Full adoption of the most effective strategies to mitigate methane emissions by ruminants can help meet the 1.5 °C target by 2030 but not 2050.

To meet the 1.5 °C target, methane (CH4) from ruminants must be reduced by 11 to 30% by 2030 and 24 to 47% by 2050 compared to 2010 levels. A meta-analysis identified strategies to decrease product-based (PB; CH4 per unit meat or milk) and absolute (ABS) enteric CH4 emissions while maintaining or increasing animal productivity (AP; weight gain or milk yield). Next, the potential of different adoption rates of one PB or one ABS strategy to contribute to the 1.5 °C target was estimated. The database included findings from 430 peer-reviewed studies, which reported 98 mitigation strategies that can be classified into three categories: animal and feed management, diet formulation, and rumen manipulation. A random-effects meta-analysis weighted by inverse variance was carried out. Three PB strategies­namely, increasing feeding level, decreasing grass maturity, and decreasing dietary forage-to-concentrate ratio­decreased CH4 per unit meat or milk by on average 12% and increased AP by a median of 17%. Five ABS strategies­namely CH4 inhibitors, tanniferous forages, electron sinks, oils and fats, and oilseeds­decreased daily methane by on average 21%. Globally, only 100% adoption of the most effective PB and ABS strategies can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in CH4 due to increasing milk and meat demand. Notably, by 2030 and 2050, low- and middle-income countries may not meet their contribution to the 1.5 °C target for this same reason, whereas high-income countries could meet their contributions due to only a minor projected increase in enteric CH4 emissions.

LncRNA S100PBP promotes proliferation and steroid hormone synthesis of granulosa cells by sponging MiR-2285bc-BMPR2 in bovine.

In bovine follicular development, the proliferation of bovine granulosa cells (GCs) affect follicular selection, atresia, and cystic follicle formation. With the proliferation of GCs and secretion of steroid hormones, follicles develop further and increase in diameter. However, when cystic follicles appear on the ovaries, GCs stop proliferating, resulting in the reduction of GCs layer. In our previous study, the whole transcriptome sequencing revealed that Bone morphogenetic protein receptor 2 (BMPR2) was differentially expressed (DE) between cystic and normal follicular GCs. We speculated that lncRNA may act as ceRNA targeting miRNAs and then regulating the expression of BMPR2 and the function of GCs, thereby affecting follicular development and cyst formation. In this study, the results elucidated that lncRNA S100PBP (NONBTAT011846.2) directly bound miR-2285bc, which targeted in the BMPR2 3'-UTR. miR-2285bc suppresses GCs proliferation by downregulating BMPR2 expression. Furthermore, lncRNA S100PBP was silenced by small interfering RNA (siRNA), and lncRNA S100PBP regulated BMPR2 expression by sponging miR-2285bc investigated through cross-verification. When siRNA of lncRNA S100PBP was transfected into GCs, the results revealed similar molecular changes as those transfected with miR-2285bc mimics. Silencing lncRNA S100PBP or overexpressing miR-2285bc altered the expressions of some follicular development-related genes, which could be related to follicular cyst occurrence. In conclusion, our findings support that lncRNA S100PBP regulates the expression of BMPR2 through sponge miR-2285bc, promotes the proliferation of GCs, inhibits their apoptosis, and increases the synthesis and secretion of follicular steroid hormones, thus promoting the development of bovine follicles and potentially inhibiting the formation of follicular cysts.

Understanding potential opportunities and risks associated with feeding supplemental rumen available fats to mitigate enteric methane emissions in lactating dairy cows.

Supplemental dietary rumen available fats show promise as enteric methane (eCH4) mitigators for lactating dairy cows. However, concerns include variability in eCH4 response and possible negative effects on dairy cow performance. Successful implementation of this mitigation option requires better prediction of responses specifically to rumen available FA as well as understanding the modulating effects of other dietary and animal characteristics. Using meta-analytic and meta-regression techniques, 35 published studies with diet definition were used to assess changes in eCH4 emissions and lactation performance associated with supplemental fat, specific supplemental rumen available FA types, and other dietary characteristics. Enteric CH4 (g/d) was reduced by 3.77% per percentage unit of supplemental rumen available EE (RAEE). Supplemental rumen available PUFA (C18:2 and C18:3) and UFA (C18:1, C18:2, C18:3) mitigated eCH4 (g/d) emissions in dairy cows by 6.88 and 4.65% per percentage unit increase, respectively. The anti-methanogenic effects of PUFA, MUFA and MCFA increased with correspondingly greater basal dietary levels of each FA type. Higher rumen-degradable starch (RDS; > 18% DM) in the basal diet promoted greater reductions in eCH4 yield (eCH4/DMI, g/kg) with supplemental rumen available PUFA and UFA. Both milk fat percentage and yield (kg/d) were reduced with rumen available fat supplementation with a reduction of 7.8% and 6.0%, respectively, relative to control diets. Our results highlight the importance of determining basal levels of the rumen available FA before providing supplemental rumen available FA as an option for enteric eCH4 mitigation. Dairy nutritionists can use estimates generated from this analysis to predict changes in eCH4 emissions and dairy cow performance associated with dietary supplementation of rumen available EE and specific rumen available FA types for the purpose of eCH4 mitigation.

Effects of BAMBI on luteinized follicular granulosa cell proliferation and steroid hormone production in sheep.

Bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI) regulates mammalian ovarian follicle growth and maturation; however, its effect on luteinized granulosa cells (LGCs) in sheep ovarian follicles remains unknown. Here we explored the regulatory role of LGC functions and steroid hormone synthesis by BAMBI. Multiple sequence alignment revealed that the sheep BAMBI gene sequence was relatively conserved. Sheep LGCs were strongly positive for BAMBI. LGC proliferation increased when BAMBI was silenced and decreased when BAMBI was overexpressed. After BAMBI overexpression, the expression of CASP3, CASP8, CASP9, and BAX significantly increased, whereas that of BCL2 and the ratio of BCL2/BAX expression decreased. The opposite was observed after BAMBI silencing. CDKN1A, CCND1, and CCND2 were downregulated with BAMBI overexpression and upregulated with BAMBI silencing. Expression of steroid hormone-related genes (CYP11A1, STAR, and 3BHSD), except CYP19A1, significantly increased after BAMBI overexpression. Moreover, estrogen and progesterone secretion increased after BAMBI overexpression and decreased after BAMBI interference. The effect of the exogenous addition of bone morphogenetic protein 2 (BMP2) on GCs was similar to that of BAMBI overexpression. In conclusion, BAMBI can regulate the proliferation and steroid hormone synthesis of sheep LGCs, and BMP2 can affect LGCs as an activator of BAMBI. These findings provide a basis for further research on the physiological role of BAMBI.

A meta-analysis of effects of 3-nitrooxypropanol on methane production, yield, and intensity in dairy cattle.

Ruminants, particularly dairy and beef cattle, contribute to climate change through mostly enteric methane emissions. Several mitigating options have been proposed, including the feed additive 3-nitrooxypropanol (3-NOP). The objectives of this study were to explain the variability in the mitigating effect of 3-NOP and to investigate the interaction between diet composition and 3-NOP dose, using meta-analytical approaches. Data from 13 articles (14 experiments) met the selection criteria for inclusion in the meta-analysis, and 48 treatment means were used for the analysis. Mean differences were calculated as 3-NOP treatment mean minus control treatment mean and then expressed as a percentage of the control mean. Three types of models were developed: (1) one including 3-NOP dose, overall mean, and individual covariate; (2) a combination of neutral detergent fiber (NDF), 3-NOP dose, and overall mean; and (3) one selected model from all combinations of up to 5 covariates, which were compared using a leave-one-out cross validation method. Models including only 3-NOP dose resulted in a significant reduction of 32.7%, 30.9%, and 32.6% for CH4 production (g/d), yield (g/kg dry matter intake), and intensity (g/kg energy-corrected milk), respectively, at an average 3-NOP dose of 70.5 mg/kg dry matter (DM). The greater the NDF content in the diet, the lower the reduction efficiency for a given 3-NOP dose. For 10 g/kg DM increase in NDF content from its mean (329 g of NDF/kg of DM) the 3-NOP effect on CH4 production was impaired by 0.633%, the 3-NOP effect on CH4 yield by 0.647%, and the 3-NOP effect on CH4 intensity by 0.723%. The analysis based on leave-one-out cross validation showed an increase in NDF and crude fat content reduces efficacy of 3-NOP and an increase in 3-NOP dose increases efficacy. A 1% (10 g/kg) DM decrease in dietary NDF content from its mean may increase the efficacy of 3-NOP in reducing CH4 production by 0.915%. A 1% (10 g/kg DM) decrease in dietary crude fat content from its mean enhances the efficacy of 3-NOP on CH4 production by 3.080% at a given dose and NDF level. For CH4 yield, next to 3-NOP dose, dietary NDF content and dietary crude fat content were included in the selected model, but also dietary starch content with an opposite direction to NDF and crude fat. The effect of 3-NOP dose on CH4 intensity was similar to its effect on CH4 production, whereas the effect of dietary NDF content was slightly lower. Expanding the previously published models with the newly available data published from trials since then improved model performance, hence demonstrating the value of regularly updating meta-analyses if a wider range of data becomes available.

Smoothing spline assessment of the accuracy of enteric hydrogen and methane production measurements from dairy cattle using various sampling schemes.

Estimating daily enteric hydrogen (H2) and methane (CH4) emitted from dairy cattle using spot sampling techniques requires accurate sampling schemes. These sampling schemes determine the number of daily samplings and their intervals. This simulation study assessed the accuracy of daily H2 and CH4 emissions from dairy cattle using various sampling schemes for gas collection. Gas emission data were available from a crossover experiment with 28 cows fed twice daily at 80% to 95% of the ad libitum intake, and an experiment that used a repeated randomized block design with 16 cows twice daily fed ad libitum. Gases were sampled every 12 to 15 min for 3 consecutive days in climate respiration chambers. Feed was fed in 2 equal portions per day in both experiments. Per individual cow-period combination, generalized additive models were fitted to all diurnal H2 and CH4 emission profiles. Per profile, the models were fitted using the generalized cross-validation, REML, REML while assuming correlated residuals, and REML while assuming heteroscedastic residuals. The areas under the curve (AUC) of these 4 fits were numerically integrated over 24 h to compute the daily production and compared with the mean of all data points, which was considered the reference. Next, the best of the 4 fits was used to evaluate 9 different sampling schemes. This evaluation determined the average predicted values sampled at 0.5, 1, and 2 h intervals starting at 0 h from morning feeding, at 1 and 2 h intervals starting at 0.5 h from morning feeding, at 6 and 8 h intervals starting at 2 h from morning feeding, and at 2 unequally spaced intervals with 2 or 3 samples per day. Sampling every 0.5 h was needed to obtain daily H2 productions not different from the selected AUC for the restricted feeding experiment, whereas less frequent sampling had predictions varying from 47% to 233% of the AUC. For the ad libitum feeding experiment, sampling schemes had H2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH4 production needed samplings every 2 h or shorter, or 1 h or shorter, depending on sampling time after feeding, whereas sampling scheme did not affect CH4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H2 production, particularly with restricted feeding, whereas daily CH4 production was less severely affected by sampling scheme.

Neddylation inactivation affects cell cycle and apoptosis in sheep follicular granulosa cells.

Protein neddylation inactivation is a novel topic in cancer research. However, there are few studies on the mechanism of neddylation underlying the development of sheep follicular granulosa cells (GCs). In this study, the development of follicular GCs in sheep was inactivated by MLN4924, a neddylation-specific inhibitor, which significantly attenuated the proliferation and cell index of sheep follicular GCs. Further, the inactivation of neddylation by MLN4924 caused the accumulation of the cullin ring ligase (CRLs) substrates Wee1 and c-Myc, which could upregulate NOXA protein expression. Meanwhile, the B-cell lymphoma/leukemia 2 (BCL2) family members Bcl-2 and MCL-1 were downregulated, subsequently inducing apoptosis in follicular GCs of sheep. Increasing Wee1 levels caused G2/M-phase arrest. The effects of neddylation inactivation on Akt, the JAK2/STAT3 signaling pathway, and Forkhead box class O(FOXO) family members were evaluated. Neddylation inactivation by MLN4924 increased the levels of phospho-Akt, JAK2, phospho-STAT3, and FOXO1 (p < 0.05) and decreased the levels of phospho-FOXO3a and STAT3 (p < 0.05). In addition, MLN4924 could alter the mitochondrial morphology of GCs, increase cellular glucose utilization and lactate production, increase reactive oxygen species (ROS) generation, and promote sheep follicular GCs glycolysis, thus causing changes in mitochondrial functions. Together, these findings point to an unrecognized role of neddylation in regulating follicular GCs proliferation in sheep.

Invited review: Current enteric methane mitigation options.

Ruminant livestock are an important source of anthropogenic methane (CH4). Decreasing the emissions of enteric CH4 from ruminant production is strategic to limit the global temperature increase to 1.5°C by 2050. Research in the area of enteric CH4 mitigation has grown exponentially in the last 2 decades, with various strategies for enteric CH4 abatement being investigated: production intensification, dietary manipulation (including supplementation and processing of concentrates and lipids, and management of forage and pastures), rumen manipulation (supplementation of ionophores, 3-nitrooxypropanol, macroalgae, alternative electron acceptors, and phytochemicals), and selection of low-CH4-producing animals. Other enteric CH4 mitigation strategies are at earlier stages of research but rapidly developing. Herein, we discuss and analyze the current status of available enteric CH4 mitigation strategies with an emphasis on opportunities and barriers to their implementation in confined and partial grazing production systems, and in extensive and fully grazing production systems. For each enteric CH4 mitigation strategy, we discuss its effectiveness to decrease total CH4 emissions and emissions on a per animal product basis, safety issues, impacts on the emissions of other greenhouse gases, as well as other economic, regulatory, and societal aspects that are key to implementation. Most research has been conducted with confined animals, and considerably more research is needed to develop, adapt, and evaluate antimethanogenic strategies for grazing systems. In general, few options are currently available for extensive production systems without feed supplementation. Continuous research and development are needed to develop enteric CH4 mitigation strategies that are locally applicable. Information is needed to calculate carbon footprints of interventions on a regional basis to evaluate the impact of mitigation strategies on net greenhouse gas emissions. Economically affordable enteric CH4 mitigation solutions are urgently needed. Successful implementation of safe and effective antimethanogenic strategies will also require delivery mechanisms and adequate technical support for producers, as well as consumer involvement and acceptance. The most appropriate metrics should be used in quantifying the overall climate outcomes associated with mitigation of enteric CH4 emissions. A holistic approach is required, and buy-in is needed at all levels of the supply chain.

Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database.

Enteric methane (CH4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH4 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 CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 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 CH4 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 CH4 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 CH4 emission conversion factors for specific regions are required to improve CH4 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 CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

Models for predicting enteric methane emissions from dairy cows in North America, Europe, and Australia and New Zealand.

There are several models in the literature for predicting enteric methane (CH4 ) emissions. These models were often developed on region or country-specific data and may not be able to predict the emissions successfully in every region. The majority of extant models require dry matter intake (DMI) of individual animals, which is not routinely measured. The objectives of this study were to (i) evaluate performance of extant models in predicting enteric CH4 emissions from dairy cows in North America (NA), Europe (EU), and Australia and New Zealand (AUNZ) and (ii) explore the performance using estimated DMI. Forty extant models were challenged on 55, 105, and 52 enteric CH4 measurements (g per lactating cow per day) from NA, EU, and AUNZ, respectively. The models were ranked using root mean square prediction error as a percentage of the average observed value (RMSPE) and concordance correlation coefficient (CCC). A modified model of Nielsen et al. (Acta Agriculturae Scand Section A, 63, 2013 and 126) using DMI, and dietary digestible neutral detergent fiber and fatty acid contents as predictor variables, were ranked highest in NA (RMSPE = 13.1% and CCC = 0.78). The gross energy intake-based model of Yan et al. (Livestock Production Science, 64, 2000 and 253) and the updated IPCC Tier 2 model were ranked highest in EU (RMSPE = 11.0% and CCC = 0.66) and AUNZ (RMSPE = 15.6% and CCC = 0.75), respectively. DMI of cows in NA and EU was estimated satisfactorily with body weight and fat-corrected milk yield data (RMSPE < 12.0% and CCC > 0.60). Using estimated DMI, the Nielsen et al. (2013) (RMSPE = 12.7 and CCC = 0.79) and Yan et al. (2000) (RMSPE = 13.7 and CCC = 0.50) models still predicted emissions in respective regions well. Enteric CH4 emissions from dairy cows can be predicted successfully (i.e., RMSPE < 15%), if DMI can be estimated with reasonable accuracy (i.e., RMSPE < 10%).

Nutritional and Environmental Effects on Ammonia Emissions from Dairy Cattle Housing: A Meta-Analysis.

Nitrogen excreted in dairy manure can be potentially transformed and emitted as NH, which can create livestock and human respiratory problems and be an indirect source of NO. The objectives of this study were to: (i) investigate environmental factors influencing NH emissions from dairy housing; and (ii) identify key explanatory variables in the NH emissions prediction from dairy housing using a meta-analytical approach. Data from 25 studies were used for the preliminary analysis, and data from 10 studies reporting 87 treatment means were used for the meta-analysis. Season and flooring type significantly affected NH emissions. For nutritional effect analysis, the between-study variability (heterogeneity) of mean NH emission was estimated using random-effect models and had a significant effect ( < 0.01). Therefore, random-effect models were extended to mixed-effect models to explain heterogeneity regarding the available dietary and animal variables. The final mixed-effect model included milk yield, dietary crude protein, and dry matter intake separately, explaining 45.5% of NH emissions heterogeneity. A unit increase in milk yield (kg d) resulted in a 4.9 g cow d reduction in NH emissions, and a unit increase in dietary crude protein content (%) and dry matter intake (kg d) resulted in 10.2 and 16.3 g cow d increases in NH emissions, respectively, in the scope of this study. These results can be further used to help identify mitigation strategies to reduce NH emissions from dairy housing by developing predictive models that could determine variables with strong association with NH emissions.

Prediction of enteric methane emissions from cattle.

Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle.

Retrospective analysis of the main feedstocks for animal feed in the world: How the green revolution has affected their environmental performance over the last 60 years, from 1961 to 2021.

At the end of the 1950s, studies began to create high-yield cultivars with the aim of increasing the supply of basic foods in the world, this action was called "green evolution". It was associated with the increase in the use of inputs to increase production levels, leading agriculture to a possible increase in environmental impacts and "harmful habits" of management. To characterize the historical damage of this action, it is necessary to use methods that generate universal results, capable of representing the world. Then, we use Life cycle assessment (LCA) to estimate the historical evolution of the environmental impacts of the two main feedstock for feed in the world, soybeans, and corn, from 1961 to 2021. To better understand the variation in their impacts, we consider the change in agricultural management when we use as a functional unit the amount of area needed to produce 1 kg of grain. Although emissions and impacts from agriculture, by area, have increased each decade, when considering productivity through the area/production ratio, we note that a number of emissions were avoided, along with impacts in all categories evaluated. Therefore, the development and use of technologies that modify the area/production ratio can contribute to avoiding environmental impacts.

Notch2 Regulates the Function of Bovine Follicular Granulosa Cells via the Wnt2/ß-Catenin Signaling Pathway.

Ovarian follicular GCs are strongly implicated in the growth, development, and atresia of ovarian follicles. The Wnt/ß-catenin and Notch signaling pathways participate in GC proliferation, differentiation, apoptosis, and steroid hormone production during follicular development. However, the crosstalk between Wnt and Notch signaling in GCs remains unclear. This study investigated this crosstalk and the roles of these pathways in apoptosis, cell cycle progression, cell proliferation, and steroid hormone secretion in bovine follicular GCs. The interaction between ß-catenin and Notch2 in GCs was assessed by overexpressing CTNNB1, which encodes ß-catenin. The results showed that inhibiting the Notch pathway by Notch2 silencing in GCs arrested the cell cycle, promoted apoptosis, reduced progesterone (P4) production, and inhibited the Wnt2-mediated Wnt/ß-catenin pathway in GCs. IWR-1 inhibited Wnt2/ß-catenin and Notch signaling, reduced GC proliferation, stimulated apoptosis, induced G1 cell cycle arrest, and reduced P4 production. CTNNB1 overexpression had the opposite effect and increased 17ß-estradiol (E2) production and Notch2 protein expression. Co-immunoprecipitation assays revealed that Notch2 interacted with ß-catenin. These results elucidate the crosstalk between the Wnt/ß-catenin and Notch pathways and the role of these pathways in bovine follicular GC development.

Models to predict nitrogen excretion from beef cattle fed a wide range of diets compiled from South America.

The objective of this meta-analysis was to develop and evaluate models for predicting nitrogen (N) excretion in feces, urine, and manure in beef cattle in South America. The study incorporated a total of 1,116 individual observations of N excretion in feces and 939 individual observations of N excretion in feces and in urine (g/d), representing a diverse range of diets, animal genotypes, and management conditions in South America. The dataset also included data on dry matter intake (DMI; kg/d) and nitrogen intake (NI; g/d), concentrations of dietary components, as well as average daily gain (ADG; g/d) and average body weight (BW; kg). Models were derived using linear mixed-effects regression with a random intercept for the study. Fecal N excretion was positively associated with DMI, NI, nonfibrous carbohydrates, average BW, and ADG and negatively associated with EE and CP concentration in the diet. The univariate model predicting fecal N excretion based on DMI (model 1) performed slightly better than the univariate model, which used NI as a predictor variable (model 2) with a root mean square error (RMSE) of 38.0 vs. 39.2%, the RMSE-observations SD ratio (RSR) of 0.81 vs. 0.84, and concordance correlation coefficient (CCC) of 0.53 vs. 0.50, respectively. Models predicting urinary N excretion were less accurate than those derived to predict fecal N excretion, with an average RMSE of 43.7% vs. 37.0%, respectively. Urinary and manure N excretion were positively associated with DMI, NI, CP, average BW, and ADG and negatively associated with neutral detergent fiber concentration in the diet. As opposed to fecal N excretion, the univariate model predicting urinary N excretion using NI (model 10) performed slightly better than the univariate model using DMI (model 9) as predictor variable with an RMSE of 36.0% vs. 39.7%, RSR 0.85 vs. 0.93, and CCC of 0.43 vs. 0.29, respectively. The models developed in this study are applicable for predicting N excretion in beef cattle across a broad spectrum of dietary compositions and animal genotypes in South America. The univariate model using DMI as a predictor is recommended for fecal N prediction, while the univariate model using NI is recommended for predicting urinary and manure N excretion because the use of more complex models resulted in little to no benefits. However, it may be more useful to consider more complex models that incorporate nutrient intakes and diet composition for decision-making when N excretion is a factor to be considered. Three extant equations evaluated in this study have the potential to be used in tropical conditions typical of South America to predict fecal N excretion with good precision and accuracy. However, none of the extant equations are recommended for predicting urine or manure N excretion because of their high RMSE, and low precision and accuracy.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows.

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Carbon footprint of South Dakota dairy production system and assessment of mitigation options.

Livestock production contributes to greenhouse gas (GHG) emissions. However, there is a considerable variability in the carbon footprint associated with livestock production. Site specific estimates of GHG emissions are needed to accurately focus GHG emission reduction efforts. A holistic approach must be taken to assess the environmental impact of livestock production using appropriate geographical scale. The objective of this study was to determine baseline GHG emissions from dairy production in South Dakota using a life cycle assessment (LCA) approach. A cradle-to-farm gate LCA was used to estimate the GHG emissions to produce 1 kg of fat and protein corrected milk (FPCM) in South Dakota. The system boundary was divided into feed production, farm management, enteric methane, and manure management as these activities are the main contributors to the overall GHG emissions. The production of 1 kg FPCM in South Dakota dairies was estimated to emit 1.23 kg CO2 equivalents. The major contributors were enteric methane (46%) and manure management (32.7%). Feed production and farm management made up 14.1 and 7.2%, respectively. The estimate is similar to the national average but slightly higher than the California dairy system. The source of corn used in the dairies influences the footprint. For example, South Dakota corn had fewer GHG emissions than grain produced and transported in from Iowa. Therefore, locally and more sustainably sourced feed input will contribute to further reducing the environmental impacts. Improvements in efficiency of milk production through better genetics, nutrition animal welfare and feed production are expected to further reduce the carbon footprint of South Dakota dairies. Furthermore, anaerobic digesters will reduce emissions from manure sources.

MNQ derivative D21 protects against LPS-induced inflammatory damage in bovine ovarian follicular GCs in vitro via the steroid biosynthesis signaling pathway.

Bacterial infections of the reproductive system of dairy cows lead to inflammation, and lipopolysaccharide (LPS) of the cell wall of Gram-negative bacteria is the main pathogenic component of inflammation. LPS inhibits follicular growth and development and alters the expression of follicular granulosa cells (GCs) genes in the ovary, leading to their functional disorders. Naphthoquinones have anti-inflammatory effects. In this experiment, 2-methoxy-1,4-naphthoquinone (MNQ), an extract of Impatiens balsamina L, and its derivative D21 were used to eliminate the inflammatory response of GCs exposed to LPS in vitro and to restore functional disorders in GCs. The anti-inflammatory effects of the two compounds were compared and their mechanism of action was investigated. The cytotoxicity of MNQ and its derivative D21 on follicular GCs was determined by MTT method. The relative expression of inflammatory factors and steroid synthesis-related genes were determined by qRT-PCR. The protective effects of MNQ and D21 on cellular inflammatory damage were observed by TEM. ELISA were performed to detect the levels of estradiol (E2) and progesterone (P4) in the culture supernatant. The expression of differential genes was analyzed by RNA-seq, and GO and KEGG enrichment analysis of differential genes were performed to investigate the mechanism of anti-inflammatory effect of D21. The results showed that the maximum no-cytotoxic concentrations of MNQ and D21 acting on GCs for 12 h were 4 µM and 64 µM, respectively. LPS concentration of 10 µg/mL had little effect on the survival of follicular GCs, but the relative expressions of IL-6, IL-1ß and TNF-α were significantly higher (P < 0.05). The results of qRT-PCR, ELISA and TEM observations showed that the anti-inflammatory effect of D21 was stronger than that of MNQ. RNA-seq analysis revealed a total of 341 differential genes between the LPS vs CK group (Control group) and the D21+L vs LPS group, which were mainly enriched in signaling pathways such as steroid biosynthesis. Nine genes in this signaling pathway were analyzed, and the RNA-seq and qRT-PCR results were found to be basically consistent. In this study, we confirmed that derivative D21 has stronger in vitro anti-inflammatory effects and better efficacy in protecting bovine follicular GCs from inflammatory damage than MNQ and acts through the steroid biosynthesis signaling pathway.

Protective effects of MNQ against Lipopolysaccharide-induced inflammatory damage in bovine ovarian follicular granulosa cells in Vitro.

Inflammation of the reproductive tract in dairy cows lead to functional disorders of follicular granulosa cells (GCs) in mammalian ovaries resulting in infertility and serious losses to the livestock industry. Lipopolysaccharide (LPS) can induce an inflammatory response in follicular granulosa cells in vitro. The aim of this study was to investigate the cellular regulatory mechanism of MNQ (2-methoxy-1,4-naphthoquinone) on eliminating the inflammatory response and restoring normal functions for bovine ovarian follicular GCs cultured in vitro exposed to LPS. The cytotoxicity of MNQ and LPS on GCs were detected by MTT method to determine the safe concentration. The relative expression of inflammatory factors and steroid synthesis-related genes were detected by qRT-PCR. The concentration of steroid hormones in the culture broth were detected by ELISA. Differential gene expressions were analyzed by RNA-seq. There were no toxic effects on GCs at MNQ and LPS concentrations of less than 3 µM and 10 µg/mL, respectively and treated in 12 h. The relative expressions of IL-6, IL-1ß and TNF-α were significantly higher in the LPS group compared with the CK group when GCs cultured in vitro were treated with the above concentrations and times (P < 0.05), but significantly lower in the MNQ+LPS group compared with the LPS group (P < 0.05). The levels of E2 and P4 in the culture solution were significantly reduced in the LPS group compared to the CK group (P < 0.05), and restored in the MNQ+LPS group. The relative expressions of CYP19A1, CYP11A1, 3ß-HSD, and STAR were significantly decreased in the LPS group compared with the CK group (P < 0.05), while the MNQ+LPS group also recovered to some extent. There were 407 differential genes shared by LPS vs CK and MNQ+LPS vs LPS by RNA-seq analysis, which were mainly enriched in steroid biosynthesis and TNF signaling pathway. We screened 10 genes for analysis and found consistent results for RNA-seq and qRT-PCR. In this study, we confirmed the protective effect of MNQ, an extract from Impatiens balsamina L, on LPS-induced inflammatory responses in bovine follicular granulosa cells in vitro as well as functional damage, and acted through steroid biosynthesis and TNF signaling pathways.

Rumen microbial degradation of bromoform from red seaweed (Asparagopsis taxiformis) and the impact on rumen fermentation and methanogenic archaea.

BACKGROUND: The red macroalgae Asparagopsis is an effective methanogenesis inhibitor due to the presence of halogenated methane (CH4) analogues, primarily bromoform (CHBr3). This study aimed to investigate the degradation process of CHBr3 from A. taxiformis in the rumen and whether this process is diet-dependent. An in vitro batch culture system was used according to a 2 × 2 factorial design, assessing two A. taxiformis inclusion rates [0 (CTL) and 2% DM diet (AT)] and two diets [high-concentrate (HC) and high-forage diet (HF)]. Incubations lasted for 72 h and samples of headspace and fermentation liquid were taken at 0, 0.5, 1, 3, 6, 8, 12, 16, 24, 48 and 72 h to assess the pattern of degradation of CHBr3 into dibromomethane (CH2Br2) and fermentation parameters. Additionally, an in vitro experiment with pure cultures of seven methanogens strains (Methanobrevibacter smithii, Methanobrevibacter ruminantium, Methanosphaera stadtmanae, Methanosarcina barkeri, Methanobrevibacter millerae, Methanothermobacter wolfei and Methanobacterium mobile) was conducted to test the effects of increasing concentrations of CHBr3 (0.4, 2, 10 and 50 µmol/L). RESULTS: The addition of AT significantly decreased CH4 production (P = 0.002) and the acetate:propionate ratio (P = 0.003) during a 72-h incubation. The concentrations of CHBr3 showed a rapid decrease with nearly 90% degraded within the first 3 h of incubation. On the contrary, CH2Br2 concentration quickly increased during the first 6 h and then gradually decreased towards the end of the incubation. Neither CHBr3 degradation nor CH2Br2 synthesis were affected by the type of diet used as substrate, suggesting that the fermentation rate is not a driving factor involved in CHBr3 degradation. The in vitro culture of methanogens showed a dose-response effect of CHBr3 by inhibiting the growth of M. smithii, M. ruminantium, M. stadtmanae, M. barkeri, M. millerae, M. wolfei, and M. mobile. CONCLUSIONS: The present work demonstrated that CHBr3 from A. taxiformis is quickly degraded to CH2Br2 in the rumen and that the fermentation rate promoted by different diets is not a driving factor involved in CHBr3 degradation.