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

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

Review: More effective linkages between science and policy are needed to minimize the negative environmental impacts of livestock production.

Animals form an integral part of our planetary ecosystem but balance is critical to effective ecosystem functioning as demand for livestock products has increased, greater numbers of domesticated livestock have created an imbalance and hence had a negative impact on a number of ecosystem services which means that life as we know it will become unsustainable. Policies and technology advances have helped to manage the impact but more needs to be done. The aim of this paper is to highlight ways in which better knowledge of animal science, and other disciplines, can both harness technology and inform policy to work towards a sustainable balance between livestock and the environment. Effective policies require simple, quantifiable indicators against which to set targets and monitor progress. Indicators are clear for water pollution, but more complex for biodiversity. Hence, more progress has been made with the former. It is not yet possible to measure the impacts of changes in livestock management on greenhouse gas emissions per se at a farm level and progress has been slower, although new technologies are emerging. With respect to land use, the simple indicator of area has been used, but total area is oversimplistic. Our analysis of land suitability and use highlights a relatively overlooked role of livestock in acting as a 'buffer' to use by-products and grains which do not meet the standards for processing by industry during years of inclement weather, which in the past has provided an 'insurance policy' for farmers. Since extreme weather events are increasing in frequency with climate change, this role for livestock may be more important in future. The conclusions of the review with respect to strengthening the links between research and policy are i) to encourage animal scientists to identify the relevant environmental indicators, work with the cutting edge experts developing technologies to measure these cost-effectively and across a range of relevant livestock systems and ii) to work with the feed industry to optimize diets not just in terms of least cost financially but also least 'cost' in terms of global carbon flux and engage in dialogue with the food industry and policy makers on regulations for grain quality.

Genome-Wide Association Studies for Methane Production in Dairy Cattle.

Genomic selection has been proposed for the mitigation of methane (CH4) emissions by cattle because there is considerable variability in CH4 emissions between individuals fed on the same diet. The genome-wide association study (GWAS) represents an important tool for the detection of candidate genes, haplotypes or single nucleotide polymorphisms (SNP) markers related to characteristics of economic interest. The present study included information for 280 cows in three dairy production systems in Mexico: 1) Dual Purpose (n = 100), 2) Specialized Tropical Dairy (n = 76), 3) Familiar Production System (n = 104). Concentrations of CH4 in a breath of individual cows at the time of milking (MEIm) were estimated through a system of infrared sensors. After quality control analyses, 21,958 SNPs were included. Associations of markers were made using a linear regression model, corrected with principal component analyses. In total, 46 SNPs were identified as significant for CH4 production. Several SNPs associated with CH4 production were found at regions previously described for quantitative trait loci of composition characteristics of meat, milk fatty acids and characteristics related to feed intake. It was concluded that the SNPs identified could be used in genomic selection programs in developing countries and combined with other datasets for global selection.

Short communication: Heritability of methane production and genetic correlations with milk yield and body weight in Holstein-Friesian dairy cows.

Greenhouse gases originating from the dairy sector, including methane (CH4), contribute to global warming. A possible strategy to reduce CH4 production is to use genetic selection. This requires genetic parameters for CH4 production and correlations with production traits. Data were available on 184 Holstein-Friesian cows. Methane production was measured in the milking robot during milking from December 2009 to April 2010. In total 2,456 observations for CH4 production were available. Milk yield (MY) and body weight (BW) were obtained at every milking from November 2008 to October 2010. In total 4,567 observations for milk yield and 4,570 observations for BW were available. Restricted maximum likelihood, using random regression models, was used to analyze the data. Heritability (standard error given in parentheses) for CH4 production ranged from 0.12 (0.16) to 0.45 (0.11), and genetic correlations with MY ranged from 0.49 (0.12) to 0.54 (0.26). The positive genetic correlation between CH4 production and milk yield indicates that care needs to be taken when genetically selecting for lower CH4 production, to avoid a decrease in MY at the animal level. However, this study shows that CH4 production is moderately heritable and therefore progress through genetic selection is possible.

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

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

Does the diurnal pattern of enteric methane emissions from dairy cows change over time?

Diet manipulation and genetic selection are two important mitigation strategies for reducing enteric methane (CH4) emissions from ruminant livestock. The aim of this study was to assess whether the diurnal pattern of CH4 emissions from individual dairy cows changes over time when cows are fed on diets varying in forage composition. Emissions of CH4 from 36 cows were measured during milking in an automatic (robotic) milking station in three consecutive feeding periods, for a total of 84 days. In Periods 1 and 2, the 36 cows were fed a high-forage partial mixed ration (PMR) containing 75% forage, with either a high grass silage or high maize silage content. In Period 3, cows were fed a commercial PMR containing 69% forage. Cows were offered PMR ad libitum plus concentrates during milking and CH4 emitted by individual cows was sampled during 8662 milkings. A linear mixed model was used to assess differences among cows, feeding periods and time of day. Considerable variation was observed among cows in daily mean and diurnal patterns of CH4 emissions. On average, cows produced less CH4 when fed on the commercial PMR in feeding Period 3 than when the same cows were fed on high-forage diets in feeding Periods 1 and 2. The average diurnal pattern for CH4 emissions did not significantly change between feeding periods and as lactation progressed. Emissions of CH4 were positively associated with dry matter (DM) intake and forage DM intake. It is concluded that if the management of feed allocation remains constant then the diurnal pattern of CH4 emissions from dairy cows will not necessarily alter over time. A change in diet composition may bring about an increase or decrease in absolute emissions over a 24-h period without significantly changing the diurnal pattern unless management of feed allocation changes. These findings are important for CH4 monitoring techniques that involve taking measurements over short periods within a day rather than complete 24-h observations.

Transport of fatty acids within plasma lipoproteins in lactating and non-lactating cows fed on fish oil and hydrogenated palm oil.

The aim of this study was to elucidate the effect of dietary fish oil (FO) and a blend of FO and hydrogenated palm oil (FOPO) on transport of fatty acids (FA) within plasma lipoproteins in lactating and non-lactating cows. Two trials were conducted (one with lactating and another with non-lactating dairy cows) in two 3 × 3 Latin squares that included three periods of 21 days. Dietary treatments for lactating cows consisted of a basal diet (Control; no fat supplement), and fat-supplemented diets containing FO (500 g/day/cow) and FOPO (250 FO + 250 g/day/cow hydrogenated palm oil). For non-lactating cows, dietary treatments consisted of a basal diet (Control; no fat supplement), and fat-supplemented diets containing FO (170 g/day/cow) and FOPO (85 FO + 85 hydrogenated palm oil g/day/cow). In lactating cows, compared with control and FOPO, FO increased C16:0, C18:3 cis-9, 12, 15, C18:2 cis-9, trans-11 and total saturated and polyunsaturated FA in plasma and increased C16:0, C18:2 cis-9, trans-11, total polyunsaturated and total polyunsaturated n-6 in high-density lipoprotein (HDL), whereas in non-lactating cows, compared with control and FOPO, FO increased C16:0, C18:1 trans-11, C18:2 trans-9, 12, C18:2 cis-9, trans-11, C20:5 n-3 and total saturated and polyunsaturated FA in plasma; C16:0, C18:1 trans-11, C18:1 cis-9, C18:2 trans-9, 12, C20:5 n-3 and total monounsaturated FA in HDL; and C18:1 trans-6-8, C18:1 trans-9, C18:1 trans-10, C18:1 trans-11, C18:3 cis-9, 12, 15 and C20:5 n-3 in low-density lipoprotein (LDL). FO increased C20:5 n-3 in plasma and lipoproteins in non-lactating cows and increased C18:3 cis-9, 12, 15 in plasma (in lactating cows) and LDL (in non-lactating cows). We concluded from results of this study that in bovine plasma, the LDL fraction appears to be the main lipoprotein transporting C18:1 trans isomers and is more responsive than other lipoprotein fractions to variation in supply of dietary lipids.

Quantitative analysis of ruminal bacterial populations involved in lipid metabolism in dairy cows fed different vegetable oils.

Vegetable oils are used to increase energy density of dairy cow diets, although they can provoke changes in rumen bacteria populations and have repercussions on the biohydrogenation process. The aim of this study was to evaluate the effect of two sources of dietary lipids: soybean oil (SO, an unsaturated source) and hydrogenated palm oil (HPO, a saturated source) on bacterial populations and the fatty acid profile of ruminal digesta. Three non-lactating Holstein cows fitted with ruminal cannulae were used in a 3×3 Latin square design with three periods consisting of 21 days. Dietary treatments consisted of a basal diet (Control, no fat supplement) and the basal diet supplemented with SO (2.7% of dry matter (DM)) or HPO (2.7% of DM). Ruminal digesta pH, NH3-N and volatile fatty acids were not affected by dietary treatments. Compared with control and HPO, total bacteria measured as copies of 16S ribosomal DNA/ml by quantitative PCR was decreased (P<0.05) by SO. Fibrobacter succinogenes, Butyrivibrio proteoclasticus and Anaerovibrio lipolytica loads were not affected by dietary treatments. In contrast, compared with control, load of Prevotella bryantii was increased (P<0.05) with HPO diet. Compared with control and SO, HPO decreased (P<0.05) C18:2 cis n-6 in ruminal digesta. Contents of C15:0 iso, C18:11 trans-11 and C18:2 cis-9, trans-11 were increased (P<0.05) in ruminal digesta by SO compared with control and HPO. In conclusion, supplementation of SO or HPO do not affect ruminal fermentation parameters, whereas HPO can increase load of ruminal P. bryantii. Also, results observed in our targeted bacteria may have depended on the saturation degree of dietary oils.

Short communication: Chemical composition, fatty acid composition, and sensory characteristics of Chanco cheese from dairy cows supplemented with soybean and hydrogenated vegetable oils.

Lipid supplements can be used to alter fatty acid (FA) profiles of dairy products. For Chanco cheese, however, little information is available concerning effects of lipid supplements on sensorial properties. The objective of this study was to examine effects of supplementation of dairy cow diets with soybean (SO) and hydrogenated vegetable (HVO) oils on chemical and FA composition of milk and cheese and sensory characteristics of cheese. Nine multiparous Holstein cows averaging 169±24d in milk at the beginning of the study were used in a replicated (n=3) 3×3 Latin square design that included 3 periods of 21d. All cows received a basal diet formulated with a 56:44 forage:concentrate ratio. Dietary treatments consisted of the basal diet (control; no fat supplement), and the basal diet supplemented with SO (unrefined oil; 500g/d per cow) and HVO (manufactured from palm oil; 500g/d per cow). Milk fat yield was lower with HVO compared with control and SO. Cheese chemical composition and sensory profile were not affected by dietary treatment. Vaccenic (C18:1 trans-11) and oleic (C18:1 cis-9) acids were higher for SO than for control and HVO. Compared with control and HVO, SO decreased saturated FA and increased monounsaturated FA. The thrombogenic index of milk and cheese produced when cows were fed SO was lower than when cows were fed on control and HVO. The outcome of this study showed that, compared with control and HVO, supplementing dairy cow diets with SO improves milk and cheese FA profile without detrimental effects on the chemical composition of milk and cheese and the sensory characteristics of cheese.

Methane emissions among individual dairy cows during milking quantified by eructation peaks or ratio with carbon dioxide.

The aims of this study were to compare methods for examining measurements of CH4 and CO2 emissions of dairy cows during milking and to assess repeatability and variation of CH4 emissions among individual dairy cows. Measurements of CH4 and CO2 emissions from 36 cows were collected in 3 consecutive feeding periods. In the first period, cows were fed a commercial partial mixed ration (PMR) containing 69% forage. In the second and third periods, the same 36 cows were fed a high-forage PMR ration containing 75% forage, with either a high grass silage or high maize silage content. Emissions of CH4 during each milking were examined using 2 methods. First, peaks in CH4 concentration due to eructations during milking were quantified. Second, ratios of CH4 and CO2 average concentrations during milking were calculated. A linear mixed model was used to assess differences between PMR. Variation in CH4 emissions was observed among cows after adjusting for effects of lactation number, week of lactation, diet, individual cow, and feeding period, with coefficients of variation estimated from variance components ranging from 11 to 14% across diets and methods of quantifying emissions. No significant difference was detected between the 3 PMR in CH4 emissions estimated by either method. Emissions of CH4 calculated from eructation peaks or as CH4 to CO2 ratio were positively associated with forage dry matter intake. Ranking of cows according to CH4 emissions on different diets was correlated for both methods, although rank correlations and repeatability were greater for CH4 concentration from eructation peaks than for CH4-to-CO2 ratio. We conclude that quantifying enteric CH4 emissions either using eructation peaks in concentration or as CH4-to-CO2 ratio can provide highly repeatable phenotypes for ranking cows on CH4 output.

Variation in enteric methane emissions among cows on commercial dairy farms.

Methane (CH4) emissions by dairy cows vary with feed intake and diet composition. Even when fed on the same diet at the same intake, however, variation between cows in CH4 emissions can be substantial. The extent of variation in CH4 emissions among dairy cows on commercial farms is unknown, but developments in methodology now permit quantification of CH4 emissions by individual cows under commercial conditions. The aim of this research was to assess variation among cows in emissions of eructed CH4 during milking on commercial dairy farms. Enteric CH4 emissions from 1964 individual cows across 21 farms were measured for at least 7 days/cow using CH4 analysers at robotic milking stations. Cows were predominantly of Holstein Friesian breed and remained on the same feeding systems during sampling. Effects of explanatory variables on average CH4 emissions per individual cow were assessed by fitting a linear mixed model. Significant effects were found for week of lactation, daily milk yield and farm. The effect of milk yield on CH4 emissions varied among farms. Considerable variation in CH4 emissions was observed among cows after adjusting for fixed and random effects, with the CV ranging from 22% to 67% within farms. This study confirms that enteric CH4 emissions vary among cows on commercial farms, suggesting that there is considerable scope for selecting individual cows and management systems with reduced emissions.

A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms.

Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity.

Reducing dietary protein in dairy cow diets: implications for nitrogen utilization, milk production, welfare and fertility.

In light of increasing global protein prices and with the need to reduce environmental impact of contemporary systems of milk production, the current review seeks to assess the feasibility of reducing levels of dietary CP in dairy cow diets. At CP levels between 140 and 220 g/kg DM there is a strong positive relationship between CP concentration and dry matter intake (DMI). However, such effects are modest and reductions in DMI when dietary CP is below 180 g/kg DM can be at least partially offset by improving the digestibility and amino acid profile of the undegradable protein (UDP) component of the diet or by increasing rumen fermentable energy. Level and balance of intestinally absorbable amino acids, in particular methionine and lysine, may become limiting at lower CP concentrations. In general the amino acid composition of microbial protein is superior to that of UDP, so that dietary strategies that aim to promote microbial protein synthesis in the rumen may go some way to correcting for amino acid imbalances in low CP diets. For example, reducing the level of NDF, while increasing the proportion of starch, can lead to improvements in nitrogen (N) utilisation as great as that achieved by reducing dietary CP to below 150 g/kg. A systematic review and meta-analysis of responses to rumen protected forms of methionine and lysine was conducted for early/mid lactation cows fed diets containing ⩽150 g CP/kg DM. This analysis revealed a small but significant (P=0.002) increase in milk protein yield when cows were supplemented with these rumen protected amino acids. Variation in milk and milk protein yield responses between studies was not random but due to differences in diet composition between studies. Cows fed low CP diets can respond to supplemental methionine and lysine so long as DMI is not limiting, metabolisable protein (MP) is not grossly deficient and other amino acids such as histidine and leucine do not become rate limiting. Whereas excess dietary protein can impair reproduction and can contribute to lameness, there is no evidence to indicate that reducing dietary CP levels to around 140 to 150 g CP/kg DM will have any detrimental effect on either cow fertility or health. Contemporary models that estimate MP requirements of dairy cows may require refinement and further validation in order to predict responses with low CP diets.

Mutations in genes involved in oestrous cycle associated expression of oestrus.

Detection of oestrus is a key determinant of profitability of dairy herds, but oestrus is increasingly difficult to observe in the modern dairy cow, with shorter duration and less intense oestrus. Concurrent with the unfavourable correlation between milk yield and fertility, oestrous detection rates have decreased to less than 50%. A number of mutations have been identified in genes associated with fertility and production traits, but, to date, no single nucleotide polymorphism (SNP) has been associated with oestrous expression. Therefore, the objective of this study was to investigate SNPs, linked to fertility, for the association with oestrous expression. Blood was collected from 205 Holstein Friesian dairy cows and genotyped at 41 loci of 18 genes chosen for their roles in the oestrous cycle and milk production. SNPs were then examined for correlations with increase in activity at oestrus, recorded via activity monitors, using generalised linear models. Physical activity increased at oestrus between two and four fold. Larger increases were associated with mutant alleles in oestrogen receptor-α and gonadotrophin releasing hormone receptor genes (P<0.05) and in the STAT5A gene (P<0.05). Smaller increases were associated with mutant alleles of the activin receptor type IIB and prolactin receptor genes (P<0.10). In conclusion, alleles in these five genes provide the opportunity for selection of animals displaying greater oestrous activity which could aid reversal of the decrease in oestrous detection and thereby contribute to sustainability of the dairy industry worldwide.

Technical note: a novel approach to the detection of estrus in dairy cows using ultra-wideband technology.

Detection of estrus is a key determinant of profitability of dairy herds, but estrus is increasingly difficult to observe in the modern dairy cow with shorter duration and less-intense estrus. Concurrent with the unfavorable correlation between milk yield and fertility, estrus-detection rates have declined to less than 50%. We tested ultra-wideband (UWB) radio technology (Thales Research & Technology Ltd., Reading, UK) for proof of concept that estrus could be detected in dairy cows (two 1-wk-long trials; n=16 cows, 8 in each test). The 3-dimensional positions of 12 cows with synchronized estrous cycles and 4 pregnant control cows were monitored continuously using UWB mobile units operating within a network of 8 base units for a period of 7d. In the study, 10 cows exhibited estrus as confirmed by visual observation, activity monitoring, and milk progesterone concentrations. Automated software was developed for analysis of UWB data to detect cows in estrus and report the onset of estrus in real time. The UWB technology accurately detected 9 out of 10 cows in estrus. In addition, UWB technology accurately confirmed all 6 cows not in estrus. In conclusion, UWB technology can accurately detect estrus and hence we have demonstrated proof of concept for a novel technology that has significant potential to improve estrus-detection rates.

Variation among individual dairy cows in methane measurements made on farm during milking.

The objective of this study was to quantify on-farm variation between and within cows in methane emissions measured during milking, and to determine which factors are related to this variation. Methane emission rate during milking (MERm) was recorded at milking using methane analyzers installed in automatic (robotic) milking stations for 215 cows over a period of 5 mo. Between-cow variation in MERm (mean 2.07, SD 0.629 g/min), was greater than within-cow variation and was related to variation in body weight, milk yield, parity, and week of lactation. Estimation of daily methane emissions from MERm data, using an equation derived from comparisons with respiration chamber data, produced estimates that ranged from 278 to 456 g of CH4/d and were commensurate with values predicted from metabolizable energy requirements for observed body weight and milk yield. It is concluded that methane emissions vary considerably between dairy cows housed under commercial conditions. This variation needs to be taken into account when performing inventories or testing mitigation strategies, but it might offer opportunities for genetic selection.

On-farm methane measurements during milking correlate with total methane production by individual dairy cows.

The objective of this study was to investigate whether measurement of methane emissions by individual dairy cows during milking could provide a useful technique for monitoring on-farm methane emissions. To quantify methane emissions from individual cows on farm, we developed a novel technique based on sampling air released by eructation during milking. Eructation frequency and methane released per eructation were used to estimate methane emission rate. For 82 cows, methane emission rate during milking increased with daily milk yield (r = 0.71), but varied between individuals with the same milk yield and fed the same diet. For 12 cows, methane emission rate recorded during milking on farm showed a linear relationship (R² = 0.79) with daily methane output by the same cows when housed subsequently in respiration chambers. For 42 cows, the methane emission rate during milking was greater on a feeding regimen designed to produce high methane emissions, and the increase compared with a control regimen was similar to that observed for cows in respiration chambers. It was concluded that, with further validation, on-farm monitoring of methane emission rate during milking could provide a low-cost reliable method to estimate daily methane output by individual dairy cows, which could be used to study variation in methane, to identify cows with low emissions, and to test outcomes of mitigation strategies.

Short communication: heritability of milk fatty acid composition and stearoyl-CoA desaturase indices in dairy cows.

Activity of stearoyl-CoA desaturase (SCD) in the mammary gland is important for determining the relative proportions of saturated and monounsaturated fatty acids in milk and the concentration of the conjugated linoleic acid isomer rumenic acid (RA; cis-9,trans-11 18:2). Previous studies identified a large degree of between-cow variation in SCD activity, which was consistent across diets and suggests a genetic influence. The objectives of this study were to quantify genetic and phenotypic variations in fatty acid concentrations and SCD indices in milk fat and to estimate their heritabilities in a population of United Kingdom dairy cows. Milk samples were collected from 2,408 daughters of 597 Holstein-Friesian sires on 325 commercial farms for determination of fatty acid profiles. Indices of SCD activity were calculated by expressing each SCD product (cis-9 14:1, cis-9 16:1, cis-9 18:1, and RA) as a proportion of the precursor plus product [e.g., SCDI(14)=cis-9 14:1/(14:0+cis-9 14:1)]. For individual fatty acids, phenotypic variance was considerably greater than additive genetic variance, resulting in small and nonsignificant heritability estimates (+/- standard error) for all except 6:0 (h(2)=0.27+/-0.10), 8:0 (h(2)=0.27+/-0.09), 12:0 (h(2)=0.13+/-0.07), cis-9 14:1 (h(2)=0.28+/-0.10), and cis-9 18:1 (h(2)=0.12+/-0.07). Heritability estimates of desaturase indices were significant for SCDI(14) (h(2)=0.38+/-0.11), SCDI(18) (h(2)=0.19+/-0.09), and SCDI(RA) (h(2)=0.21+/-0.09), but not for SCDI(16) (h(2)=0.05+/-0.06). This study provides evidence that additive effects are responsible for a significant proportion of the phenotypic variation in SCD activity in dairy cows. It is concluded that because heritability of desaturase indices is moderate and significant in many cases, these indices could be investigated further for use in future breeding programs to increase concentrations of monounsaturated fatty acids and RA while decreasing concentrations of saturated fatty acids in milk fat.

Dietary omega-3 and -6 polyunsaturated fatty acids affect the composition and development of sheep granulosa cells, oocytes and embryos.

The evidence that omega-3 (n-3) and -6 (n-6) polyunsaturated fatty acids (PUFAs) have differential effects on ovarian function, oocytes and embryo quality is inconsistent. We report on the effects of n-3 versus n-6 PUFA-enriched diets fed to 36 ewes over a 6-week period, prior to ovarian stimulation and follicular aspiration, on ovarian steroidogenic parameters and embryo quality. Follicle number and size were unaltered by diet, but follicular-fluid progesterone concentrations were greater in n-3 PUFA-fed ewes than in n-6 PUFA-fed ewes. The percentage of saturated FAs (mostly stearic acid) was greater in oocytes than in either granulosa cells or plasma, indicating selective uptake and/or de novo synthesis of saturated FAs at the expense of PUFAs by oocytes. High-density lipoproteins (HDLs) fractionated from sera of these ewes increased granulosa cell proliferation and steroidogenesis relative to the FA-free BSA control during culture, but there was no differential effect of n-3 and n-6 PUFAs on either oestradiol or progesterone production. HDL was ineffective in delivering FAs to embryos during culture, although n-6 PUFA HDL reduced embryo development. All blastocysts, irrespective of the treatment, contained high levels of unsaturated FAs, in particular linoleic acid. Transcripts for HDL and low-density lipoprotein (LDL) receptors (SCARB1 and LDLR) and stearoyl-CoA desaturase (SCD) are reported in sheep embryos. HDL reduced the expression of transcripts for LDLR and SCD relative to the BSA control. The data support a differential effect of n-3 and n-6 PUFAs on ovarian steroidogenesis and pre-implantation development, the latter in the absence of a net uptake of FAs.

Dietary carbohydrates and amino acids influence oocyte quality in dairy heifers.

The objective of the present experiment was to determine whether increasing plasma insulin by different nutritional regimes affects oocyte quality. Holstein dairy heifers (eight per treatment) were assigned, using a two times two factorial design, to diets containing either low or high dietary leucine and either low or high dietary starch. Each heifer underwent six sessions of ovum pick-up beginning 25 days after introduction of the diets. Oocyte quality was assessed by development to the blastocyst stage in synthetic oviducal fluid following in vitro fertilisation. Feeding diets containing high leucine resulted in significantly higher plasma free leucine and tyrosine concentrations. The high-starch diet significantly increased plasma insulin but not glucagon concentration, whereas high dietary leucine increased plasma glucagon but not insulin. Oocyte cleavage was not influenced by diet. The high-starch diet, which was associated with a high plasma insulin : glucagon ratio, had adverse effects on oocyte quality that were avoided when leucine intake was increased. There was an association between total plasma free amino acid concentration and oocyte cleavage. Therefore, in dairy heifers dietary amino acids and carbohydrates during antral follicle development appear to mediate effects on oocyte quality by different mechanisms. These findings have implications for both diet formulation and feeding regimes.