animal differences. The CH4:CO2 ratio can therefore be particularly useful to identify low CH4 producing cows. These findings indicate that CO2 production data can be used to accurately predict CH4 emissions to generate large scale data for management and genetic evaluations for the dairy industry. Keywords: Dairy cattle, Methane, Carbon dioxide, Oxygen, Prediction

Although concentrate supplements in ruminant diets have been recognised as an effective enteric methane mitigation strategy, very few studies have examined the effects of concentrate supplementation on enteric methane emissions under grazing conditions. Twenty four multiparous Holstein Friesian cows were used in a crossover design study to investigate the effects of two concentrate feeding levels across two periods on enteric methane emissions and milk production of grazing dairy cows. Each period had a duration of four weeks (three weeks for diet adaptation and one week for measurements) and no interval in between them. Dietary treatments consisted of two concentrate feeding levels per cow (1 vs. 5 kg; as-fed basis) offered daily in equal meals during milking. Enteric methane emissions from cows grazing perennial ryegrass pasture were measured during the final week of each period using the sulphur hexafluoride tracer technique. Milk yield and liveweight were determined daily during each methane measurement period, whereas milk composition and body condition score (BCS) were determined weekly. Daily herbage intake by individual cows during methane measurement weeks was estimated using an energy requirement model and animal records and diet composition. In period 1, cows receiving 5 kg concentrate supplement were estimated to reduce herbage intake by 1.8 kg DM/d compared to cows receiving 1 kg of concentrate, whereas in period 2 cows receiving the 5 kg concentrate supplementation were estimated to reduce herbage intake by 4.4 kg DM/d, compared to cows receiving 1 kg of concentrate. In both periods, milk yield increased with increasing concentrate level, with an average milk response to concentrate supplementation of 0.68 kg milk DM/kg concentrate DM over the two periods. Concentrate feeding level had no effect on milk fat, protein or total solids contents. In period 2, lactose content increased in cows offered 5 kg/d concentrate. Increasing concentrate feeding level increased liveweight and BCS in period 1, but not in period 2. Feeding 5 kg of concentrate supplement increased enteric methane emission by 34 g/d in period 1 (323 vs. 357 g/d) and 41 g/d in period 2 (349 vs. 390 g/d) compared to 1 kg of concentrate supplement. However, enteric methane emission per unit of estimated feed intake (dry matter or gross energy) or milk output (gross or energy corrected) was not affected by level of concentrate supplementation. It was concluded that under generous grazing conditions (high allowance of good quality herbage) a moderate increase in concentrate supplementation resulted in a simultaneous increase in milk yield and enteric methane emission, so that enteric methane emission per unit of milk yield was unaffected. Thus, a moderate level of concentrate supplementation of dairy cows grazing pastures of high digestibility would not be an effective enteric methane mitigation strategy.

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Methane (CH4) emissions from ruminant animals contribute significantly to the global greenhouse gas budget. The accurate quantification of this source of emissions requires detailed animal and feed information, however there is little information available on systematic measurement of CH4 emissions from young cattle at various ages. The present study was designed to address this gap of knowledge. Data used were derived from a study with 20 Autumn-calved Holstein cattle (10 steers and 10 heifers) with CH4 emissions measured at age of 6, 12, 18 and 22 months, respectively. The cattle were offered a typical diet used on UK commercial farms containing a single grass silage mixed with concentrates. In each period, the cattle were housed as a single group in cubicle accommodation for the first 20 days, individually in metabolism units for the next 3 days, and then in indirect open-circuit respiration calorimeter chambers for the final 5 days with feed intake, feces and urine outputs and gaseous exchange measured during the final 4 days. Within each period, gender had no effect (P > 0.05) on nutrient digestibility and any CH4 emission variable in terms of total CH4 emission, CH4 emission as a proportion of live weight or feed intake, or CH4 energy output as a proportion of energy intake. The data from the two groups were therefore pooled to develop prediction equations for daily CH4 emissions (g day−1). A range of prediction equations have been developed using BW (body weight), feed intake and energy intake. The present data were also used to calculate accumulated CH4 emissions for the two genders. Although gender had no effect (P > 0.05) on the results, the accumulated CH4 emissions increased with the growth of cattle (mean 36.2 and 64.3 kg year−1 for both genders in years 1 and 2, respectively). A number of prediction equations were developed for total CH4 emission factors (kg year−1) for heifers and steers during the first and second year of the rearing. These factors were very strongly related to (r2 = 0.75–0.95) to BW recorded at the beginning, middle and the end of 1 or 2 year of age. These data can add novel information to the scientific literature and can be used to improve national inventories of CH4 emissions and to develop appropriate mitigation strategies for young Holstein cattle of high genetic merit herds.

Twenty 5-mo-old Holstein cattle (10 steers and 10 heifers) were selected from a dairy herd for a 28 d study of enteric methane emissions and energy utilization. The cattle were offered a completely mixed diet with grass silage and concentrates (0.45 and 0.55, DM basis, respectively). They were housed as a single group in cubicle accommodation for the fi rst 20 d, transferred to metabolism units for 3 d, and subsequently housed in indirect open-circuit respiration calorimeter chambers for next 5 d with measurements of feed intake, feces and urine outputs, and gaseous exchange. There were no signifi cant differences (P > 0.05) between the 2 groups in terms of animal performance (feed intake, BW, or BW gain), energy metabolism (energy intake, energy outputs, or energy use effi ciency), or methane emission rates (total methane emissions expressed on feed intake or energy intake basis). Therefore, the data from the 2 groups were pooled to develop a range of relationships between inputs and outputs. The regression of energy balance or heat production against ME intake (r 2 = 0.85; P < 0.001) indicated a NE m of 0.57MJ/kg BW 0.75 , which is greater than reported for adult dairy cattle. The methane energy output was found to be 0.068 of GE intake when the intercept was omitted from the linear equation (r 2 = 0.73; P < 0.001), which is greater than the commonly accepted value (0.065) for adult cattle used for development of methane emission inventories for dairy and beef production systems. These data can add useful information, as there is little information available on measurements of maintenance energy requirement or methane emissions in young stock (6 mo old) of the current high-yielding dairy cattle. The use of these data can potentially improve the accuracy of prediction of energy requirement and methane emissions for dairy and beef production systems in these dietary conditions.

As one of the potent greenhouse gases, methane emission from ruminants has been intensively studied over the past decades. Various regression-based models have been applied to examine factors affecting enteric methane emission. Based on Bayesian networks, this paper proposes an alternative network-based approach to model the relationship among factors affecting enteric methane emissions from milking cows. It was evaluated on the dataset consisting of 934 milking dairy cows collected at Agri-Food and Biosciences Institute, Northern Ireland. The preliminary results demonstrated that the proposed model has a great potential to capture the complex relationship among factors and establish causal influence among predictors. To the best of our knowledge, this is the first study to use Bayesian networks to model causal influence among factors associated with enteric methane emission from milking cows.

Although many studies have investigated mitigation strategies for methane (CH 4 ) output from dairy cows fed a wide variety of diets, research on the effects of concentrate crude protein (CP) content on CH 4 emissions from dairy cows offered fresh grass is limited. The present study was designed to evaluate the effects of cow genotype and concentrate CP level on nutrient digestibility, energy utilization, and CH 4 emissions in dairy cows offered fresh-grass diets. Twelve multiparous lactating dairy cows (6 Holstein and 6 Holstein × Swedish Red) were blocked into 3 groups for each breed and assigned to a low-, medium-, or high-CP concentrate diet [14.1, 16.1, and 18.1% CP on a dry matter (DM) basis, respectively], in a 3-period changeover study (25d per period). Total diets contained (DM basis) 32.8% concentrates and 67.2% perennial ryegrass, which was harvested daily. All measurements were undertaken during the final 6d of each period: digestibility measurements for 6d and calorimetric measurements in respiration chambers for 3d. Feed intake and milk production data were reported in a previous paper. We observed no significant interaction between concentrate CP level and cow genotype on any parameter. Concentrate CP level had no significant effect on any energy utilization parameter, except for urinary energy output, which was positively related to concentrate CP level. Similarly, concentrate CP content had no effect on CH 4 emission (g/d), CH 4 per kg feed intake, or nutrient digestibility. Cross breeding of Holstein cows significantly reduced gross energy, digestible energy, and metabolizable energy intake, heat production, and milk energy output. However, cow genotype had no significant effect on energy utilization efficiency or CH 4 parameters. Furthermore, the present study yielded a value for gross energy lost as CH 4 (5.6%) on fresh grass-based diets that was lower than the widely accepted value of 6.5%. The present findings indicate that reducing concentrate CP content from 18.1 to 14.1% may not be a successful way of alleviating CH 4 emissions from lactating dairy cows offered good-quality fresh grass, but grazing cows could be offered a low-CP concentrate without compromising energy utilization efficiency. Further research is needed to investigate whether larger differences in dietary CP content may yield positive results.

Twenty castrated Boer crossbred goats were used in the present study with two treatments to examine the effect of dietary replacement of ordinary rice with red yeast rice on nutrient utilization, enteric methane emission and ruminal archaea structure and composition. Two treatment diets contained (DM basis) 70.0% of forage, 21.8% of concentrates and 8.2% of either ordinary rice (control) or red yeast rice (RYR). Nutrient utilization was measured and enteric methane emissions were determined in respiration chambers. Results showed that RYR had significantly lower digestibility of N and organic matter compared to control group. However, feeding red yeast rice did not affect N retention as g/d or a proportion of N intake, and reduced heat production as MJ/d or as a proportion of metabolizable energy intake, thus leading to a higher proportion of metabolizable energy intake to be retained in body tissue. RYR also had significantly lower methane emissions either as g/d, or as a proportion of feed intake. Although feeding red yeast rice had no negative effect on any rumen fermentation variables, it decreased serum contents of total cholesterol, triglycerides, HDL-cholesterol and LDL-cholesterol. In the present study, 75616 archaeal sequences were generated and clustered into 2364 Operational Taxonomic Units. At the genus level, the predominant archaea in the rumen of goats was Methanobrevibacter, which was significantly inhibited with the supplementation of red yeast rice. In conclusion, red yeast rice is a potential feed ingredient for mitigation of enteric methane emissions of goats. However, caution should be taken when it is used because it may inhibit the digestibility of some nutrients. Further studies are required to evaluate its potential with different diets and animal species, as well as its effects on animal health and food safety.

Simple Summary Enteric methane emissions produced by ruminant livestock has gained global interest due to methane being a potent greenhouse gas and ruminants being a significant source of emissions. In the absence of measurements, prediction models can facilitate the estimation of enteric methane emissions from ruminant livestock and aid investigation of mitigation options. This study developed a practical method using feed analysis information for predicting enteric methane emissions from sheep, beef cattle and dairy cows fed diets encompassing a wide range of nutrient concentrations. Abstract Enteric methane (CH4) is a by-product from fermentation of feed consumed by ruminants, which represents a nutritional loss and is also considered a contributor to climate change. The aim of this research was to use individual animal data from 17 published experiments that included sheep (n = 288), beef cattle (n = 71) and dairy cows (n = 284) to develop an empirical model to describe enteric CH4 emissions from both cattle and sheep, and then evaluate the model alongside equations from the literature. Data were obtained from studies in the United Kingdom (UK) and Australia, which measured enteric CH4 emissions from individual animals in calorimeters. Animals were either fed solely forage or a mixed ration of forage with a compound feed. The feed intake of sheep was restricted to a maintenance amount of 875 g of DM per day (maintenance level), whereas beef cattle and dairy cows were fed to meet their metabolizable energy (ME) requirement (i.e., production level). A linear mixed model approach was used to develop a multiple linear regression model to predict an individual animal’s CH4 yield (g CH4/kg dry matter intake) from the composition of its diet. The diet components that had significant effects on CH4 yield were digestible organic matter (DOMD), ether extract (EE) (both g/kg DM) and feeding level above maintenance intake: CH4 (g/kg DM intake) = 0.046 (±0.001) × DOMD − 0.113 (±0.023) × EE − 2.47 (±0.29) × (feeding level − 1), with concordance correlation coefficient (CCC) = 0.655 and RMSPE = 14.0%. The predictive ability of the model developed was as reliable as other models assessed from the literature. These components can be used to predict effects of diet composition on enteric CH4 yield from sheep, beef and dairy cattle from feed analysis information.

The objectives of the present study were to compare the sulfur hexafluoride (SF₆) and respiration chamber techniques for measuring methane (CH₄) emissions from dairy cows and to determine the proportion of CH₄ that is released through the rectum. Data used were derived from 20 early lactation dairy cows in a 2 × 2 factorial design study for 4 periods with 6 wk/period. The 4 treatment diets consisted of grass silage and 2 levels of concentrate (30 and 60% dry matter basis), with or without yeast supplement. At the end of each period, CH₄ emissions were measured simultaneously using the SF₆ and respiration chamber techniques when cows were housed in chambers. The SF₆ technique was also used when cows were housed in digestibility units (barn location) before and after respiratory chamber measurements (chamber location). The simultaneous measurements in chamber location revealed that CH₄ emission estimates by the SF₆ technique were similar to those by the respiration chamber technique in the first 3 periods, although the SF₆ estimates were significantly higher in period 4. The regression of all data from the 4 periods demonstrated a linear relationship between the SF₆ and respiration chamber measurements for total CH₄ emissions (g/d, R² = 0.69) and for CH₄ emissions per unit of milk yield (g/kg, R² = 0.88), and a quadratic relationship for CH₄ emissions per unit of dry matter intake (g/kg, R² = 0.64). The CH₄ emissions from the rectum were calculated as the difference between CH₄ estimates from the SF₆ technique when cows were housed in respiratory chambers and barn locations, which was 3% of the total CH₄ emissions from the mouth, nostrils, and rectum. The SF₆ estimates in the chamber location accounted for all sources of emissions, whereas those in the barn location, like that in grazing conditions, did not include CH₄ emission from the rectum. Therefore, the SF₆ measurements for grazing cattle should be adjusted for CH₄ emissions from the rectum (3% of total). We conclude that the SF₆ technique is reasonably accurate for estimating CH₄ emissions.

Beef cattle production is valuable to food security, contributing meat of high nutritional value. However, beef cattle are rather inefficient in utilising dietary nitrogen (N), thus excreting substantial amounts of N in their urine and faeces and imposing an environmental burden. The aim of this study was to evaluate the main dietary factors affecting N use efficiency (NUE) in beef cattle and develop prediction models for N excretion in manure, faeces and urine. This knowledge is essential for the development and evaluation of cost-effective N mitigation strategies. A database of 289 treatment means was constructed from 69 published studies and 1194 animals. Data included diet contents of N, dry matter (DM), organic matter (OM), neutral-detergent fibre (NDF), acid-detergent fibre (ADF), ether extract, starch, ash, gross energy (GE), metabolisable energy (ME), and outputs of N in manure, in urine or in faeces. Regression equations to predict N outputs in manure (MNO), urine (UNO) and faeces (FNO), as well as various NUE indicators, were developed using residual maximum likelihood analysis. Evaluation of new and existing models was performed using the mean prediction error (MPE) to describe prediction accuracy. Manure, urine and faeces N outputs were predicted with improved accuracy (MPE from 0.557 to 0.162; from 0.764 to 0.208; and from 0.458 to 0.177, respectively) when DM or OM digestibilities, and/or diet contents of N, NDF, ADF, Starch, OM, GE, ME, and/or forage proportion in the diet were added as predictors in different equations already containing either DM intake, N intake or body weight as primary predictor. New and existing models displayed an under-prediction of N outputs at the highest range of actual N outputs (when MNO > 207 g/d, UNO > 109 g/d). However, some of the new equations had improved overall accuracy (best MPE for MNO, UNO and FNO being 0.162, 0.208 and 0.177, respectively) and, when DM digestibility, and contents of N, NDF, Starch and ME were added as predictors in different equations, the extent of this under-prediction was also reduced (occurring when MNO > 208 g/d, UNO > 132 g/d). The regression models for NUE, demonstrated that diets which are more digestible and contain less N and fibre and more ME, may reduce N excretions, but mitigation strategies will also need to account for the potential effect on animal productivity and health.