The effects of improved performance in the U.S. dairy cattle industry on environmental impacts between 2007 and 2017

Fifty years of environmental progress for United States dairy farms

Dairy farms in the United States have changed in many ways over the past 50 yr. Milk production efficiency has increased greatly, with ∼30% fewer cows producing about twice the amount of milk today. Other improvements include increases in crop yields, fuel efficiency of farm equipment, and efficiency in producing most resources used on farms (e.g. electricity, fuel, fertilizer). These improvements have led to changes in the environmental impact of farms. Through simulation of representative dairy farms in 1971 and 2020, changes in nutrient losses and farmgate life cycle assessments of greenhouse gas (GHG) emissions, fossil energy use, and blue (ground and surface) water use were determined for 6 regions and the United States. For all environmental metrics studied, intensities expressed per unit of fat- and protein-corrected milk produced were reduced, but the total effects over all farms or milk produced increased for 5 of the 13 environmental metrics. Reductions in the impacts of dairy farms in the eastern United States were offset by large increases in western regions because of a major increase in cow numbers in the West. The national average intensity of GHG emissions decreased by 42%, which gave just a 14% increase in the total GHG emissions of all dairy farms over the 50-yr period. The intensity of fossil energy use decreased by 54%, with the total for all farms decreasing by 9%. Water use related to milk production decreased in intensity by 28%, but due to the large increase in dairy production in the dry western regions that have a greater dependence on irrigated feed crops, total blue water use increased by 42%. Major pathways of nitrogen loss included ammonia volatilization, leaching, and denitrification, where total ammonia emissions related to US dairy farms increased by 29%, while leaching losses decreased by 39%, with little change in nitrous oxide emissions. Simulated nitrogen and phosphorus runoff losses totaled for all dairy farms decreased by 27% to 51% through more efficient fertilizer use, reduced tillage, and greater use of cover crops. Emissions of methane and reactive non-methane volatile organic compounds increased by 32% and 53%, respectively, due to greater use of long-term manure storage and silage stored in bunkers and piles. Although much progress has been made in improving production efficiency, continued improvements with new strategies and technologies are needed to meet the demand for dairy products and mitigate total environmental impacts, particularly in view of projected climate variability.

Dry matter intake in US Holstein cows: exploring the genomic and phenotypic impact of milk components and body weight composite

Large data sets allow estimating feed required for individual milk components or body maintenance. Phenotypic regressions are useful for nutrition management, but genetic regressions are more useful in breeding programs. Dry matter intake (DMI) records from 8,513 lactations of 6,621 Holstein cows were predicted from phenotypes or genomic evaluations for milk components and body size traits. The mixed models also included days in milk, age-parity subclass, trial date, management group, and body weight change during 28- and 42-d feeding trials in mid-lactation. Phenotypic regressions of DMI on milk (0.014 ± 0.006), fat (3.06 ± 0.01), and protein (4.79 ± 0.25) were much less than corresponding genomic regressions (0.08 ± 0.03, 11.30 ± 0.47, and 9.35 ± 0.87) or sire genomic regressions multiplied by 2 (0.048 ± 0.04, 6.73 ± 0.94, and 4.98 ± 1.75). Thus, marginal feed costs as fractions of marginal milk revenue were higher from genetic than phenotypic regressions. According to the energy-corrected milk formula, fat production requires 69% more DMI than protein production. In the phenotypic regression, it was estimated that protein production requires 56% more DMI than fat. However, the genomic regression for the animal showed a difference of only 21% more DMI for protein compared with fat, while the sire genomic regressions indicated approximately 35% more DMI for fat than protein. Estimates of annual maintenance in kg DMI / kg body weight/lactation were similar from phenotypic regression (5.9 ± 0.14), genomic regression (5.8 ± 0.31), and sire genomic regression multiplied by 2 (5.3 ± 0.55) and are larger than those estimated by NASEM (2021) based on NEL equations. Multiple regressions on genomic evaluations for the 5 type traits in body weight composite (BWC) showed that strength was the type trait most associated with body weight and DMI, agreeing with the current BWC formula, whereas other traits were less useful predictors, especially for DMI. The Net Merit formula used to weight different genetic traits to achieve an economically optimal overall selection response was revised in 2021 to better account for these estimated regressions. To improve profitability, breeding programs should select smaller cows with negative residual feed intake that produce more milk, fat, and protein.

Genetic analysis of lactation consistency in US Holsteins using temporal variation in daily milk weights

The ability of a dairy cow to perform reliably over time is an interesting trait to include in dairy cattle breeding programs aimed at improving dairy cow resilience. Consistency, defined as the quality of performing as expected each day of the lactation, could be highly associated with resilience, defined as animal's ability to maintain health and performance in the presence of environmental challenges, including pathogens, heat waves, and nutritional changes. A total of 51,415,022 daily milk weights collected from 2018 to 2023 were provided for 255,191 multiparous Holstein cows milked 3 times daily in conventional parlor systems on farms in 32 states. The temporal variance (TEMPVAR) of milk yield from 5 to 305 d postpartum was computed as the log-transformed variance of daily deviations between observed and expected individual milk weights. Lower values of TEMPVAR imply smaller day-to-day deviations from expectations, indicating consistent performance, whereas larger values indicate inconsistent performance. Expected daily milk weights were computed using 3 nonparametric and parametric regression models: (1) loceally estimated scatterplot smoothing regression with a 0.75 span; (2) polynomial quantile regression using the median (0.5 quantile), and (3) polynomial quantile regression using a 0.7 quantile. The univariate statistical model included age at first calving and herd-year-season as fixed effects and cow as a random effect. Heritability estimates (standard errors) of TEMPVAR phenotypes calculated over the entire lactation ranged between 0.227 (0.011) and 0.237 (0.011), demonstrating that cows are genetically predisposed to display consistent or inconsistent performance. Estimated genetic correlations calculated using a multiple-trait model between TEMPVAR traits and between lactations were high (>0.95), indicating TEMPVAR is repeatable across lactations and robust to the model used to compute expected daily milk yield. Higher TEMPVAR phenotypes reflect more variation in performance, hence greater inconsistency, which is undesirable. Therefore, correlations between predicted transmitting abilities (PTA) for TEMPVAR and milk yield of 0.57 indicate that high-producing cows exhibit more day-to-day variation in performance. Correlations with productive life and livability were -0.38 and -0.48, respectively. Correlations between PTA for TEMPVAR and those of postpartum health traits were also negative, ranging from -0.41 to -0.08. Given that health traits are derived from disease resistance measurements, and higher health trait PTA are preferred, our results indicate that more consistent cows tend to have fewer health problems and greater longevity. Overall, our findings suggest that temporal variation in daily milk weights can be used to identify consistent animals that maintain expected performance throughout the lactation, which will enable selection for greater resilience to management and environmental perturbations.

Describing the distribution type of DM intake for dairy cow pens based on pen characteristics

In practice, cows are fed by pen, but a diet is formulated to the nutrient requirements of a single cow. If the DM intake (DMI) of a pen were equal for all cows, this approach would have no error, but cows are grouped into pens on pregnancy and other management factors creating a distribution of DMI. The goal of precision feeding is to meet the requirements of individual animals to increase efficiency and reduce environmental impact but is not achieved when a group is fed as if the individuals have uniform requirements and the DMI distribution is not normal. The hypothesis of this work is that the DMI of cow pens are not normally distributed and the total DMI from the best-fit distribution shape for a cow pen will have lower percentage error to the observed DMI than a prediction of a single DMI that is fed at a uniform level and assumes a normal distribution. Our objective was to describe the distribution shape of DMI by week of lactation, and for different pen types. Pens were generated by randomly assorting cows by the week of lactation from a database into different categories of pen for size and lactation period. These pens were fitted to the best distribution type, and its parameters were used to randomly generate distribution plots that predict the total DMI for each pen. A second predictive model estimated the DMI of each pen using an empirical equation of DMI that was multiplied by the number of cows in the pen to represent feeding of a uniform DMI quantity. The percentage error for the distribution shape model was significantly lower than the empirical model with pen errors being less than 1%. The beta distribution type was the most common distribution to best represent the data of pen DMI. Describing the distribution and using it to predict a total pen DMI provides accurate estimates of feed quantity for a group. Reducing error by using the distribution of DMI for feed formulation, instead of the nutrient requirements of an individual animal can provide a precision nutrition approach to group feeding.

Calf health veterinary services: Making them work for calves, farmers and veterinarians

BACKGROUND

Despite an appetite among UK veterinarians (vets) and farmers to improve calf health, vets face challenges in delivering and sustaining proactive calf health services.

METHODS

Forty-six vets and 10 veterinary technicians (techs) participated in a project to determine what makes calf health services successful while improving their own services. In four facilitated workshops and two seminars, carried out between August 2021 and April 2022, participants described their approaches to calf work, discussed measures of success, identified challenges and success factors, and addressed knowledge gaps.

RESULTS

Many approaches to calf health services were described, and these could be categorised into three overlapping models. Success involved enthusiastic, knowledgeable vets/techs, supported by their practice team, fostering positive attitudes among farmers by providing the services they need, creating a tangible return on investment for farmers and the practice. Lack of time was identified as the most prominent challenge to achieving success.

LIMITATIONS

Participants were self-selected from one nationwide group of practices.

CONCLUSION

Successful calf health services depend on identifying the needs of calves, farmers and veterinary practices, and delivering measurable benefits to each. More calf health services embedded as a core part of farm veterinary practice could bring wide ranging benefits to calves, farmers and vets.

State-level trends in the greenhouse gas emission intensity of US milk production

The greenhouse gas emission intensity of US milk production (i.e., greenhouse gas emissions per unit of production) has varied across time and states. However, research has not examined how farm-sector trends affect the state-level emission intensity of production. We estimated fixed effects regressions with state-level panel data from 1992 through 2017 to test how US dairy farm-sector changes influenced the greenhouse gas emission intensity of production. We found that increases in per cow milk productivity reduced the enteric greenhouse gas emission intensity of milk production, while it had no statistically significant effect on the manure greenhouse gas emission intensity of production. In contrast, increases in average farm size and the number of farms reduced the manure greenhouse gas emission intensity of milk production, while they did not affect the enteric greenhouse gas emission intensity of production.

The importance of historically popular sires on the accuracy of genomic predictions of young animals in the US Holstein population

The dairy industry is known for its extensive use of artificial insemination, which has resulted in a population where most animals can be traced back to only a few sires. Due to their relatedness to the population, old influential sires could still contribute to the accuracy of genomic predictions. The objective of the study was to identify the impact of historically influential sires on the recent population. This was tested by constructing a genomic relationship matrix using recursion with different sets of sires. Differences in prediction accuracies with different sets are indicative of how important each set is. Recursion coefficients linking young animals to those sets reveal the relative importance of specific sires to the prediction accuracy of recent animals. The data included ∼10 million scores for stature and fore udder attachment (FUA) measured from 1983. Genotypes of 569,404 animals were available. Sire sets included the 100 most popular sires born within different time periods. Computations were with single-step genomic BLUP. In general, the younger sires had higher prediction accuracies than the oldest sires, even though they generally have fewer progeny. The accuracy of evaluation for stature was increased from 0.54 with the most popular sires born before 1981 to 0.69 with sires born from 2001 to 2010, while the accuracy for FUA increased from 0.47 to 0.61. The accuracy achieved using the overall 100 most used sires was 0.66 for stature and 0.58 for FUA. All 100 sires from each period were combined in a subset to determine the importance of each sire relative to all 400 animals in the combined subset. The highest relative impact of a sire that was born within the different time sets was 1.97 for Valiant (before 1981), 1.94 for Blackstar (1981 to 1990), 4.38 for Shottle (1991 to 2000), and 3.09 for Planet (2001 to 2010). The 3 sires among the 400 with the greatest impact were Shottle, Goldwyn (3.73), and Planet. The relative impact of a sire was not strongly related to the number of progeny. For instance, the relative impact of Durham with 34K progeny was 2.29, whereas the impact of O Man with 15K progeny was 3.13. The impact of a sire is also influenced by whether it was used as a sire of sires. Results show that younger sires are more relevant to the accuracy of breeding value prediction in the recent population.

An observational study of ear-tagged calf mortality (1 to 100 days) on Irish dairy farms and associations between biosecurity practices and calf mortality on farms participating in a Johne's disease control program

Postnatal mortality among replacement stock has a detrimental effect on the social, economic, and environmental sustainability of dairy production. Calf mortality rates vary between countries and show differences in temporal trends; most, however, are characterized by high levels of between-farm variability. Explaining this variation can be difficult because herd-level information on management practices relevant to calf health is often not available. The Irish Johne's Control Programme (IJCP) contains a substantial on-farm monitoring program called the Veterinary Risk Assessment and Management Plan (VRAMP). Although this risk assessment is largely focused on factors relevant to the transmission of paratuberculosis, many of its principles are good practice biocontainment policies that are also advocated for the protection of calf health. The objectives of this study were (1) to quantify mortality in ear-tagged Irish dairy calves between 2016 and 2020 using both survival and risk approaches, (2) to determine risk factors for 100-d cumulative mortality hazard in ear-tagged Irish dairy calves between 2016 and 2020, (3) to determine whether 100-d cumulative mortality hazard was higher in ear-tagged calves within herds registered in the IJCP versus those that were not registered in the IJCP and whether there were differences between these cohorts over time, and (4) within IJCP herds, to determine whether VRAMP score or changes in VRAMP score were associated with 100-d cumulative mortality hazard. Excluding perinatal mortality, the overall 100-d cumulative mortality hazard was 4.1%. Calf mortality was consistently underestimated using risk approaches that did not account for calf censoring. Cox proportional hazards models showed that cumulative mortality hazard was greater in male calves; particularly, calves born to Jersey breed dams and those with a beef breed sire. Mortality hazard increased with increasing herd size, was highest in calves born in herds that contract-reared heifers, and lowest in those born in mixed dairy-beef enterprises. Mortality hazard decreased over time with the mortality hazard in 2020 being 0.83 times that of 2016. Mortality hazard was higher in IJCP-registered herds than nonregistered herds (hazard ratio 1.06, 95% CI 1.01-1.12), likely reflecting differences in herds that enrolled in the national program. However, we detected a significant interaction between IJCP status (enrolled vs. not enrolled) and year (hazard ratio 0.96, 95% CI 0.92-1.00), indicating that the decrease in mortality hazard between 2016 and 2020 was greater in IJCP herds versus non-IJCP herds. Finally, increasing VRAMP scores (indicating higher risk for paratuberculosis transmission) were positively associated with increased calf mortality hazard. Postnatal calf mortality rates in Irish dairy herds declined between 2016 and 2020. Our study suggests that implementation of recommended biocontainment practices to control paratuberculosis in IJCP herds was associated with a reduction in calf mortality hazard.

Animal board invited review: Genomic-based improvement of cattle in response to climate change

Climate change brings challenges to cattle production, such as the need to adapt to new climates and pressure to reduce greenhouse emissions (GHG). In general, the improvement of traits in current breeding goals is favourably correlated with the reduction of GHG. Current breeding goals and tools for increasing cattle production efficiency have reduced GHG. The same amount of production can be achieved by a much smaller number of animals. Genomic selection (GS) may offer a cost-effective way of using an efficient breeding approach, even in low- and middle-income countries. As climate change increases the intensity of heatwaves, adaptation to heat stress leads to lower efficiency of production and, thus, is unfavourable to the goal of reducing GHG. Furthermore, there is evidence that heat stress during cow pregnancy can have many generation-long lowering effects on milk production. Both adaptation and reduction of GHG are among the difficult-to-measure traits for which GS is more efficient and suitable than the traditional non-genomic breeding evaluation approach. Nevertheless, the commonly used within-breed selection may be insufficient to meet the new challenges; thus, cross-breeding based on selecting highly efficient and highly adaptive breeds may be needed. Genomic introgression offers an efficient approach for cross-breeding that is expected to provide high genetic progress with a low rate of inbreeding. However, well-adapted breeds may have a small number of animals, which is a source of concern from a genetic biodiversity point of view. Furthermore, low animal numbers also limit the efficiency of genomic introgression. Sustainable cattle production in countries that have already intensified production is likely to emphasise better health, reproduction, feed efficiency, heat stress and other adaptation traits instead of higher production. This may require the application of innovative technologies for phenotyping and further use of new big data techniques to extract information for breeding.

Dairy production sustainability through a one-health lens

Dairy production provides high-quality, healthful nutrients to people on a planet soon to be inhabited by over 9 billion people. In doing so, it is ever more important to continuously improve the care of dairy animals, safeguard the environment we all share, and reliably produce nutritious food while maintaining the economic viability of the people working in dairy agriculture. In this paper, we review some associations between dairy consumption and human health along with the many interconnections between people, dairy animals, plants, and our shared environment. Understanding these relationships is an example of one health at work. In the US, total dairy consumption is at its highest point in the last 50 years, while many objective measures of cow health (eg, subclinical mastitis) have never been better since they have been recorded. Further, indications of food safety such as violative antibiotic residues in milk have never been lower. Dairy foods provide essential nutrients such as protein, vitamin B12, and calcium, while there is also evidence that they are protective against chronic conditions such as cardiovascular disease. Finally, the environmental footprint of dairy production in the US, as measured by metrics such as carbon dioxide-equivalent emissions intensity per unit of dairy nutrient, is the lowest it has ever been. The companion Currents in One Health by Nguyen et al, AJVR, January 2023, discusses some additional animal welfare and environmental impact implications of modern dairy production management in detail.

Investigating the effect of temporal, geographic, and management factors on US Holstein lactation curve parameters

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.

Feeding Bakery Former Foodstuffs and Wheat Distiller’s as Partial Replacement for Corn and Soybean Enhances the Environmental Sustainability and Circularity of Beef Cattle Farming

The effects of the partial substitution of corn and soybean meals with bakery former foodstuffs (BFF) and wheat wet distiller’s grains (WDGs) on environmental sustainability, production performance, and health status were evaluated in beef cattle. Newly arrived Limousine beef heifers (n = 408) housed an intensive farm in Campagnatico (Grosseto, Italy) were balanced for initial weight and body conformation and then randomly divided in two groups: (i) Traditional corn–soybean meal diet; (ii) Circular diet with average as-fed 1.5 kg BFF and 1.5 kg WDGs as substitute for 1.6 kg corn and 0.3 kg soybean meal. The environmental impact of the diet was analyzed considering greenhouse gases emissions (GHG, kg CO2 eq), water (H2O, L), and land use (LU, m2) as well as consumption of human-edible feeds (HE, kg). The growth performance, feed intake (FI), feed conversion ratio (FCR), carcass characteristics, apparent total tract digestibility (aTTD), and health status of heifers were evaluated. The Circular diet led to a reduction per kg of cold carcass weight (CCW) of 1.00 kg CO2 eq of GHG, 72.38 L of H2O, 1.20 m2 of LU, and 0.95 kg of HE (p < 0.0001). Growth performances, carcass characteristics, and health status were not affected (p > 0.05). Sugar and pectin aTTD were significantly higher (p < 0.0001) in the Circular group. Replacing traditional feed ingredients with BFF and WDGs reduced the environmental impact of the diet of fattening Limousine heifers and the food competition between humans and beef cattle in accordance with circular economy principles.

Effect of a Blend of Essential Oils, Bioflavonoids and Tannins on In Vitro Methane Production and In Vivo Production Efficiency in Dairy Cows

Two trials were performed to evaluate the efficacy of a blend of essential oils, bioflavonoids and tannins on methane (CH4) emissions (in vitro) and on the production efficiency of dairy cows (in vivo). The in vitro trial tested the production of total gas and CH4 at 16, 20 and 24 h of incubation, and volatile fatty acids (VFA) at 16 and 24 h, through biochemical methane potential (BMP) assays. In the in vivo trial, milk yield, dry matter intake (DMI), feed conversion rate (FCR), milk quality and apparent total tract digestibility (aTTD) were evaluated in 140 lactating Holstein Friesian cows. Animals were allocated into two groups: (i) Control, standard diet; (ii) Treatment, standard diet plus 10 g/head/d of a powder with a 10% concentration of a blend of essential oils, bioflavonoids and tannins. Statistical analysis was performed using the mixed procedure of SAS either for single or repeated measures. For all the parameters a p-value ≤ 0.05 was considered statistically significant. The blend significantly reduced the in vitro total gas and CH4 emissions at 16, 20 and 24 h of incubation (p < 0.001). In addition, acetic acid was reduced (p < 0.001), while propionic acid concentration was increased (p < 0.001) at 16 h and 24 h. In the in vivo trial, the Treatment group showed significantly raised milk yield, DMI, FCR (p < 0.001), and of the aTTD of cellulose and starch (p ≤ 0.002), while the milk quality traits were not affected. Overall, the results from the study indicated that the blend of essential oils, bioflavonoids, and tannins significantly reduced in vitro total gas and CH4 production and improved the production efficiency of lactating dairy cows in vivo.

The Role of Anaerobic Digestion and Solar PV to Achieve GHG Neutrality in a Farm Setting

Dairy farms are challenged to increase productivity while achieving environmental sustainability, where greenhouse gas (GHG) emissions are at the center of the discussion. The U.S. dairy industry leadership has committed to a Net Zero Initiative to achieve GHG neutrality, but the specifics on how to achieve this are still uncertain. Life cycle assessment methods were used to quantify GHGs and net energy intensity (NEI) of a large (1000 cows) and a small (150 cows) farm in Wisconsin. The GHGs are 1.0 and 1.3 kg CO2-eq/kg FPCM and the NEI is 2.4 and 3.2 MJ/kg FPCM for the large and small farm, respectively. The GHG benefits from anaerobic digestion (AD, sized to process all manure on both farms) and PV (sized to match AD electricity production) are not enough to achieve GHG neutrality. Increasing the capacity of these systems showed that AD is more cost-effective for the larger farm, but the challenges and costs related to securing and disposing the extra manure needed for energy production limit its feasibility. For the smaller farm, the total annualized costs to achieve GHG neutrality are lower for PV vs. AD, even before accounting for any transportation costs related to handling the extra manure.

Current Perspectives on Achieving Pronounced Enteric Methane Mitigation From Ruminant Production

Limiting global warming to 1.5°C above pre-industrial levels by 2050 requires achieving net zero emissions of greenhouse gases by 2050 and a strong decrease in methane (CH4) emissions. Our aim was to connect the global need for mitigation of the emissions of greenhouse gases and enteric CH4 from ruminant production to basic research on the biological consequences of inhibiting rumen methanogenesis in order to better design strategies for pronounced mitigation of enteric CH4 production without negative impacts on animal productivity or economic returns. Ruminant production worldwide has the challenge of decreasing its emissions of greenhouse gases while increasing the production of meat and milk to meet consumers demand. Production intensification decreases the emissions of greenhouse gases per unit of product, and in some instances has decreased total emissions, but in other instances has resulted in increased total emissions of greenhouse gases. We propose that decreasing total emission of greenhouse gases from ruminants in the next decades while simultaneously increasing meat and milk production will require strong inhibition of rumen methanogenesis. An aggressive approach to pronounced inhibition of enteric CH4 emissions is technically possible through the use of chemical compounds and/or bromoform-containing algae, but aspects such as safety, availability, government approval, consumer acceptance, and impacts on productivity and economic returns must be satisfactorily addressed. Feeding these additives will increase the cost of ruminant diets, which can discourage their adoption. On the other hand, inhibiting rumen methanogenesis potentially saves energy for the host animal and causes profound changes in rumen fermentation and post-absorptive metabolism. Understanding the biological consequences of methanogenesis inhibition could allow designing strategies to optimize the intervention. We conducted meta-regressions using published studies with at least one treatment with &gt;50% inhibition of CH4 production to elucidate the responses of key rumen metabolites and animal variables to methanogenesis inhibition, and understand possible consequences on post-absorptive metabolism. We propose possible avenues, attainable through the understanding of biological consequences of the methanogenesis inhibition intervention, to increase animal productivity or decrease feed costs when inhibiting methanogenesis.

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle

Simple Summary

Sensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.

Abstract

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.

Biotechnologies to Bridge the Schism in the Bioeconomy

Schism is the new normal for the bioeconomy concept. Since its proliferation in governments, the concept has been adapted to fit national or regional exigencies. Earlier this century the knowledge-based bioeconomy (KBBE) in Europe was seen as a technical and knowledge fix in the evolving sustainability landscape. At the OECD, the concept was further honed by imagining a future where biotechnologies contribute significantly to economic growth and development. Countries started to make national bioeconomy strategies. Some countries have diverged and made the bioeconomy both much larger and more general, involving a wide variety of sectors, such as industry, energy, healthcare, agriculture, aquaculture, forestry and fishing. Whatever the approach, what seems to be consistent is the need to reconcile environmental, social and economic sustainability. This paper attempts to establish one schism that could have ramifications for the future development of the bioeconomy. Some countries, including some of the largest economies but not exclusively so, are clearly following a biotechnology model, whereas others are clearly not. In the wake of the COVID-19 pandemic, biotechnologies offer outstanding potential in healthcare, although this sector is by no means included in all bioeconomy strategies. The paper also attempts to clarify how biotechnologies can address the grand challenges and the United Nations Sustainable Development Goals. The communities of scientists seem to have no difficulty with this, but citizens and governments find it more difficult. In fact, some biotechnologies are already well established, whereas others are emerging and more controversial.

Greenhouse Gas Emissions from Agriculture in EU Countries—State and Perspectives

Agriculture is one of the main sources of greenhouse gas (GHG) emissions and has great potential for mitigating climate change. The aim of this study is to analyze the amount, dynamics of changes, and structure of GHG emissions from agriculture in the EU in the years 2005–2018. The research based on data about GHG collected by the European Environment Agency. The structure of GHG emissions in 2018 in the EU is as follows: enteric fermentation (45%), agricultural soils (37.8%), manure management (14.7%), liming (1.4%), urea application (1%), and field burning of agricultural residues (0.1%). Comparing 2018 with the base year, 2005, emissions from the agricultural sector decreased by about 2%, which is less than the assumed 10% reduction of GHG emissions in the non-emissions trading system (non-ETS) sector. The ambitious goals set by the EU for 2030 assume a 30% reduction in the non-ETS sector. This will require a significant reduction in GHG emissions from agriculture. Based on the analysis of the GHG emission structure and available reduction techniques, it was calculated that in this period, it should be possible to reduce emissions from agriculture by about 15%.

Sustainability of the Dairy Industry: Emissions and Mitigation Opportunities

Dairy cattle provide a major benefit to the world through upcycling human inedible feedstuffs into milk and associated dairy products. However, as beneficial as this process has become, it is not without potential negatives. Dairy cattle are a source of greenhouse gases through enteric and waste fermentation as well as excreting nitrogen emissions through their feces and urine. However, these negative impacts vary widely due to how and what these animals are fed. In addition, there are many promising opportunities for further reducing emissions through feed and waste additives. The present review aims to further expand on where the industry is today and the potential avenues for improvement. This area of research is still not complete and additional information is required to further improve our dairy systems impact on sustainable animal products.

Modeling the effects of steroid implant use on the environmental and economic sustainability of Brazilian beef production

Brazilian beef systems contribute 14.9% of global beef production, therefore given climate change concerns, there is a clear need to reduce environmental impacts while maintaining economic viability. This study evaluated the hypothesis that steroid implant use in Brazilian beef cattle would reduce resource use, greenhouse gas (GHG) emissions and economic costs of production, thereby improving environmental and economic sustainability. A deterministic model based on beef cattle population demographics, nutrition and performance was used to quantify resource inputs and GHG emissions per 1.0 × 106 kg of hot carcass weight (HCW) beef. System boundaries extended from cropping input manufacture to cattle arriving at the slaughterhouse. Beef systems were modeled using herd population dynamics, feed and performance data sourced from producers in four Brazilian states, with additional data from global databases. Implants were used in calves, growing and finishing cattle at low (LI), medium (MI), and high (HI) levels of performance enhancement, compared to nonimplanted (NI) controls. Feed use results were used in combination with producer-derived input costs to assess the economic impacts of implant use, including production costs and returns on investment. Improved FCE, ADG, and carcass weights conferred by implant use reduced the number of cattle and the time taken to produce 1.0 × 106 kg HCW beef. Compared to NI controls, the quantities of feed, land, water and fossil fuels required to produce 1.0 × 106 kg HCW beef was reduced in implanted cattle, with reductions proportional to the performance-enhancing effect of the implant (HI > MI > LI). Implant use reduced GHG emissions per 1.0 × 106 kg HCW beef by 9.4% (LI), 12.6% (MI), or 15.8% (HI). Scaling up the MI effects to represent all eligible Brazilian cattle being implanted, revealed avoided GHG emissions equivalent to the annual exhaust emissions of 62.0 × 106 cars. Economic impacts of implant use reflected the environmental results, resulting in a greater margin for the producers within each system (cow-calf through to finishing). The 6.13% increase in kg of HCW beef produced generates a cost reduction of 3.76% and an increase in the return on invested capital of 4.14% on average. Implants offer the opportunity for Brazilian beef producers to demonstrate their dedication to improving environmental and economic sustainability through improved productivity, although care must be taken to avoid negative trade-offs.

A dataset of human-inedible byproduct feeds consumed by dairy cows in the United States

Dairy cows convert human-indigestible forages and byproducts nutrients into edible food for humans [1]. Because of microbiota located in their rumen, dairy cows can digest fibrous forages and feeds which are not exploited by humans and monogastric animals like pigs. Dairy cows in the U.S. have been fed byproduct feeds as part of their diet for decades [2], [3]. Dairy nutritionists use complex nutrition models to develop economical and nutritious diets composed of grains, byproduct feeds, and forages. Accurate, complete, up-to-date information on byproduct feed consumption by dairy cows would be useful for both public and private researchers seeking to understand the type and extent of byproduct usage on US dairies. In collaboration with the American Feed Industry Association (AFIA), a survey was sent to US feed company representatives inquiring about the types and amounts of byproducts sold as dairy cow feed during the last year, the number of lactating cows serviced, the amount of milk produced by these lactating cows, and the states where these cows were located. A similar survey was sent to practicing US dairy nutritionists inquiring about their typical daily feeding rates of byproduct feeds by type, the number of cows consuming these byproducts, the amount of milk produced by the lactating cows, and the states where these cows were located. Survey data are representative of 33.5% of US lactating cows and 35.7% of US milk production in 2019 [4]. Amounts of each type of byproduct feed consumed per US milking cow (including replacement heifers and dry cows) and per kg of milk produced were calculated for the US and its four regions [5]. Total 2019 regional and US byproduct consumption by type was calculated. Nutrient compositions of each byproduct feed were reported.

Effect of Slow-Release Urea Administration on Production Performance, Health Status, Diet Digestibility, and Environmental Sustainability in Lactating Dairy Cows

The effects of partially replacing soybean meal (SBM) with a slow-release urea source (SRU) on production performance, feed efficiency, digestibility, and environmental sustainability of dairy cows were evaluated. A total of 140 lactating Holstein Frisian cows were allocated into two study groups: (i) control (diet entirely based on SBM), and (ii) treatment (diet of 0.22% on dry matter basis (d.m.)) of SRU. Milk yield, dry matter intake (DMI), feed conversion rate (FCR), body condition score (BCS), reproductive parameters, and milk quality were evaluated. The chemical composition of the feeds and feces were analyzed to calculate the in vivo digestibility of the two diets. The carbon footprint (CFP) and predicted methane (CH₄) emissions were evaluated. The inclusion of SRU significantly increases milk yield, DMI, and FCR (p < 0.0001), whereas milk quality, BCS, and reproductive indicators were not affected (p > 0.05). In the treatment group, the digestibility of crude protein (CP) (p = 0.012), NDF (p = 0.039), and cellulose (p = 0.033) was significantly higher, while the other nutritional parameters weren't affected. All the environmental parameters were significantly improved in the treatment group (p < 0.0001). Replacing SBM with SRU can be a strategy to enhance dairy cows' sustainability due to improved production efficiency, reduced feed CFP, and predicted CH₄ production.

Effects of Heated Drinking Water on the Growth Performance and Rumen Functionality of Fattening Charolaise Beef Cattle in Winter

Simple Summary

Efficiency has been a major metric for measuring the production performances and profitability of zootechny, especially in beef cattle farming, even in terms of environmental sustainability. More efficient beef cattle farming should include a decrease in total feed consumption, equal or greater production performance and lower methane emissions and manure excretion. In fact, the rumen is the keystone of cattle efficiency. Strategies to maintain the rumen’s stability while enhancing its functionality can be drivers of better overall efficiency. Besides the feeds used and nutritional management, drinking water—specifically, its temperature—can alter and modulate the ruminal environment, due to the high sensitivity of the ruminal microbiota. Drinking heated water kept at a constant temperature can lead to enhanced production efficiency, due to better rumen stability and increased viability of ruminal bacteria.

Abstract

The effects of heated drinking water on growth performance and rumen functionality in fattening beef cattle during winter were evaluated. Newly received Charolaise bulls (n = 224) were allocated to two experimental groups: (i) water at room temperature (RTW) (weight 408 ± 34 kg); (ii) constantly heated water (25 °C) (HW) (weight 405 ± 38 kg). Growth performances, feed intake, feed conversion rate, water intake and carcass characteristics were evaluated. Internal reticuloruminal wireless boluses were used to collect rumen pH and temperature values every 10 min. Bodyweight was not affected by the water temperature, but the overall average daily gain (ADG) was significantly higher in the HW group (1.486 vs. 1.438 kg/head/day in the RTW; p = 0.047). Dry matter intake was significantly higher in the HW group (p = 0.001), even though the final feed conversion rate (FCR) was not influenced. There was also a tendency for better cold carcass weight (CCW) and carcass yield (CY) in the HW group. Drinking heated water reduced the time (min/day) during which the ruminal pH was below pH 5.8 or 5.5, and the time during which the temperature was lower than 37 or 39 °C (p < 0.001). The use of heated drinking water is a plausible a strategy for enhancing ruminal stability and the overall production efficiency in fattening beef cattle, which will lead to both better growth performance and higher ruminal stability.

Review: Perspective on high-performing dairy cows and herds

Milk and dairy products provide highly sustainable concentrations of essential amino acids and other required nutrients for humans; however, amount of milk currently produced per dairy cow globally is inadequate to meet future needs. Higher performing dairy cows and herds produce more milk with less environmental impact per kg than lower performing cows and herds. In 2018, 15.4% of the world's dairy cows produced 45.4% of the world's dairy cow milk, reflecting the global contribution of high-performing cows and herds. In high-performing herds, genomic evaluations are utilized for multiple trait selection, welfare is monitored by remote sensing, rations are formulated at micronutrient levels, health care is focused on prevention and reproduction is managed with precision. Higher performing herds require more inputs and generate more waste products per cow, thus innovations in environmental management on such farms are essential for lowering environmental impacts. Our focus is to provide perspectives on technologies and practices that contribute most to sustainable production of milk from high-performing dairy cows and herds.

The Ruminant Farm Systems Animal Module: A Biophysical Description of Animal Management

Dairy production is an important source of nutrients in the global food supply, but environmental impacts are increasingly a concern of consumers, scientists, and policy-makers. Many decisions must be integrated to support sustainable production-which can be achieved using a simulation model. We provide an example of the Ruminant Farm Systems (RuFaS) model to assess changes in the dairy system related to altered animal feed efficiency. RuFaS is a whole-system farm simulation model that simulates the individual animal life cycle, production, and environmental impacts. We added a stochastic animal-level parameter to represent individual animal feed efficiency as a result of reduced residual feed intake and compared High (intake = 94% of expected) and Very High (intake = 88% of expected) efficiency levels with a Baseline scenario (intake = 100% of expected). As expected, the simulated total feed intake was reduced by 6 and 12% for the High and Very High efficiency scenarios, and the expected impact of these improved efficiencies on the greenhouse gas emissions from enteric methane and manure storage was a decrease of 4.6 and 9.3%, respectively.

Pasture-Based Dairy Systems in Temperate Lowlands: Challenges and Opportunities for the Future

Improved efficiency in dairy systems is a significant challenge for the future, to meet increased food demand while competing for inputs, adapting to climate change, and delivering ecosystem services. Future grazing systems can play a major role to supply healthier foods within systems with a reduced reliance on fossil fuels and chemical inputs, while also delivering environmental, biodiversity, and animal welfare benefits. Can we design lower-input systems that deliver efficient levels of output in a positive environmental context? Lower-input systems will have a lower reliance on concentrates and inorganic fertilizers, and an increased reliance on extended grazing seasons and high quality forage. Multiple strategies will be needed to maximize nitrogen use efficiency, including a strong reliance on legume-based swards that displace inorganic nitrogen fertilizer. Expected environmental benefits include a reduction in GHG emissions and nitrate leaching, an increase in C sequestration and a reduced reliance on the use of herbicides and pesticides. In comparison with confinement feeding systems, the relatively low energy density and high climate sensitivity of grazing diets requires both effective pasture management and robust and adaptive animals. The appropriate cow for grazing systems must be able to harvest pasture efficiently by re-calving every 365 days to efficiently utilize peak pasture supply, achieve large intakes of forage relative to their genetic potential for milk production (i.e., aggressive grazers) and be adaptable to fluctuations in feed supply. Legume-based multi-species grassland mixtures can maximize the use of symbiotically-fixed nitrogen, and displace the use of inorganic N fertilizer. There is a need for system-scale experiments that use legume-based mixtures within paddocks, and in grassland leys within crop rotations. Moreover, lower-input systems will need a combined focus on research and knowledge transfer for rapid testing and implementation. New opportunities and requirements will arise as policy, society, and the markets demand a higher level of environmental sustainability from food systems and products. This raises the possibility of public-private partnerships for the demand and reward of provision of environmental benefits. To deliver these benefits, future food systems will need to be redesigned to incorporate the enhanced supply of a range of ecosystem goods and services, which should be better incentivized through the market price returned to producers.

Driving Sustainability in Dairy Farming from a TBL Perspective: Insights from a Case Study in the West Region of Santa Catarina, Brazil

All companies in agribusiness supply chains need to be aware of the best use of available resources, which demands an integrated assessment of environmental, economic and social aspects, i.e., the Triple Bottom Line (TBL). Such analysis allows us to get a more balanced and complete understanding of the real performance of companies, supply chains and industries. Companies in the upstream of agribusinesses supply chains present some limitations, but can contribute significantly to the overall sustainability of the entire value chain. The objective of this research was to understand the role of the drivers of sustainability in dairy farming from a TBL perspective, such as assistance to producers and the value chain, and the use of better technology and management practices. A sample of 54 rural farms in the dairy supply chain of the western region of Santa Catarina, Brazil, was used to test four hypotheses about what can drive sustainability. Furthermore, first- and second-order structural equation models using SMART PLS software were used for the analysis of the data. The results obtained show that social sustainability is positively influenced by the use of good management practices, and the latter, as well as public policies, positively influence economic sustainability. Furthermore, it was found that improvements in production techniques positively influence environmental sustainability, and this is mostly influenced by the use of good management practices, and less so by policies directed at the supply chain. Finally, from the analysis of the second-order variable for sustainability, it was highlighted that the economic dimension prevails in the eyes of the farmers, as the main dimension of sustainability, and that environmental aspects are still neglected.