Methane yield values (MY; g methane/kg dry-matter intake) in beef cattle reported in the global literature (expanded MitiGate database of methane-mitigation studies) were analysed by cluster and meta-analyses. The Ward and k means cluster analyses included accounting for the categorical effects of methane measurement method, cattle breed type, country or region of study, age and sex of cattle, and proportion of grain in the diet and the standardised continuous variables of number of animals, liveweight and MY. After removal of data from outlier studies, meta-analyses were conducted on subsets of data to produce prediction equations for MY. Removing outliers with absolute studentised residual values of >1, followed by meta-analysis of data accounting for categorical effects, is recommended as a method for predicting MY. The large differences among some countries in MY values were significant but difficult to interpret. On the basis of the datasets available, a single, global MY or percentage of gross energy in feed converted to methane (Ym) value is not appropriate for use in Intergovernmental Panel on Climate Change (IPCC) greenhouse accounting methods around the world. Therefore, ideally country-specific MY values should be used in each country’s accounts (i.e. an IPCC Tier 2 or 3 approach) from data generated within that country.

A bioeconomic, stochastic spreadsheet model, that included calculation of the net present value of the additional value of all future descendants resulting from increased selection intensity, was developed to study the profitability of using sexed semen in a high input-high output dairy herd. Three management strategies were modeled: (1) only heifers inseminated with sex-sorted semen and cows inseminated with unsorted semen; (2) both heifers and cows inseminated with sex-sorted semen; and (3) a reference scenario, in which all breeding females were inseminated with unsorted semen. A Monte Carlo simulation (@risk software, Palisade Corp., Ithaca, NY) was run to study the sensitivity of net profit and sexed semen advantage to key input parameters. Most input parameters were given truncated normal distributions, whereas the maximum numbers of inseminations in heifers and cows were given discrete distribution functions. The calculated intensity of selection accounted for the different numbers of dairy females born for each of the 100,000 iterations. Using sexed semen (X-sorted, female) was shown to be profitable, with insemination of both heifers and cows being most profitable. The returns on assets were higher when only heifers were inseminated with sexed semen (8.54% ± 2.94; ±SD) or all females were inseminated with sexed semen (8.85% ± 2.93) than when all females were inseminated with unsexed semen (8.38% ± 2.95). The range in net profit was most sensitive to the assumed distributions of milk protein price (€/kg), milk fat price (€/kg), cow pregnancy rate, fertilizer price (€/t), and concentrate price (€/t) when unsorted semen was used. When only heifers or both heifers and cows were inseminated with sex-sorted semen, the range in net profit was most sensitive to the same distributions, with fertilizer price and cow pregnancy rate in reverse order of sensitivity. However, the range in sex-sorted semen advantage (in net profit) when only heifers were inseminated with sex-sorted semen was most sensitive to the assumed distributions of cow pregnancy rate, sex-sorted semen pregnancy rate as a percent of unsorted semen rates, standard deviation of index, additional cost of sex-sorted semen (€/dose), dairy bull calf price (€/head), and dairy heifer calf price (€/head). When both heifers and cows were inseminated, the order of importance of the last 2 inputs was reversed. This study highlights the relatively high effect of pregnancy rate and the genetic value of dairy bulls in determining the level of financial advantage from using sex-sorted semen in a dairy herd.

The sensitivity of pasture intake estimates obtained from using 13C as a marker to differences in assumed diet composition and 13C diet-faecal discrimination was studied. Angus stud heifers grazed a silver grass, perennial ryegrass, bent grass and yorkshire fog pasture. The individual heifers were fed controlled and monitored daily amounts of maize and faecal samples were taken and analysed to estimate dry matter intake (DMI) and DMI/liveweight (LW). Daily methane production was also measured. Monte Carlo simulations using a uniform distribution of diet composition and an extreme value distribution for the 13C diet-faecal discrimination found that the DMI/LW ratio was twice as sensitive to assumed diet composition (and hence pasture 13C) than to the diet-faeces discrimination factor. DMI estimates would be useful for ranking animals on DMI intake alone as the rank correlations for DMI estimated using different input assumptions were high. A genetic algorithm approach was helpful as a means of determining the optimum diet selection or plant proportions to use for each animal and the diet-faecal discrimination to use when uncertainty exists as to their true values, which may often be the case. Some animals had non-credible DMI/LW values when using standard calculation methods. There are no definitive goals or constraints to use but careful choice of the range of individual DMI/LW values set as a hard constraint enabled credible DMI/LW values for all animals to be obtained when using a genetic algorithm approach.

Reducing daily methane production (DMP) via selection for lower estimated daily (pasture) feed intake (DFI) has the potential to be more cost effective than direct selection for DMP. Daily feed intake has a high heritability and high genetic correlation to DMP and has a potential lower cost of measurement. This study's main aim was to determine for a breeding nucleus the optimal proportion of randomly selected young male and female cattle in which to estimate DFI. This optimum proportion was determined by modeling the measurement costs and response to selection of Angus cattle on a (standard industry) Angus breeding index (ABI) augmented with DFI and DMP in a combined breeding objective (BO), but without DMP being measured. For the assumed herd structure and considering a 20 yr planning horizon, the highest net present value (NPV) occurred when 64% of males and no females were measured for DFI. The highest breakeven DFI test cost (A$41.51/head) and highest returns on investment (ROI) occurred when 36% of males and no females had DFI estimates. Higher ROI were achieved when all males had DFI estimates before any females had DFI estimates. There was a diminishing increase in rate of genetic gain when moving from 36% to 64% of males with DFI estimates, thus ROI decreased from 29.7% to 23.1%. When 36% of males had DFI estimates (and no females), herd DMP genetic gain was slightly positive as the DMP reduction per generation from male selection (-0.086) was more than offset by the DMP increase per generation from female selection (+0.110). The selection response for DMP only became negative when at least 40% of males had DFI estimates. Having 64% of males with DFI estimates resulted in a predicted genetic decrease in DMP (-0.018 kgCOe/head per yr), compared to an increase of 0.052 kgCOe/head per yr when no animals had DFI estimates. The optimum proportion of males with DFI estimates (36 to 64%) depends on the breeders attitude toward ROI and the value of genetic change for DMP. Sensitivity analysis showed that the economic value (EV), heritability and genetic variance of DFI had a higher impact on the NPV and ROI outcomes than parameters related to ABI and DMP, so future work should focus on obtaining robust estimates for DFI parameters. Higher EV for feed intake and DMP would result in higher percentages of animals being profitably measured for DFI, leading to larger reductions in DMP.

Calculation of the maintenance metabolisable energy (ME) requirements should include the additional ME required to counteract heat loss in cold conditions if ambient temperatures occur below the lower critical temperature (LCT) of sheep. This correction requires an estimate of the fleece length of sheep during the year. Equations are presented to estimate the monthly fleece length of Romneys assuming different patterns of seasonality of wool growth, month of shearing and total fleece length. These lengths are discussed in the context of predicted levels of fleece insulation, which in turn influence sheep energy requirements under New Zealand climatic conditions. Predicted fleece insulation varied from 1 to 8 degrees C m(2) d/MJ in different months. The additional maintenance ME requirements of ewes are predicted for each month following shearing for different months of shearing. An example calculation resulted in an estimated additional 30% of ME being required when the average daily ambient temperature in the month of shearing was 5 degrees C below the LCT.

It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (VE ) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep.

As daily methane production (DMP; g CH4/day) is strongly correlated with dry matter intake (DMI), the breeding of cattle that require less feed to achieve a desired rate of average daily gain (ADG) by selection for a low residual feed intake (RFI) can be expected to reduce DMP and also emission intensity (EI; g CH4/kg ADG). An experiment was conducted to compare DMP and EI of Angus cattle genetically divergent for RFI and 400-day weight (400dWT). In a 6-week grazing study, 64 yearling-age cattle (30 steers, 34 heifers) were grazed on temperate pastures, with heifers and steers grazing separate paddocks. Liveweight (LW) was monitored weekly and DMP of individual cattle was measured by a GreenFeed emission monitoring unit in each paddock. Thirty-nine of the possible 64 animals had emission data recorded for 15 or more days, and only data for these animals were analysed. For these cattle, regression against their mid-parent estimated breeding value (EBV) for post-weaning RFI (RFI-EBV) showed that a lower RFI-EBV was associated with higher LW at the start of experiment. Predicted dry matter intake (pDMI), predicted DMP (pDMP) and measured DMP (mDMP) were all negatively correlated with RFI-EBV (P < 0.05), whereas ADG, EI, predicted CH4 yield (pMY; g CH4/kg DMI) were not correlated with RFI-EBV (P > 0.1). Daily CH4 production was positively correlated with animal LW and ADG (P < 0.05). The associations between ADG and its dependent traits EI and pMY and predicted feed conversion ratio (kg pDMI/kg ADG) were strongly negative (r = –0.82, –0.57 and –0.85, P < 0.001) implying that faster daily growth by cattle was accompanied by lower EI, MY and feed conversion ratio. These results show that cattle genetically divergent for RFI do not necessarily differ in ADG, EI or pMY on pasture and that, if heavier, cattle with lower RFI-EBV can actually have higher DMP while grazing moderate quality pastures.

Australia is the largest supplier of high-quality wool in the world. The environmental burden of sheep production must be shared between wool and meat. We examine different methods to handle these co-products and focus on proportional protein content as a basis for allocation, that is, protein mass allocation (PMA). This is the first comprehensive investigation applying PMA for calculating greenhouse gas (GHG) emissions for Australian sheep production, evaluating the variation in PMA across a large number of farms and locations over 20 years.

Greenhouse gas emissions (GHG) from broadacre sheep farms constitute ~16% of Australia’s total livestock emissions. To study the diversity of Australian sheep farming enterprises a combination of modelling packages was used to calculate GHG emissions from three sheep enterprises (Merino ewe production for wool and meat, Merino-cross ewes with an emphasis on lamb production, and Merino wethers for fine wool production) at 28 sites across eight climate zones in southern Australia. GHG emissions per ha, per dry sheep equivalents and emissions intensity (EI) per tonne of clean wool or liveweight sold under different pasture management or animal breeding options (that had been previously determined in interviews with farmers) were assessed relative to baseline farms in each zone (‘Nil’ option). Increasing soil phosphorus fertility or sowing 40% of the farm area to lucerne resulted in the smallest and largest changes in GHG/dry sheep equivalents, respectively (–66%, 113%), though both of these options had little influence on EI for either clean wool or liveweight sold. Breeding ewes with greater body size or genotypes with higher fleece weight resulted in 11% and 9% reductions, respectively, in EI. Enterprises specialising in lamb production (crossbred ewes) had 89% lower EI than enterprises specialising in fine wool production (Merino wethers). Thus, sheep producers aiming for lower EI could focus more on liveweight turnoff than wool production. Emissions intensities were typically highest in cool temperate regions with high rainfall and lowest in semiarid and arid regions with low aboveground net primary productivity. Overall, animal breeding options reduced EI more than feedbase interventions.

No Australian wool price hedonic studies have separated auction data into different end product-processing groups (PPR) on the basis of all fibre attributes that affect the suitability of wool sale lots for PPR. This study was conducted to assess: (1) whether including information about PPR groupings is more useful in understanding price than clustering by broad fibre diameter (FD) categories, and (2) if the ‘noise’ of macroeconomic effects on price can be reduced by using a clean price relative to the market indicator (RelPrice) formula or a log RelPrice formula compared with log price or clean price. Hedonic models using data derived from 369 918 Australian auction sale lots in 2010–2011 were estimated for these four dependent price variables. Linear FD models predicted less of price’s variance than quadratic or exponential models. Segmenting wool sale lots into 10 PPR before wool price analyses was found to increase the proportion of price variance explained and thus be worthwhile. The change in price with a change in FD, staple length and staple strength differs significantly between PPR. Calculating RelPrice or log RelPrice appears a better price parameter than clean price or log price. Comparing the RelPrice and clean price models, the mean absolute percentage errors were 6.3% and 16.2%, respectively. The differences in price sensitivity to FD, staple length and staple strength across PPR implies a complex set of price-setting mechanisms for wool as different users place different values on these wool properties. These price-setting mechanisms need to be incorporated in hedonic models for agricultural products that possess this characteristic. The wool price premiums can be used to estimate relative economic values when constructing sheep breeding selection indexes and can help determine the most profitable wool clip preparation strategies.

In 2014, the Australian Government implemented the Emissions Reduction Fund to offer incentives for businesses to reduce greenhouse gas (GHG) emissions by following approved methods. Beef cattle businesses in northern Australia can participate by applying the ‘reducing GHG emissions by feeding nitrates to beef cattle’ methodology and the ‘beef cattle herd management’ methods. The nitrate (NO3) method requires that each baseline area must demonstrate a history of urea use. Projects earn Australian carbon credit units (ACCU) for reducing enteric methane emissions by substituting NO3 for urea at the same amount of fed nitrogen. NO3 must be fed in the form of a lick block because most operations do not have labour or equipment to manage daily supplementation. NO3 concentrations, after a 2-week adaptation period, must not exceed 50 g NO3/adult animal equivalent per day or 7 g NO3/kg dry matter intake per day to reduce the risk of NO3 toxicity. There is also a ‘beef cattle herd management’ method, approved in 2015, that covers activities that improve the herd emission intensity (emissions per unit of product sold) through change in the diet or management. The present study was conducted to compare the required ACCU or supplement prices for a 2% return on capital when feeding a low or high supplement concentration to breeding stock of either (1) urea, (2) three different forms of NO3 or (3) cottonseed meal (CSM), at N concentrations equivalent to 25 or 50 g urea/animal equivalent, to fasten steer entry to a feedlot (backgrounding), in a typical breeder herd on the coastal speargrass land types in central Queensland. Monte Carlo simulations were run using the software @risk, with probability functions used for (1) urea, NO3 and CSM prices, (2) GHG mitigation, (3) livestock prices and (4) carbon price. Increasing the weight of steers at a set turnoff month by feeding CSM was found to be the most cost-effective option, with or without including the offset income. The required ACCU prices for a 2% return on capital were an order of magnitude higher than were indicative carbon prices in 2015 for the three forms of NO3. The likely costs of participating in ERF projects would reduce the return on capital for all mitigation options.

This study compared measuring the stable isotope, 13C, in the faeces with measuring alkanes and alcohols, using a system for automatically dispensing supplement, to determine the proportions of C3 (temperate legumes and grasses) and C4 (maize grain supplement) dietary components. These proportions enable the estimation of the total pasture intake of individual animals if the intake of one dietary component (the supplement) is known. Pasture intakes of 32 Hereford yearling bulls that had been fed known amounts of maize grain mixed with paraffin wax, while grazing C3 pasture, were estimated. Intake estimates from 13C results corrected for both diet discrimination and organic matter digestibility, using a C4 supplement, were more credible than solely correcting for diet discrimination. 13C values were similar for the C3 plants in the study so the assumed mixture of C3 plants in the diet had minimal impact on the ranking of animals for total intake. Intakes determined by alkane and alcohol concentrations in the faeces did not appear to be more credible than intakes determined by 13C due to the analytical variability that can occur with measuring alkanes and alcohols. The rank correlations of the bulls’ feed efficiencies (estimated as liveweight gain over 76 days / estimated intake) determined by different intake marker methods and assumed pasture mixes in the diet were all 0.95–0.96. When total pasture intake estimates are required, rather than intakes of all dietary components, the most cost- effective method studied was to use 13C as a marker and a C4 plant, such as maize grain, as a supplement.

The marketing strategies of agricultural producers have become increasingly focussed on the sale of differentiated products to intermediary buyers rather than the sale of homogeneous commodities directly to retailers. The wool value chain in Australia fits the description of differentiated products being sold by wool producers to agribusiness firms that are intermediaries in the chain. The attributes of wool that are the source of this differentiation are used by firms to add value to their operations, reflected in higher retail prices paid for wool products.We measure the overall efficiency with which wool is converted into value across different processing routes and end products in the Australian wool value chain and decompose it into its technical, scale and mix efficiency components. We find that wool price changes significantly with a change in fibre diameter, staple length and staple strength and employ a flexible functional form to capture the relations between these wool attributes and lot value. Results show that considerable scope exists to increase the value of most sale lots, and indicate that the overall efficiency in extracting value is lower for wool supplied to processes that produce high-value wool garments. We then ascertain that various factors related to wool production and product characteristics significantly influence the level of technical efficiency.The mix of the three key attributes in wool lots was found not to be a major factor influencing overall efficiency whereas scale efficiency scores (which we measure as returns to wool attributes) were clearly much lower than those for technical and mix efficiency scores, a function of strongly increasing returns to wool lots as the levels of attributes increase. We test propositions about the skewness of distributions of efficiency scores in translating wool attributes into value. Most distributions of overall efficiency scores are positively skewed for production processes paying high prices for wool, and differences in overall efficiency were observed across selling centres. Prima facie, the results provide a strong case for wool producers to move to higher value levels of wool attributes by producing finer, stronger and longer wool fibres -especially the former. But such a strategy may not be an optimal one for producers to follow because the investments they make to implement such a strategy may entail high costs and take a long period to fruition that would lead to a heavy discounting of future benefits. A full benefit-cost analysis would be needed of any investments to raise the levels of wool attributes and otherwise improve wool quality at the farm level.

This review explores research and development in wool metrology to date. In doing so, it highlights the research work undertaken by three organisations, in particular, to the development of wool and textile metrology research covering all of the important physical properties of wool. Three key wool research centres at the beginning of the twenty-first century were CSIRO's Division of Textile and Fibre Technology at Belmont near Geelong, Victoria, the School of Fibre Science and Technology, University of NSW at Kensington, NSW in Australia, and the Wool Research Organisation of New Zealand Inc. at Lincoln near Christchurch, New Zealand. Due to funding pressures between 1997 and 2007, these centres either ceased to operate or were absorbed into larger, non-wool-focused organisations. The substantial contribution to the world's wool metrology literature made by their staff and graduates, over the period when the three organisations had around 300–500 staff involved in wool-related research activities, is recognised. The review analyses the research undertaken on wool properties to identify gaps that might be exploited through the application of new or novel use of technologies by the next generation of wool metrologists. The analysis indicates that although the main fibre/fleece characteristics which currently affect the pricing and trading of Merino wool are able to be readily and accurately measured, there remains considerable work to be done in linking wool measurements to the prediction of performance both in processing and in the final product.

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

Nitrate may serve as a non-protein nitrogen (NPN) source in ruminant diets while also reducing enteric methane emissions. A study was undertaken to quantify methane emissions of cattle when nitrate replaced urea in a high concentrate diet. Twenty Angus steers were allocated to two treatment groups and acclimated to one of two iso-energetic and iso-nitrogenous finisher rations (containing NPN as urea or as calcium nitrate), with all individual feeding events recorded. A single methane measurement device (C-lock Inc., Rapid City, SD, USA) was exchanged weekly between treatments (2 × 1-week periods per treatment) to provide estimations of daily methane production (DMP; g CH4/day). A 17% reduction in estimated DMP (P = 0.071) resulted from nitrate feeding, attributed to both a tendency for reduced dry matter intake (DMI; P = 0.088) and H2 capture by the consumed nitrate. NO3-fed cattle consumed a larger number of meals (14.69 vs 7.39 meals/day; P < 0.05) of smaller size (0.770 vs 1.820 kg/meal) each day, so the average interval between a feeding event and methane measurement was less in NO3-fed cattle (3.44 vs 5.15 h; P < 0.05). This difference could potentially have skewed the estimated DMP and contributed to the tendency (P = 0.06) for NO3-fed cattle to have a higher methane yield (g CH4/kg DMI) than urea-fed cattle. This study found short-term methane emission measurements made over 2 weeks (per treatment group) were adequate to show dietary nitrate tended to reduce emission and change the feeding pattern of feedlot cattle. Changes in feeding frequency may have confounded the ability of short-term methane measurements to provide data suitable for accurately estimating methane per unit feed intake.

In 2011, the Australian government introduced a voluntary carbon offset scheme called the Carbon Farming Initiative (CFI), which provides an incentive mechanism for farmers to earn carbon credits by lowering greenhouse gas (GHG) emissions or sequestering carbon. In Australia, there is now interest in developing offset methods for controlled feeding of lipids or nitrates to livestock, where individual animal daily supplement intake is controlled and recorded. Carbon offset methodologies are being drafted that require the impact of voluntary versus controlled feeding of these supplements on methane mitigation to be modelled. This paper presents modelling results and tests the hypothesis that controlled feeding would result in higher mitigation than would voluntary, uncontrolled feeding. Controlled feeding with all animals either having the same average supplement intake (C1) or having a controlled maximum intake (C2) resulted in higher herd- or flock-scale methane mitigation than did voluntary, uncontrolled feeding (VFI) from the same total amount of supplement fed. The percentage reductions in methane from C1 and C2 feeding patterns versus VFI were relatively greater at higher levels of both lipid and nitrate supplementation. The modelled effect of higher methane production from VFI than from C1 or C2 was larger for nitrate than for lipid supplements. Controlled feeding can be expected to result in a far more even and consistent intake per animal than from VFI. Any supplementation aimed at reducing enteric methane is therefore more effectively administered through some form of controlled feeding. Also, due to the potential toxicity from excess intake of nitrate, controlled supplementation is far less likely to lead to excessive intake and toxicity.