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Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH 4 ]:[CO 2 ], in breath from individual animals (the so-called "sniffer technique") and estimated CO 2 production can be used to estimate CH 4 production, provided that CO 2 production can be reliably calculated. This would allow CH 4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH 4 production might become possible and their values could be used for breeding of low CH 4 -emitting animals. Estimates of CO 2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO 2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO 2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO 2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 ("best model"), where all significant traits were included; model 2 ("on-farm model"), where DMI was excluded; and model 3 ("reduced on-farm model"), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (-0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO 2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO 2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO 2 production from lactating dairy cows., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The frequency, duration, and intensity of heat waves in Australia are increasing. To reduce the impact of heat waves on milk production, novel management strategies are required. Altering the forage type and amount offered affect the heat load on dairy cows and offer potential strategies to ameliorate the effects of hot weather. Thirty-two multiparous, lactating Holstein-Friesian cows were assigned one of four dietary treatments: chicory high amount, chicory low amount, pasture silage high amount, or pasture silage low amount. These cows were exposed to a heat wave in controlled-environment chambers. Cows that were offered fresh chicory had similar feed intake to cows that were offered pasture silage (15.3 kg DM/d). However, cows that were offered chicory produced greater energy-corrected milk (21.9 vs. 17.2 kg/d) and had a lower maximum body temperature (39.4 vs. 39.6 °C) than cows that were offered pasture silage overall. Cows that were offered the high amount of forage had greater feed intake (16.5 vs. 14.1 kg DM/d) and energy corrected milk yield (20.0 vs. 17.9 kg/d) than cows that were offered the low amount, as intended, but with no difference in maximum body temperature (39.5 °C). We conclude that feeding chicory instead of pasture silage to dairy cows shows promise as a dietary strategy to ameliorate the effect of heat exposure, and there was no advantage in restricting feed amount.

Cereal grains that differ in the rate and extent of ruminal fermentation differ in heat increment and may be used to improve thermoregulation during heat stress. This experiment investigated the responses of dairy cows in late lactation to a heat challenge when offered wheat-grain or corn-grain. Eighteen lactating cows, 220 ± 94 (mean ± standard deviation) days in milk, 3.7 ± 0.17 years of age and 558 ± 37 kg bodyweight, were allocated treatments containing 6 kg dry matter (DM)/day of wheat grain or 6 kg DM/day corn grain (9 per treatment) plus 14 kg DM/day of alfalfa hay. Measurements were made during a 7-day pre-challenge period at ambient conditions in individual stalls, during a 4-day heat challenge (temperature humidity index of 74 to 84) in individual controlled-climate chambers, then during a 7-day recovery period at ambient conditions in individual stalls. During the heat challenge, cows offered corn had lower respiration rates ( p = 0.017) and greater feed intake ( p = 0.021) but energy-corrected milk ( p = 0.097) was not different to that of cows offered wheat. Feeding corn grain to dairy cows during a heat challenge reduced some of the negative impacts of heat stress, enabling the cows to consume more forage compared with supplementing with wheat grain.

Fermentation of pasture grasses and grains in the rumen of dairy cows and other ruminants produces methane as a by-product, wasting energy and contributing to the atmospheric load of greenhouse gasses. Many feeding trials in farmed ruminants have tested the impact of dietary components on feed efficiency, productivity and methane yield (MeY). Such diets remodel the rumen microbiome, altering bacterial, archaeal, fungal and protozoan populations, with an altered fermentation outcome. In dairy cows, some dietary grains can reduce enteric methane production. This is especially true of wheat, in comparison to corn or barley. Using a feeding trial of cows fed rolled wheat, corn or barley grain, in combination with hay and canola, we identified wheat-associated changes in the ruminal microbiome. Ruminal methane production, pH and VFA concentration data together with 16S rRNA gene amplicon sequences were used to compare ruminal bacterial and archaeal populations across diets. Differential abundance analysis of clustered sequences (OTU) identified members of the bacterial families Lachnospiraceae, Acidaminococcaceae, Eubacteriaceae, Prevotellaceae, Selenomonadaceae, Anaerovoracaceae and Fibrobacteraceae having a strong preference for growth in wheat-fed cows. Within the methanogenic archaea, (at >99% 16S rRNA sequence identity) the growth of Methanobrevibacter millerae was favoured by the non-wheat diets, while Methanobrevibacter olleyae was unaffected. From the wheat-preferring bacteria, correlation analysis found OTU strongly linked to reduced MeY, reduced pH and raised propionic acid levels. OTU from the genera Shuttleworthia and Prevotella_7 and especially Selenomonadaceae had high anti-methane correlations. An OTU likely representing (100% sequence identity) the fumarate-reducing, hydrogen-utilising, rumen bacterium Mitsuokella jalaludinii, had an especially high negative correlation coefficient (-0.83) versus MeY and moderate correlation (-0.6) with rumen pH, strongly suggesting much of the MeY suppression is due to reduced hydrogen availablity. Other OTU, representing as yet unknown species from the Selenomonadaceae family and the genera Prevotella_7, Fibrobacter and Syntrophococcus also had high to moderate negative MeY correlations, but low correlation with pH. These latter likely represent bacterial species able to reduce MeY without causing greater ruminal acidity, making them excellent candidates, provided they can be isolated, for development as anti-methane probiotics., Competing Interests: No authors have competing interests.

Ex ante economic analysis can be used to establish the production threshold for a proposed experimental diet to be as profitable as the control treatment. This study reports (1) a pre-experimental economic analysis to estimate the milk production thresholds for an experiment where dietary supplements were fed to dairy cows experiencing a heat challenge, and (2) comparison of these thresholds to the milk production results of the subsequent animal experiment. The pre-experimental thresholds equated to a 1% increase in milk production for the betaine supplement, 9% increase for the fat supplement, and 11% increase for fat and betaine in combination, to achieve the same contribution to farm profit as the control diet. For the post-experimental comparison, previously modelled climate predictions were used to extrapolate the milk production results from the animal experiment over the annual hot-weather period for the dairying region in northern Victoria, Australia. Supplementing diets with fat or betaine had the potential to produce enough extra milk to exceed the production thresholds, making either supplement a profitable alternative to feeding the control diet during the hot-weather period. Feeding fat and betaine in combination failed to result in the extra milk required to justify the additional cost when compared to the control diet.

Supplementing the diet of lactating cows with ingredients that increase energy density, or reduce internal heat production, may reduce some of the negative impacts of hot weather on milk yield. Thirty-two dairy cows were assigned either: (1) basal diet only, (2) basal diet plus canola oil, (3) basal diet plus betaine, or (4) basal diet plus canola oil and betaine. The basal diet was lucerne hay, pasture silage, and grain. Cows were exposed to a four-day heat challenge (temperature-humidity index 74 to 84) in controlled-environment chambers. Canola oil supplementation increased milk production (22.0 vs. 18.7 kg/d) across all periods of our experiment and increased body temperature (39.6 vs. 39.0 °C) during the heat challenge. Betaine supplementation reduced maximum body temperature during the pre-challenge period (39.2 vs. 39.6 °C) but not during the heat challenge (40.3 °C). Cows fed canola oil had greater declines in dry matter intake (5.4 vs 2.7 kg DM) and energy corrected milk (1.3 vs. 1.0 kg) from the pre-challenge to the heat challenge than other cows. Contrary to our expectations, the combination of fat and betaine supplements did not result in a clear benefit in terms of milk production or body temperature. Further work is warranted to understand the interactions between diet and hot weather.

Selecting for lower methane (CH 4 ) emitting animals is one of the best approaches to reduce CH 4 given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH 4 , combining data from different countries could help to expedite accurate genetic parameters for CH 4 traits and build a future genomic reference population. Additionally, if we want to include CH 4 in the breeding goal, it is important to know the genetic correlations of CH 4 traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH 4 . The third aim was to evaluate the expected response of economically important traits by including CH 4 traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

There has been considerable interest in the use of red seaweed, and in particular Asparagopsis taxiformis, to increase production of cattle and to reduce greenhouse gas emissions. We hypothesized that feeding seaweed or seaweed derived products would increase beef or dairy cattle performance as indicated by average daily gain (ADG), feed efficiency measures, milk production, and milk constituents, and reduce methane emissions. We used meta-analytical methods to evaluate these hypotheses. A comprehensive search of Google Scholar, Pubmed and ISI Web of Science produced 14 experiments from which 23 comparisons of treatment effects could be evaluated. Red seaweed (Asparagopsis taxiformis) and brown seaweed (Ascophyllum nodosum) were the dominant seaweeds used. There were no effects of treatment on ADG or dry matter intake (DMI). While there was an increase in efficiency for feed to gain by 0.38 kg per kg [standardized mean difference (SMD) = 0.56; P = 0.001] on DerSimonian and Laird (D&L) evaluation, neither outcome was significant using the more rigorous robust regression analysis (P >0.06). The type of seaweed used was not a significant covariable for ADG and DMI, but A. nodosum fed cattle had lesser feed to gains efficiency compared to those fed A. taxiformis. Milk production was increased with treatment on weighted mean difference (WMD; 1.35 ± 0.44 kg/d; P <0.001); however, the SMD of 0.45 was not significant (P = 0.111). Extremely limited data suggest the possibility of increased percentages of milk fat (P = 0.040) and milk protein (P = 0.001) on (D&L) WMD evaluation. The limited data available indicate dietary supplementation with seaweed produced a significant and substantial reduction in methane yield by 5.28 ± 3.5 g/kg DMI (P = 0.003) on D&L WMD evaluation and a D&L SMD of -1.70 (P = 0.001); however, there was marked heterogeneity in the results (I2 > 80%). In one comparison, methane yield was reduced by 97%. We conclude that while there was evidence of potential for benefit from seaweed use to improve production and reduce methane yield more in vivo experiments are required to strengthen the evidence of effect and identify sources of heterogeneity in methane response, while practical applications and potential risks are evaluated for seaweed use., Competing Interests: The authors have declared that no competing interests exist.

Despite the fact that the sulphur hexafluoride (SF 6 ) tracer technique was developed over 25 years ago to measure methane production from grazing and non-housed animals, no studies have specifically investigated whether ambient wind speed, temperature, relative humidity and rainfall influence the accuracy of the method. The aim of this research was to investigate how these weather factors influence the measurement of enteric methane production by the SF 6 technique. Six different cohorts of dairy cows (40 per cohort) were kept outdoors and fed a common diet during spring in 3 consecutive years. Methane production from individual cows was measured daily over the last 5 days of each 32-day period. An automated weather station measured air temperature, wind speed, relative humidity and rainfall every 10 min. Regression analyses were used to relate the average daily wind speed, average daily temperature, average daily relative humidity and total daily rainfall measurements to dry matter intake, average daily methane production and methane yield of each cohort of cows. It was concluded that the modified SF 6 technique can be used outdoors during a range of wind speeds, ambient temperatures, relative humidities and rainfall conditions without causing a significant effect on the measurement of methane production or methane yield of dairy cows.

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF 6 tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Ozone (O 3 ) is volatile, highly oxidative, and has theoretical potential to reduce ruminant enteric methanogenesis by interactions between archaea and bacteria, and substrate and oxygen. The effects of O 3 on the rumen microbiota, fermentation parameters, and CH 4 emissions were studied through in vitro fermentation using a RUSITEC apparatus with O 3 dissolved in the salivary buffer. The substrate consisted of maize silage or grain concentrates, and the treatments were (1) control (no O 3 ) and (2) O 3 at 0.07 ± 0.022 mg/L in the buffer. A 4-day adaptation period followed by a 6-day experimental period was used for measuring gas production and composition, as well as fermentation characteristics, which included ruminal volatile fatty acids (VFA) and liquid- and solid-associated microbial communities. Ozone treatment decreased total gas production by 15.4%, most notably CH 4 production by 20.4%, and CH 4 gas concentration by 5.8%, without compromising dry matter digestibility (DMD) of either maize silage or grain concentrates. There were no significant effects of O 3 treatment on VFA production or pH. Ozone treatment reduced the relative abundance of methanogens, particularly Methanomicrobium . This study demonstrates the potential use of O 3 as a method to reduce ruminant enteric methanogenesis., (Copyright © 2020 Zhao, Caro, Holman, Gzyl, Moate and Chaves.)

Addition of fats to the diets of ruminants has long been known to result in a reduction in enteric methane emissions. Tannins have also been used to reduce methane emissions but with mixed success. However, the effect of feeding fat in combination with tannin is unknown. Eight ruminally cannulated Holstein-Friesian cows were fed four diets in a double Latin-square, full crossover sequence. The treatments were 800 ml/day of water (CON), 800 g/day of cottonseed oil, 400 g/day of tannin, and 800 g/day of cottonseed oil and 400 g/day of tannin in combination (fat- and tannin-supplemented diet). Methane emissions were measured using open-circuit respiration chambers. Intake of basal diets was not different between treatments. Cows fed cottonseed oil had greater milk yield (34.9 kg/day) than those fed CON (32.3 kg/day), but the reduced concentration of milk fat meant there was no difference in energy-corrected milk between treatments. Methane yield was reduced when either cottonseed oil (14%) or tannin (11%) was added directly to the rumen, and their effect was additive when given in combination (20% reduction). The mechanism of the anti-methanogenic effect remains unclear but both fat and tannin appear to cause a reduction in fermentation in general rather than cause a change in the type of fermentation.

Background: A pelleted diet containing camelina hay (CAMH) or camelina meal (CAMM) as a supplement along with a control pellet (CONT) diet formulated with commonly available feeds during summer was used to investigate an alternative pathway for sustainable meat production. Sustainable meat production was based on a simple estimation of income from meat produced versus feed costs if animals were fed for an extended period over summer compared to early slaughter at the beginning of summer. Eighty maternal composite wether lambs (Composite) based on Coopworth genetics and 80 pure Merino wether yearlings were divided into 10 groups within breed ( n  = 8) using stratified randomisation based on liveweights. Following 1 week of adaptation to experimental diets, animals were fed experimental diets for up to10 weeks., Results: Animals were slaughtered after either 8, 9 or 10 weeks of full feeding when the average liveweight of diet/genetic combination reached a weight appropriate for either 'heavy lamb' or 'heavy hogget' production, which occurred between 8 and 10 weeks of full feeding. There was no diet × breed interactions except for dressing percentage (DP), where Composite lambs fed the CAMH diet had the greatest DP (48.1 ± 0.35) and the Merino yearlings fed the CAMM diet the lowest DP (45.8 ± 0.33). Composite lambs gained 17.6-20.3 kg and Merino yearlings gained 10.7-12.9 kg liveweight. Based on their DP, this resulted in the production of approximately 8.3-9.5 kg additional carcass weight in Composites and 4.9-5.7 kg in Merinos, which in turn produced greater profit per Composite lamb and a small profit per Merino yearling., Conclusions: Composite lambs fed CAMM and CAMH had 5% greater carcass weights at slaughter compared to the CONT group, but dietary treatments did not change carcass weight of Merino yearlings at slaughter. The extended feeding approach offered the producer an estimated economic gain of AUD $20.00 to $25.00 when yearly average prices were used (Method 1) and AUD $40.00 to $47.70 when pre- and post-summer average prices were used (Method 2) per Composite lambs, but extra carcass gain did not result in the same profit per Merino yearling. Among the Composites, the profit for animals fed the CAMH and CAMM were AUD $2.75 to $4.50 greater than CONT group when full year average prices were applied while AUD $3.50 to $5.50 greater than CONT group when pre- and post-summer average prices were applied. However, we acknowledge a combination approach of extended feeding for a portion of animals already on ground and selling the remaining animals pre-summer with joining of additional ewes is the most likely strategy. Considering the scenario of extended feeding for 3 weeks, based on the growth rates observed for Composite lambs, if an additional 2 kg carcass weight per animal can be gained for 50% of the 22 million lambs slaughtered in Australia (= 11 million animals), it would potentially supply an additional 22 million kg of lamb carcasses produced per annum. This is equivalent to producing an extra 1 million lamb carcasses per annum weighing 22 kg each. Feeding Composite lambs for an extended period and selling Merino yearlings pre-summer may be a good option due to faster growth rate of Composites that may help quick turn-over to market., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2020.)

Kinetic non-linear metabolic models are used extensively in medical research and increasingly for clinical diagnostic purposes. An example of such a model is the Glucose Minimal Model by Bergman and colleagues [1]. This model is similar to pharmacokinetic/pharmacodynamic models in that like pharmacokinetic/pharmacodynamic models, it is based on a small number of fairly simple ordinary differential equations and it aims to determine how the changing concentration of one blood constituent influences the concentration of another constituent. Although such models may appear prima facie, to be relatively simple, they have gained a reputation of being difficult to fit to data, especially in a consistent and repeatable fashion. Consequently, researchers and clinicians have generally relied on dedicated software packages to do this type of modeling. This article describes the use of statistical and spreadsheet software for fitting the Glucose Minimal Model to data from an insulin modified intravenous glucose tolerance test (IM-IVGTT). A novel aspect of the modeling is that the differential equations that are normally used to describe insulin action and the disposition of plasma glucose are first solved and expressed in their explicit forms so as to facilitate the estimation of Glucose Minimal Model parameters using the nonlinear (nl) optimization procedure within statistical and spreadsheet software. The most important clinical parameter obtained from the Glucose Minimal Model is insulin sensitivity (S I ). Using IM-IVGTT data from 42 horses in one experiment and 48 horses in a second experiment, we demonstrate that estimates of S I derived from the Glucose Minimal Model fitted to data using STATA and Excel, are highly concordant with S I estimates obtained using the industry standard software, MinMod Millennium. This work demonstrates that there is potential for statistical and spreadsheet software to be applied to a wide range of kinetic non-linear modeling problems., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose, (Copyright © 2020. Published by Elsevier B.V.)

Globally, annual production of grape marc (GM), the residue of skins, seeds and stems remaining after making wine, has been estimated to be approximately nine million tonnes. No previous studies have compared effects on milk production and methane emissions when GM from either red or white grapes was fed to dairy cows. This experiment examines the effects of partial replacement of a perennial ryegrass ( Lolium perenne L.) based diet with GM from either red or white grapes on yield and composition of milk and methane emissions. Thirty-two Holstein dairy cows in early lactation were offered either a control diet containing 15.0 kg dry matter (DM) of freshly harvested perennial ryegrass and 5.2 kg of a concentrate mix, or a diet similar to the control diet but with 5 kg DM of ryegrass replaced with 5 kg DM of GM from red grapes (RGM), or a diet similar to the RGM diet except the GM was from white grapes (WGM). Individual cow feed intakes, milk yields, and methane emissions were measured. Both diets containing GM decreased milk yields by approximately 10% and methane emissions by 15%. When fed to dairy cows, GM reduces methane emissions but at the cost of decreased milk production.

Wheat is the most common concentrate fed to grazing dairy cows in Australia, but no studies have examined the effects of wheat proportion in a pasture-based diet on milk production and methane emissions. In this 47-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets during d 1 to 36. Cows in each of the dietary treatment groups were individually offered no wheat (W0) or wheat at 3 kg of dry matter (DM)/d (W3), 6 kg of DM/d (W6), or 9 kg of DM/d (W9). The remainder of the diet was 2.2 kg of DM of concentrate mix and freshly harvested perennial ryegrass (Lolium perenne) such that all individual cows were offered a total diet of approximately 20.2 kg of DM/d. From d 37 to 47 the diets of cows receiving treatments W0 and W3 remained unchanged, but cows in treatments W6 and W9 received the W3 diet. Individual cow feed intakes, milk yields, milk compositions, and methane emissions were measured for d 31 to 35 (period 1) and d 45 to 47 (period 2). During period 1, the mean intakes of cows offered the W0, W3, W6, and W9 diets were 19.2, 20.4, 20.2, and 19.8 kg of DM/d. Diet caused differences in energy-corrected milk, and means for W0, W3, W6, and W9 were 29.5, 32.4, 33.0, and 32.9 kg/d, respectively. Milk fat percentage differed with respective means of 3.93, 3.94, 3.69, and 3.17. Diets also caused differences in methane emissions, with means for W0, W3, W6, and W9 of 440, 431, 414, and 319 g/d. During period 1, the cows fed the W9 diet produced less methane and had lower methane yields (g/kg of DMI) and intensities (g/kg of energy-corrected milk) than cows fed the W3 diet. However, in period 2 when the wheat intake of cows in the W9 treatment was reduced to the same level as in the W3 treatment, their methane emissions, yields, and intensities were similar to those offered the W3 treatment, yet protozoa numbers in ruminal fluid were still much lower than those in cows offered the W3 treatment. Our research shows that for diets based on perennial ryegrass and crushed wheat, only the diet containing more than 30% crushed wheat resulted in substantially depressed milk fat concentration and reduced methane emissions, methane yield, and methane intensity. Thus, although feeding a diet with a high proportion of wheat can cause substantial methane mitigation, it can come at the cost of depression in milk fat concentration., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The dry matter intake (DMI) of forage-fed cattle can be used to predict their methane emissions. However, many cattle are fed concentrate-rich diets that decrease their methane yield. A range of equations predicting methane yield exist, but most use information that is generally unavailable when animals are fed in groups or grazing. The aim of this research was to develop equations based on proportions of ruminal volatile-fatty-acids to predict methane yield of dairy cows fed forage-dominant as well as concentrate-rich diets. Data were collated from seven experiments with a total of 24 treatments, from 215 cows. Forage in the diets ranged from 440 to 1000 g/kg. Methane was measured either by open-circuit respiration chambers or a sulfur hexafluoride (SF 6 ) technique. In all experiments, ruminal fluid was collected via the mouth approximately four hours after the start of feeding. Seven prediction equations were tested. Methane yield (MY) was equally best predicted by the following equations: MY = 4.08 × (acetate/propionate) + 7.05; MY = 3.28 × (acetate + butyrate)/propionate + 7.6; MY = 316/propionate + 4.4. These equations were validated against independent published data from both dairy and beef cattle consuming a wide range of diets. A concordance of 0.62 suggests these equations may be applicable for predicting methane yield from all cattle and not just dairy cows, with root mean-square error of prediction of 3.0 g CH 4 /kg dry matter intake., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

There is a need to quantify methane (CH 4 ) emissions with alternative methods. For the past decade, milk fatty acids (MFA) could be used as proxies to predict CH 4 emissions from dairy cows because of potential common rumen biochemical pathways. However, equations have been developed based on a narrow range of diets and with limited data. The objectives of this study were to (1) construct a set of empirical models based on individual data of CH 4 emissions and MFA from a large number of lactating dairy cows fed a wide range of diets; (2) further increase the models' level of complexity (from farm to research level) with additional independent variables such as dietary chemical composition (organic matter, neutral detergent fiber, crude protein, starch, and ether extract), dairy performance (milk yield and composition), and animal characteristics (days in milk or body weight); and (3) evaluate the performance of the developed models on independent data sets including measurements from individual animals or average measurements of groups of animals. Prediction equations based only on MFA [C10:0, iso C17:0 + trans-9 C16:1,cis-11 C18:1, and trans-11,cis-15 C18:2 for CH 4 production (g/d); iso C16:0, cis-11 C18:1, trans-10 C18:1, and cis-9,cis-12 C18:2 for CH 4 yield (g/kg of dry matter intake, DMI); and iso C16:0, cis-15 C18:1, and trans-10 + trans-11 C18:1 for CH 4 intensity (g/kg of milk)] had a root mean squared error of 65.1 g/d, 2.8 g/kg of DMI, and 2.9 g/kg of milk, respectively, whereas complex equations that additionally used DMI, dietary neutral detergent fiber, ether extract, days in milk, and body weight had a lower root mean squared error of 46.6 g/d, 2.6 g/kg of DMI, and 2.7 g/kg of milk, respectively). External evaluation with individual or mean data not used for equation development led to variable results. When evaluations were performed using individual cow data from an external data set, accurate predictions of CH 4 production (g/d) were obtained using simple equations based on MFA. Better performance was observed on external evaluation with individual data for the simple equation of CH 4 production (g/d, based on MFA), whereas better performance was observed on external evaluation mean data for the simple equation of CH 4 yield (g/kg of DMI). The performance of evaluation of the models is dependent on the domain of validity of the evaluation data sets used (individual or mean)., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

The fortification of milk with phytosterols is an increasingly common practice to enhance the sterol profile and offer consumers potential health benefits. This study investigated whether cattle feed can influence the profile of phytosterols and cholesterol in the milk produced as an alternative to direct fortification of milk. Five experiments were performed using feeds commonly used by Australian dairy farmers and selected formulated rumen-protected feeds. Statistical significances were observed for some individual plant sterols and cholesterol in milk under these differing feeding regimens compared with the respective controls. In the case of the phytosterols, where the daily recommended consumption is typically 2 g per day, the total phytosterols were <0.12 mg/100 mL of milk. An experiment using a rumen-protected feed with high phytosterol levels suggested a decreased transfer of cholesterol to the milk by as much as 20%, although further work is required to confirm these preliminary results. Overall, the study suggests that different feeding practices have minimal effect on the resulting sterol profile of the milk., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: Supplementation of ruminant diets with wheat and corn grains influences ruminal fermentation. In vitro fermentation is a methodology that can be used to screen feeds for their potential to produce enteric methane. However, there is evidence that the diet of the donor cows could impact the results of in vitro analysis. This research investigated the in vitro fermentation of wheat and corn grain when incubated in ruminal fluid from cows fed different grain types and different forage-to-grain ratios., Results: The type of grain fed to the donor cows, as well as forage-to-grain ratio, affected the outcome of fermentation of wheat and corn grain. Differences in methane production (MP) between grains were only observed when incubated with ruminal fluid adapted to each specific grain type. Increasing proportions of wheat but not of corn decreased in vitro MP in a linear manner compared with MP produced from forage only., Conclusions: Wheat grain has a greater in vitro antimethanogenic effect than corn. However, to detect the different fermentations between wheat and corn, grains should be incubated in ruminal fluid from cows adapted to that specific grain type. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

Diets that contain high proportions of either wheat or supplementary fat have been individually reported to reduce enteric methane production. The objective of this research was to determine the effect of dietary fat supplementation on methane emissions and milk yield from cows fed diets containing either corn or wheat grains. It was hypothesized that cows fed a diet containing wheat would produce less methane and have lower methane yield (methane per kg of dry matter intake; MY) than cows fed a diet containing corn and that methane mitigation from fat supplementation would occur irrespective of the type of grain in the basal diet. The experiment involved 32 Holstein-Friesian dairy cows allocated to 1 of 4 treatment groups (n = 8) and individually fed different diets restricted to approximately 90% of their mean ad libitum intake measured during a covariate period. All animals were offered 11.5 kg of dry matter/d of alfalfa hay, 1.8 kg of dry matter/d of solvent-extracted canola meal, and 1 of 4 dietary supplements. Dietary supplements were 8 kg of dry matter/d of either corn or wheat, or these same treatments with the addition of 0.8 kg of canola oil. In this 5-wk experiment, d 1 to 7 served as the covariate period, d 8 to 14 as the transition period, d 15 to 28 as the adaptation period, and d 29 to 35 as the experimental period. Cows were fed their full treatment diets from d 15 to 35 during which time milk production and feed intake were measured daily. During d 29 to 35, methane production was measured for individual cows daily using the sulfur hexafluoride tracer method. The resulting averages for milk production and feed intake were analyzed by analysis of covariance with factorial grain by fat as treatment structure, animal as the unit within blocks, and the corresponding milk production or feed intake covariate averages as principal covariate. Data on milk fatty acids, ruminal fluid data on pH, ammonia, volatile fatty acids, protozoa, and methane were analyzed by ANOVA using the same treatment and blocking structures excluding the principal covariate. Cows fed a diet containing wheat had greater MY than cows fed a diet containing corn. Irrespective of the type of grain in the diet, increasing the fat concentration from 2 to 6% dry matter reduced MY. It is concluded that the grain component in the basal diet does not affect the mitigating effects of dietary fat supplements on MY., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Background: There are several methods for estimating methane production (MP) from feedstuffs in vented in vitro systems. One method (A; 'gold standard') measures methane proportions in the incubation bottle's headspace (HS) and in the vented gas collected in gas bags. Four other methods (B, C, D and E) measure methane proportion in a single gas sample from the HS. Method B assumes the same methane proportion in the vented gas as in the HS, method C assumes constant methane to carbon dioxide ratio, method D has been developed based on empirical data, and method E assumes constant individual venting volumes. This study aimed to compare the MP predictions from these methods to that of the gold standard method under different incubation scenarios, to validate these methods based on their concordance with a gold-standard method., Results: Methods C, D and E had greater concordance (0.85, 0.88 and 0.81), lower root-mean-square error (RMSE; 0.80, 0.72 and 0.85) and lower mean bias (0.20, 0.35, -0.35) with the gold standard than did method B (concordance 0.67, RMSE 1.49 and mean bias 1.26). Methods D and E were simpler to perform than method C, and method D was slightly more accurate than method E., Conclusion: Based on precision, accuracy and simplicity of implementation, it is recommended that, when method A cannot be used, methods D and E are preferred to estimate MP from vented in vitro systems. © 2018 Society of Chemical Industry., (© 2018 Society of Chemical Industry.)

The fortification of processed foods including dairy products is increasingly commonplace with phytosterols among many compounds used to improve the nutritional value of food products. It is also increasingly common practice for some dairy cattle feeds to be fortified for their potential to increase phytosterol levels in milk. In this study, a combined, streamlined protocol using acid hydrolysis, saponification and sample clean-up was developed to enable the rapid and reliable measurement of phytosterols. The method was developed with focus on streamlining the overall technique to make it suitable for commercial laboratories, to reduce labor and consumable costs, while maintaining accuracy. A total of 12 different feed types commonly used in the dairy industry were analyzed with the highest and lowest sterol contents found in cotton seed oil and tannin with average phytosterol contents of 256 and <30 mg per 100 g, respectively. With a limit of reporting of 30 mg/kg for individual sterols and a correlation coefficient > 0.99, the method was validated for milk to enable feed comparison studies with respect to the total phytosterol content in raw milk., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Enteric methane (CH 4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation., (© 2018 John Wiley & Sons Ltd.)