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Abstract Background Sustainable strategies for enteric methane (CH4) mitigation of dairy cows have been extensively explored to improve production performance and alleviate environmental pressure. The present study aimed to investigate the effects of dietary xylooligosaccharides (XOS) and exogenous enzyme (EXE) supplementation on milk production, nutrient digestibility, enteric CH4 emissions, energy utilization efficiency of lactating Jersey dairy cows. Forty-eight lactating cows were randomly assigned to one of 4 treatments: (1) control diet (CON), (2) CON with 25 g/d XOS (XOS), (3) CON with 15 g/d EXE (EXE), and (4) CON with 25 g/d XOS and 15 g/d EXE (XOS + EXE). The 60-d experimental period consisted of a 14-d adaptation period and a 46-d sampling period. The enteric CO2 and CH4 emissions and O2 consumption were measured using two GreenFeed units, which were further used to determine the energy utilization efficiency of cows. Results Compared with CON, cows fed XOS, EXE or XOS + EXE significantly (P

Ligularia virgaurea is the most widely functional native herbage in the alpine meadow pastures of the Qinghai-Tibet Plateau (QTP) and has multiple pharmacological and biological activities. The effect of L. virgaurea as a dietary component on the digestion and metabolism of sheep was evaluated by conducting feeding trials in metabolic cages. Thirty-two Tibetan yearling rams (29 ± 1.56 kg BW) were randomly allotted to four groups included in a completely randomised design with eight animals per treatment. Sheep were fed a basal diet (freshly native pasture) without the addition of L. virgaurea (control) or with the addition of L. virgaurea (100, 200, or 300 mg/kg BW per day) for 45 days. Addition of L. virgaurea to the diet of Tibetan sheep was found to influence the average daily gain (quadratic [Q], P 0.05; Q, P 0.05; Q, P ≤ 0.001) were also affected by the dietary inclusion of L. virgaurea. Effects of L. virgaurea feeding were also witnessed on methane energy (CH4-E) (L, P = 0.029), gross energy (GE) (Q, P = 0.013), digestible energy (DE) (Q, P = 0.015), and metabolisable energy (ME) intake (Q, P = 0.015). Energy utilisation efficiency expressed as a proportion of GE intake (DE/GE intake, ME/GE intake, ME/DE intake, FE/GE intake, and CH4-E/GE intake) manifested quadratic changes (P

Abstract This study aims to compare the performance of multiple linear regression and machine learning algorithms for predicting manure nitrogen excretion in lactating dairy cows, and to develop new machine learning prediction models for MN excretion. Dataset used were collated from 43 total diet digestibility studies with 951 lactating dairy cows. Prediction models for MN were developed and evaluated using MLR technique and three machine learning algorithms, artificial neural networks, random forest regression and support vector regression. The ANN model produced a lower RMSE and a higher CCC, compared to the MLR, RFR and SVR model, in the tenfold cross validation. Meanwhile, a hybrid knowledge-based and data-driven approach was developed and implemented to selecting features in this study. Results showed that the performance of ANN models were greatly improved by the turning process of selection of features and learning algorithms. The proposed new ANN models for prediction of MN were developed using nitrogen intake as the primary predictor. Alternative models were also developed based on live weight and milk yield for use in the condition where nitrogen intake data are not available (e.g., in some commercial farms). These new models provide benchmark information for prediction and mitigation of nitrogen excretion under typical dairy production conditions managed within grassland-based dairy systems.

Compared to traditional herbage, functional native herbage is playing more important role in ruminant agriculture through improving digestion, metabolism and health of livestock; however, their effects on rumen microbial communities and hindgut fermentation are still not well understood. The objective of present study was to evaluate the effects of dietary addition of Allium mongolicum on bacterial communities in rumen and feces of claves. Sixteen 7-month-old male calves were randomly divided into four groups (n = 4). All calves were fed a basal ration containing roughage (alfalfa and oats) and mixed concentrate in a ratio of 60:40 on dry matter basis. In each group, the basal ration was supplemented with Allium mongolicum 0 (SL0), 200 (SL200), 400 (SL400), and 800 (SL800) mg/kg BW. The experiment lasted for 58 days. Rumen fluid and feces in rectum were collected, Rumen fluid and hindgut fecal were collected for analyzing bacterial community. In the rumen, Compared with SL0, there was a greater relative abundance of phylum Proteobacteria (p

ABSTRACT: Direct measurements of methane (CH4) from individual animals are difficult and expensive. Predictions based on proxies for CH4 are a viable alternative. Most prediction models are based on multiple linear regressions (MLR) and predictor variables that are not routinely available in commercial farms, such as dry matter intake (DMI) and diet composition. The use of machine learning (ML) algorithms to predict CH4 emissions from across-country heterogeneous data sets has not been reported. The objectives were to compare performances of ML ensemble algorithm random forest (RF) and MLR models in predicting CH4 emissions from proxies in dairy cows, and assess effects of imputing missing data points on prediction accuracy. Data on CH4 emissions and proxies for CH4 from 20 herds were provided by 10 countries. The integrated data set contained 43,519 records from 3,483 cows, with 18.7% missing data points imputed using k-nearest neighbor imputation. Three data sets were created, 3k (no missing records), 21k (missing DMI imputed from milk, fat, protein, body weight), and 41k (missing DMI, milk fat, and protein records imputed). These data sets were used to test scenarios (with or without DMI, imputed vs. nonimputed DMI, milk fat, and protein), and prediction models (RF vs. MLR). Model predictive ability was evaluated within and between herds through 10-fold cross-validation. Prediction accuracy was measured as correlation between observed and predicted CH4, root mean squared error (RMSE) and mean normalized discounted cumulative gain (NDCG). Inclusion of DMI in the model improved within and between-herd prediction accuracy to 0.77 (RMSE = 23.3%) and 0.58 (RMSE = 31.9%) in RF and to 0.50 (RMSE = 0.327) and 0.13 (RMSE = 42.71) in MLR, respectively than when DMI was not included in the predictive model. When missing DMI records were imputed, within and between-herd accuracy increased to 0.84 (RMSE = 18.5%) and 0.63 (RMSE = 29.9%), respectively. In all scenarios, RF models out-performed MLR models. Results suggest routinely measured variables from dairy farms can be used in developing globally robust prediction models for CH4 if coupled with state-of-the-art techniques for imputation and advanced ML algorithms for predictive modeling.

Abstract Previous work has demonstrated some benefit from alternative breeds in low-input dairying, although there has been no systematic analysis of the simultaneous effect of Jersey crossbreeding on productivity, health, fertility parameters or milk nutritional quality. This work aimed to understand the effects of, and interactions/interrelations between, dairy cow genotypes (Holstein-Friesian (HF), Holstein-Friesian × Jersey crossbreds (HF × J)) and season (spring, summer, autumn) on milk yield; basic composition; feed efficiency, health, and fertility parameters; and milk fatty acid (FA) profiles. Milk samples (n = 219) and breed/diet data were collected from 74 cows in four UK low-input dairy farms between March and October 2012. HF × J cows produced milk with more fat (+ 3.2 g/kg milk), protein (+ 2.9 g/kg milk) and casein (+ 2.7 g/kg milk); and showed higher feed, fat, and protein efficiency (expressed as milk, fat and protein outputs per kg DMI) than HF cows. Milk from HF × J cows contained more C4:0 (+ 2.6 g/kg FA), C6:0 (+ 1.9 g/kg FA), C8:0 (+ 1.3 g/kg FA), C10:0 (+ 3.0 g/kg FA), C12:0 (+ 3.7 g/kg FA), C14:0 (+ 4.6 g/kg FA) and saturated FA (SFA; + 27.3 g/kg milk) and less monounsaturated FA (MUFA; -23.7 g/kg milk) and polyunsaturated FA (− 22.3 g/kg milk). There was no significant difference for most health and fertility parameters, but HF × J cows had shorter calving interval (by 39 days). The superior feed, fat and protein efficiency of HF × J cows, as well as shorter calving interval can be considered beneficial for the financial sustainability of low-input dairy farms; and using such alternative breeds in crossbreeding schemes may be recommended. Although statistically significant, it is difficult to determine if differences observed between HF and HF × J cows in fat composition are likely to impact human health, considering average population dairy fat intakes and the relatively small difference. Thus, the HF × J cow could be used in low-input dairying to improve efficiency and productivity without impacting milk nutritional properties.

Rumen bloat is the most common digestive disorder in fattening ruminants, which is responsible for around 2–3 % of deaths in the ruminants industry and is therefore considered to be a serious threat to ruminant farming. The root cause of rumen bloat caused by feeding high concentrate dies would be attributed to the production of a large amount of stable foam during the fattening period. The exact mechanism of rumen foam formation has yet to be investigated. Proteins, polysaccharides and carboxylates derived from feed, and synthesized by microbes during the rumen fermentation may act as foaming agents or stabilizers in the formation progress of rumen foam. Supplementation of condensed tannins and other additives can be an effective way to prevent feedlot bloat induced by feeding high concentrate diets.

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

The objective of this study was to determine the effect of high-concentrate diets on the blood parameters and liver transcriptome of goats. Eighteen goats were allocated into three dietary treatments: the high level of concentrate (HC) group, the medium level of concentrate (MC) group, and the low level of concentrate (LC) group. The blood parameters and pathological damage of the gastrointestinal tract and liver tissues were measured. In hepatic portal vein blood, HC showed higher LPS, VFAs, and LA; in jugular vein blood, no significant differences in LPS, VFAs, and LA were recorded among groups (p > 0.05). Compared to the LC and MC groups, the HC group showed significantly increased interleukin (IL)-1β, IL-10, TNF-α, and diamine oxidase in jugular vein blood (p < 0.05). Liver transcriptome analysis discovered a total of 1269 differentially expressed genes (DEGs) among the three groups and most of them came from the HC vs. LC group. There were 333 DEGs up-regulated and 608 down-regulated in the HC group compared to the LC group. The gene ontology enrichment analysis showed that these DEGs were mainly focused on the regulation of triacylglycerol catabolism, lipoprotein particle remodeling, and cholesterol transport. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the liver of the HC group enhanced the metabolism of nutrients such as VFAs through the activation of AMPK and other signaling pathways and enhanced the clearance and detoxification of LPS by activating the toll-like receptor signaling pathway. A high-concentrate diet (HCD) can significantly promote the digestion of nutrients; the liver enhances the adaptability of goats to an HCD by regulating the expression of genes involved in nutrient metabolism and toxin clearance.

Interest in organic cows’ milk has increased due to the perceived superior nutritional quality and improved sustainability and animal welfare. However, there is a lack of simultaneous assessments on the influence of organic dairy practices and dietary and breed drivers on productivity, feed efficiency, health parameters, and nutritional milk quality at the herd level. This work aimed to assess the impact of organic vs. conventional management and month on milk yield and basic composition, herd feed efficiency, health parameters, and milk fatty acid (FA) composition. Milk samples (n = 800) were collected monthly from the bulk tanks of 67 dairy farms (26 organic and 41 conventional) between January and December 2019. Data on breed and feeding practices were gathered via farm questionnaires. The samples were analyzed for their basic composition and FA profile using Fourier transform infrared spectroscopy (FTIR) and gas chromatography (GC), respectively. The data were analyzed using a linear mixed model, repeated measures design and multivariate redundancy analysis (RDA). The conventional farms had higher yields (kg/cow per day) of milk (+7.3 kg), fat (+0.27 kg), and protein (+0.25 kg) and higher contents (g/kg milk) of protein, casein, lactose, and urea. The conventional farms produced more milk (+0.22 kg), fat (+8.6 g), and protein (+8.1 g) per kg offered dry matter (DM). The organic farms produced more milk per kg of offered non-grazing and concentrate DM offered, respectively (+0.5 kg and +1.23 kg), and fat (+20.1 g and +51 g) and protein (+17 g and +42 g). The organic milk had a higher concentration of saturated fatty acid (SFA; +14 g/kg total FA), polyunsaturated fatty acid (PUFA; +2.4 g/kg total FA), and nutritionally beneficial FA alpha linolenic acid (ALNA; +14 g/kg total FA), rumenic acid (RA; +14 g/kg total FA), and eicosapentaenoic acid (EPA; +14 g/kg total FA); the conventional milk had higher concentrations of monounsaturated FA (MUFA; +16 g/kg total FA). Although the conventional farms were more efficient in converting the overall diet into milk, fat, and protein, the organic farms showed better efficiency in converting conserved forages and concentrates into milk, fat, and protein as a result of reduced concentrate feeding. Considering the relatively small differences in the FA profiles between the systems, increased pasture intake can benefit farm sustainability without negatively impacting consumer nutrition and health.

Abstract Background Rumen microbiota in ruminants are vital for sustaining good rumen ecology, health, and productivity. Currently, limited information is available regarding the response of yaks (Bos grunniens) to fluctuating environments, especially the rumen microbiome. To address this, we investigated the diet, rumen bacterial community, and volatile fatty acids (VFA) of rumen fluid of yaks raised in the great Qinghai-Tibet plateau (QTP) at 2800 (low altitude, L), 3700 (middle altitude, M), and 4700 m (high altitude, H) above sea level. Results The results showed that despite a partial diet overlap, H yaks harbored higher fibrous fractious contents than the M and L grazing yaks. Bacteria including Christensenellaceae_R-7_group, Ruminococcus_1, Romboutsia, Alloprevotella, Eubacterium coprostanoligenes, Clostridium, Streptococcus, and Treponema were found to be enriched in the rumen of yaks grazing at H. They also showed higher rumen microbial diversity and total VFA concentrations than those shown by yaks at M and L. Principal coordinates analysis (PCoA) on weighted UniFrac distances revealed that the bacterial community structure of rumen differed between the three altitudes. Moreover, Tax4fun metagenome estimation revealed that microbial genes associated with energy requirement and carbohydrate metabolic fate were overexpressed in the rumen microbiota of H yaks. Conclusions Collectively, our results revealed that H yaks had a stronger herbage fermenting ability via rumen microbial fermentation. Their enhanced ability of utilizing herbage may be partly owing to a microbiota adaptation for more energy requirements in the harsh H environment, such as lower temperature and the risk of hypoxia.

Objective The 3×3 factorial arrangement was used to investigate if either high water-soluble carbohydrates (WSC) cultivars or suitable time of day that the grass cut could improve nutrient values and in vitro fermentation characteristics. Methods The 3 cultivars were mowed at 3 diurnal time points and included a benchmark WSC ryegrass cultivar ‘Premium’, and 2 high WSC cultivars AberAvon and AberMagic, which contained, on average, 157, 173, and 193 g/kg dry matter (DM) of WSC, and 36.0, 36.5, and 34.1 g/kg DM of N during 7th regrowth stage, respectively. The fermentation jars were run at 39°C with gas production recorded and sampled at 2, 5, 8, 11, 14, 17, 22, 28, 36, and 48 h. The rumen liquid was collected from 3 rumen fistulated cows grazing on ryegrass pasture. Results High WSC cultivars had significantly greater WSC content, in vitro DM digestibility (IVDMD) and total gas production (TGP), and lower lag time than Premium cultivar. Methane production for AberMagic cultivar containing lower N concentration was marginally lower than that for AberAvon and Premium cultivars. Grass cut at Noon or PM contained greater WSC concentration, IVDMD and TGP, and lower N and neutral detergent fiber (NDF) contents, but CH4 production was also increased, compared to grass cut in AM. Meanwhile, the effects of diurnal cutting time were influenced by cultivars, such as in vitro CH4 production for AberMagic was not affected by cutting time. The IVDMD and gas production per unit of DM incubated were positively related to WSC concentration, WSC/N and WSC/NDF, respectively, and negatively related to N and NDF concentrations. Conclusion These results imply either grass cut in Noon or PM or high WSC cultivars could improve nutrient values, IVDMD and in vitro TGP, and that AberMagic cultivar has a slightly lower CH4 production compared to AberAvon and Premium. Further study is necessary to determine whether the increase of CH4 production response incurred by shifting from AM cutting to Noon and/or PM cutting could be compensated for by high daily gain from increased WSC concentration and DM digestibility.

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

The Qinghai-Tibet Plateau is characterized by low temperatures and hypoxia, and this feature is more obvious in the winter. However, it is not clear how Tibetan sheep adapt to extreme cold climates. To address this, we used physiological methods combined with next-generation sequencing technology to explore the differences in growth performance, forage nutrient digestion, serum biochemical indexes, and rumen microbial communities of Tibetan sheep (Ovis aries) between the summer and winter. In the summer, owing to the high nutritional quality of the forage, the Tibetan sheep showed enhanced forage degradation and fermentation though increased counts of important bacteria in the rumen, such as Bacteroidetes, Prevotella_1, Prevotellaceae_UCG-003, Ruminococcus_1, Saccharofermentans, and Ruminococcaceae_UCG-014, to improve the growth performance and increase serum immunity and antioxidant status. In the winter, owing to the low nutritional quality of the forage, the Tibetan sheep presented low values of forage degradation and fermentation indicators. The relative abundance of Firmicutes, the Firmicutes/Bacteroidetes ratio, microbial diversity, interactive activity between microorganisms, and metabolism were significantly increased, implying that the rumen microbiota could promote the decomposition of forage biomass and the maintenance of energy when forage nutritional value was insufficient in the winter. Our study helps in elucidating the mechanism by which Tibetan sheep adapt to the high-altitude harsh environments, from the perspective of the rumen microbiota.

Objective This experiment was conducted to compare the structure and composition of ruminal microorganisms in goats with high and low neutral detergent fibre (NDF) digestibility. Methods Nineteen crossbred goats were used as experimental animals and fed the same total mixed rations during the 30-day pre-treatment and 6-day digestion trialperiods. All faeces were collected during the digestion period for measuring the NDF digestibility. Then, high and the low NDF digestibility individuals were chosen for the high NDF digestibility group (HFD) and low NDF digestibility group (LFD), respectively. Rumen contents were collected for total microbial DNA extraction. The V4 region of the bacterial 16S rRNA gene was amplified using universal primers of bacteria and sequenced using high-throughput sequencer. The sequences were mainly analysed by QIIME 1.8.0. Results A total of 18,694 operational taxonomic units were obtained, within 81.98% belonged to bacteria, 6.64% belonged to archaea and 11.38% was unassigned microorganisms. Bacteroidetes, Firmicutes, and Proteobacteria were the predominant microbial phyla in both groups. At the genus level, the relative abundance of fifteen microorganisms were significantly higher (p

The effect of dietary crude protein (CP) level on ammonia (NH3) emissions from slurry from lactating Holstein-Friesian cows was studied. Twenty-four-hour total collections of faeces and urine were made from 24 lactating Holstein-Friesian cows fed four total mixed rations containing 141, 151, 177, and 201 g CP/kg DM (6 cows/diet). The collected urine and faeces from each cow were combined to form 2 kg duplicate slurry samples (weight/weight; fresh basis) according to the proportions in which they were excreted. NH3 emissions from the slurry samples were measured, during 0–24 and 24–48 h intervals in six open-circuit respiration chambers maintained at two temperatures (8 or 18 °C). NH3 emissions for the 0–24 and 0–48 h intervals, as well as the average daily emissions, increased linearly with increasing dietary CP level. Increasing the temperature from 8 to 18 °C positively affected NH3 emissions, but only for the 0–24 h interval. In situations where direct measurements are impossible, NH3 emissions from slurry can be predicted accurately using equations based on dietary CP level supported by either urinary nitrogen, faeces nitrogen, or both. In summary, increasing dietary CP level linearly increased average daily NH3 emissions from slurry, with a 5.4 g increase for each 10 g increase in dietary CP.

Objective In dryland areas of China, alfalfa hay (AH) is a possible substitute for concentrate feed for beef cattle. To evaluate the potential benefits of this substitution, we studied the effect of the ratio of AH intake to total dry matter (DM) intake on average daily body-weight gain (ADG), dietary energy utilization status, and economic benefit in Gansu province. Methods In each of two feeding trials in 2016 (trial 1 [T1], July 3 to 17; trial 2 [T2], August 15 to September 23), crossbred male Simmental calves were allocated to low AH (LA), medium AH (MA), and high AH (HA) feeding groups (n = 4 per group). The target ADG was set as 1 kg for both trials. In a one-way-layout design based on conventional feeding practices in the province, calves received diets containing the different AH amounts, with a constant ratio of corn stover:total DM and decreasing rations of concentrate feed proportional to the increase in AH. Calves in T1 received AH at 15% (T1-LA), 23% (T1-MA), or 31% (T1-HA) of their dietary DM allowances; those in T2 received 9% (T2-LA), 24% (T2-MA), or 34% (T2-HA) AH. Results Among the T1 groups, both ADG and economic benefit were highest in T1-LA; whereas in T2, they were higher in the T2-LA and T2-MA groups than in T2-HA. Energy digestibility did not significantly differ among the groups in either trial. The dietary AH inclusion ratios of 14% in the warm season and 8% to 21% in the cool season appeared to yield optimal ADG, metabolizable energy intake, and economic benefit. Conclusion Low-level inclusion of AH, ranging from 8% to 21%, is a practical approach for beef cattle feeding. This modified feeding regimen likely will promote increased growth performance during the fattening stage of beef steers in dryland areas of Gansu province, China.

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

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

Agricultural production in Minqin Oasis, China, is commonly categorized as intensive crop production (ICP), integrated crop–livestock production (ICLP), intensive livestock production (confined feeding) (IFLP), and extensive livestock production (grazing) (EGLP). The objectives of the present study were to use a life cycle assessment technique to evaluate on-farm energy balances and greenhouse gas (GHG) emissions of agricultural production, and to compare the differences among the four systems. Data used in the present study were collected from published literature and face-to face questionnaires from 529 farms in eight towns (two towns per production system) within Minqin county. The ANOVA of averaged data from 2014 to 2015 indicated that the net energy ratio (Output/Input) for the EGLP system was significantly higher than that for any other system (P < 0.01), whereas the difference among other three systems were not significant. The EGLP system generated lower CO2-eq emissions per hectare of farmland than other systems (P < 0.01). Relating carbon economic efficiency to market values (US$) of agricultural products, indicated that the carbon economic efficiency (US$/kg CO2-eq) of the IFLP system was significantly greater than that of other systems (P < 0.01). The major GHG emission sources varied across the systems, that is, soil respiration is the dominant source in EGLP, while the main sources in IFLP are enteric methane and manure management; in ICLP major sources are enteric methane, soil respiration and fertilizer; and in ICP are soil respiration and fertilizer. The structural equation modelling analysis showed that livestock category was strongly linked to net income. The direct effects and total effects of water use efficiency, via its positive influence on energy balances and GHG emissions were much stronger than those of other dependent variables. The study provides important benchmark information to help develop sustainable agricultural production systems on energy balances and GHG emissions in northwestern China.

The effect of dietary crude protein (CP) level on intake, digestibility, milk production, and nitrogen (N) use efficiency was studied. Twenty-four Holstein-Friesian cows (17 multiparous and seven primiparous) were grouped by parity, days in milk, milk yield, and live weight into six blocks of four, and randomly assigned to four total mixed ration (TMR) treatments, containing 141, 151, 177, or 210 g CP/kg dry matter (DM), over 28 day experimental periods. Apparent total-tract DM and fiber digestibilities and milk fat composition were similar across treatments. Milk protein and urea-N compositions, and urinary and manure N excretion increased linearly, while milk N efficiency (MNE) decreased linearly with increasing CP. DM intake was highest with the 177 diet, while CP intake increased linearly with increasing CP, peaking at 200 g/kg DM. Milk yield increased with CP intake for the three lower CP levels, peaking at 176 g CP/kg DM. The further increase in CP level from 177 to 210 g/kg DM did not result in improved milk yield, but resulted in decreased milk N secretion and increased urinary N excretion. In summary, milk protein composition increased linearly with increasing CP, accompanied by a linear decrease in MNE, resulting in a bell-shaped relationship between milk yield and dietary CP level.

This study is targeted at evaluating whether C. deserticola addition promotes digestion, nitrogen and energy use, and methane production of sheep fed on fresh forage from alfalfa/tall fescue pastures. The sheep feeding trial was conducted with four addition levels with C. deserticola powder, and a basal diet of fresh alfalfa (Medicago sativa) and tall fescue (Festuca arundinacea). Addition levels of 4% and 6% improved average body weight gain (BWG) by 215.71 and 142.86 g/d, and feed conversion ratio (FCR) by 0.20 and 0.14, respectively. Digestibility of dry matter (DM), organic matter (OM), neutral detergent fiber (NDF), and ether extract (EE) was 62.25%, 65.18%, 58.75%, and 47.25% under the addition level of 2%, which is greater than that in the control group. C. deserticola addition improved energy utilization efficiency, while addition levels of 2% and 4% increased nitrogen intake and deposited nitrogen. Overall, C. deserticola has the potential to improve growth performance, digestion of sheep, so it has suitability to be used as a feed additive.

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

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

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

Vaccination through recombinant proteins against rumen methanogenesis provides a mitigation approach to reduce enteric methane (CH4) emissions in ruminants. The objective of present study was to evaluate the in vivo efficacy of a new vaccine candidate protein (EhaF) on methanogenesis and microbial population in the rumen of goats. We amplified the gene mru 1407 encoding protein EhaF using fresh rumen fluid samples of mature goats and successfully expressed recombinant protein (EhaF) in Escherichia coli Rosetta. This product was evaluated using 12 mature goats with half for control and other half injected with 400ug/goat the purified recombinant protein in day 1 and two subsequent booster immunizations in day 35 and 49. All measurements were undertaken from 63 to 68 days after the initial vaccination, with CH4 emissions determined using respiration calorimeter chambers. The results showed that the vaccination caused intensive immune responses in serum and saliva, although it had no significant effect on total enteric CH4 emissions and methanogen population in the rumen, when compared with the control goats. However, the vaccination altered the composition of rumen bacteria, especially the abundance of main phylum Firmicutes and genus Prevotella. The results indicate that protein EhaF might not be an effective vaccine to reduce enteric CH4 emissions but our vaccine have potential to influence the rumen ecosystem of goats.

Enteric methane (CH 4 ) is a by-product from fermentation of feed consumed by ruminants, which represents a nutritional loss and is also considered a contributor to climate change. The aim of this research was to use individual animal data from 17 published experiments that included sheep ( n = 288), beef cattle ( n = 71) and dairy cows ( n = 284) to develop an empirical model to describe enteric CH 4 emissions from both cattle and sheep, and then evaluate the model alongside equations from the literature. Data were obtained from studies in the United Kingdom (UK) and Australia, which measured enteric CH 4 emissions from individual animals in calorimeters. Animals were either fed solely forage or a mixed ration of forage with a compound feed. The feed intake of sheep was restricted to a maintenance amount of 875 g of DM per day (maintenance level), whereas beef cattle and dairy cows were fed to meet their metabolizable energy (ME) requirement (i.e., production level). A linear mixed model approach was used to develop a multiple linear regression model to predict an individual animal’s CH 4 yield (g CH 4 /kg dry matter intake) from the composition of its diet. The diet components that had significant effects on CH 4 yield were digestible organic matter (DOMD), ether extract (EE) (both g/kg DM) and feeding level above maintenance intake: CH 4 (g/kg DM intake) = 0.046 (±0.001) × DOMD − 0.113 (±0.023) × EE − 2.47 (±0.29) × (feeding level − 1), with concordance correlation coefficient ( CCC ) = 0.655 and RMSPE = 14.0%. The predictive ability of the model developed was as reliable as other models assessed from the literature. These components can be used to predict effects of diet composition on enteric CH 4 yield from sheep, beef and dairy cattle from feed analysis information.

The objective of this research is to experimentally evaluate the specific impact of a collaborative heat sink composed of gravity heat pipes (GHP) and pulsating heat pipes (PHP) on the thermal efficiency of LED light sources. The heat sink developed in this experiment is designed to improve the thermal management system, ensuring that LED operate within a safe temperature range, which is crucial as the performance of LED is directly affected by their junction temperature. An HPPHP collaborative heat sink was employed in the experiment, where PHP served as heat dissipating fins to enhance its thermal performance, while HP handles the majority of the heat transfer tasks. The results showed that under forced convection conditions, the HP-PHP collaborative heat sink can increase the maximum thermal power capacity of LED to 192 W. The HP-PHP collaborative heat sink can reduce the substrate’s temperature to below 70.5 °C in passive mode when the LED input power does not exceed 96 W. Additional experimental results show that the minimum thermal resistance of the collaborative heat sink is 0.19 K/W under natural- convection conditions, under forced convection conditions, this value drops to 0.15 K/W, which still lower than the non-collaborative heat sink. These results demonstrate that the contact thermal resistance between HP and PHP significantly enhances the thermal performance of the collaborative heat sink. Therefore, this collaborative type of heat sink is an effective method for cooling high power LED. [ABSTRACT FROM AUTHOR]