NC2040: Metabolic Relationships in Supply of Nutrients for Lactating Cows
(Multistate Research Project)
Status: Active
NC2040: Metabolic Relationships in Supply of Nutrients for Lactating Cows
Duration: 10/01/2023 to 09/30/2028
Administrative Advisor(s):
NIFA Reps:
Non-Technical Summary
Statement of Issues and Justification
ISSUES
The US dairy industry is a major contributor to the diets of Americans and the economic viability of rural communities. With current dietary patterns in the US, dairy products supply about 11% of the calories, 17% of the protein, 52% of the calcium, 51% of the vitamin D, 29% of the vitamin A, 28% of the vitamin B12, and 17% of the zinc in diets of Americans over the age of 2 (among other essential nutrients). The industry provides 3.3 million jobs and total economic activity of more than $750 billion annually in the US. Despite these important contributions, there are also significant challenges to the sustainability of the industry, including concerns about the environmental footprint of dairy production, animal well-being, and rising input costs.
Our long-term goal is to improve the efficiency of milk production as well as cow health and longevity, and thus promote environmental and economic sustainability of the US dairy industry. Our approach to achieve this goal is to systematically identify biological and nutritional management processes that will provide the greatest improvement and to concentrate our collaborative research efforts there. This is done partly through the construction, evaluation, and refinement of computer-assisted bio-mathematical models that describe the metabolic relationships between feed inputs and milk outputs of cattle. We use the terminology “precision feeding systems” to reflect the goal of being able to efficiently feed dairy cows that widely differ in genetics, environment and diets. Although dairy producers large and small feed dairy cattle in a wide variety of ways, a major goal is to be precise in meeting the needs of their cows across those diverse systems.
Improvement in animal and resource efficiency is slowed by a lack of clear research priorities addressing the most critical areas. This is due to a combination of factors, including: lack of quantitative data regarding absorbed nutrients and the metabolic responses of cows to those nutrients; a lack of integration of existing data into bio-mathematical models that will point out areas of greatest need; and a lack of real and enthusiastic support in the research and funding communities for cooperative, large-scale, integrated research work. In addition, integration of recent discoveries concerning genetic regulation and animal genotypes and phenotypes (genomics, transcriptomics, proteomics, metabolomics) into traditional livestock nutritional science has been slow. Recent technological advancements and an appreciation for the importance of genotype in nutrient use by dairy nutritionists are now increasing the pace of that integration. Likewise, increasing knowledge of how nutrition impacts animal health opens an avenue for dairy nutritionists to address sustainability challenges linked to the short productive life of US dairy cattle. These developments hold great promise for quantum improvements in efficiency (10 to 15% on a herd basis as opposed to the traditional incremental increases).
Our committee has addressed these gaps in knowledge steadfastly in the last 40 years, including the last 5, and the research and outreach done by this group continues to improve the understanding and efficiency of dairy production. A cornerstone of the recent achievements is the 2021 publication of the NASEM Nutrient Requirements of Dairy Cattle that was written by a committee with more than half of members who are current or retired NC-2040 members. This publication is the go-to resource for definitive information on dairy cattle nutrition, and the contributions of this committee in shaping that resource are among our greatest impacts. In the revision beginning in 1987, a conscious effort was made to plan and conduct experiments to provide data to improve research and practical nutritional models. The outcomes of this work were essential in the 2021 NASEM publication; however, much remains to be done. For reasons given in the previous paragraph, improvements in designing, conducting and interpretating complex research, including integrating information into model systems, has been slow. Yet this committee has continued to do excellent scientific work in practical and basic dairy nutrition. New additions to the committee in the past 5 years have maintained our traditional strength in applied dairy nutrition while also enhancing expertise in rumen microbiology, molecular biology, and quantitative analysis. With these changes, the committee has identified new approaches and set new goals, all under the umbrella of feeding and metabolism of dairy cattle.
We have retained our title as it still accurately describes our collective mission. Our specific objectives are organized under three themes. Our first theme is to quantify properties of feeds that determine the availability and utilization of nutrients critical to milk production. Our second theme is to quantify metabolic and molecular interactions that alter synthesis of milk components. Our final theme is to use this knowledge of feed properties and metabolic and molecular quantitative relationships to challenge and refine precision feeding systems for dairy cattle.
The overarching goal is to do sound, collaborative research directed toward identifying specific biological concepts and processes that can be applied to improve dairy cattle feeding. Our work contributes to 1) improved accuracy of feeding standards and nutrient requirement predictions for dairy cattle, 2) standardization of analytical methods for feed evaluation, 3) reduced losses of nutrients and greenhouse gasses to the environment from dairy cattle, 4) profitable and environmentally sustainable use of available feedstuffs, 5) continued expansion into new areas of integrative biology involving nutrition and 6) continued supply of affordable, nutritious products for human consumption.
JUSTIFICATION:
The Need as Indicated by Stakeholders. Approximately 52% of the calcium, 17% of the protein, and 11% of the energy in the US diet are supplied by dairy products; thus, the US consumer is a major stakeholder for the NC-2040 committee. Consumers want dairy products that are safe and inexpensive, but increasingly they also want an environmentally friendly dairy industry that promotes animal well-being. Recently, attention has been given to bioactive molecules in milk such as conjugated linoleic acids, and the expertise of the NC-2040 committee is well aligned with objectives to increase delivery of bioactive compounds into milk. Primary direct stakeholders include other scientists, practicing nutritionists, veterinarians, and farmers. Feed inputs are a major determinant of milk yield, cow health, feed efficiency, profitability, and waste output, and the work of the NC-2040 committee is critical to meet stakeholder needs.
Importance of the Work. Natural resources are used most efficiently when milk production per unit feed and per cow is high. To efficiently produce milk, a cow must have a well-developed mammary gland and be able to supply the gland with the nutrients it needs. Nutrition in the first year of life affects mammary gland development, and nutrition around the time of calving and throughout lactation has a major effect on the health, productivity, and efficiency of cows. Feeding for optimal nutrient intake requires not only the provision of the necessary nutrients for milk production but also consideration to the effects of diet on mammary capacity and on appetite, health, and metabolic regulation of the cow. Because feed costs account for half of all costs on a dairy farm, nutrition also significantly impacts farm expenses. The NC-2040 committee considers all of these factors for optimal feeding. For example, if we could maintain current milk production while feeding diets with 4 percentage units less total protein, we would decrease N losses to the environment in the US by 300,000 metric tons per year and save US dairy farmers $540 M per year in feed costs. This type of progress only can be made if we take an integrated approach, with the use of mechanistic bio-mathematical models that accurately describe metabolism and production of cows.
Technical Feasibility. This committee has a record of making significant impacts in our knowledge of dairy cattle nutrition and metabolism and in the way that dairy cattle are fed and managed nationwide. Computer-based, mechanistic, and quantitative metabolic models are useful in two ways: first, they help us determine critical needs in research and secondly, they enable practical improvements in dairy cow feeding. Critical research needs are determined by using existing data from NC-2040 members or conducting new experiments to test model predictions of physiological responses to experimental diets. Examples of such responses include: rumen pH; microbial growth and function; alterations in gene expression and hormonal release of organs such as the adipose tissue; and alterations in milk fatty acid compositions. By challenging our working models in this way, we identify shortcomings that then become the basis for developing new testable hypotheses for further collaborative experimentation. Results from new experiments are incorporated into the models, and they are challenged again for further refinement. Thus, we continue to build our models so they are more mechanistic, quantitative, and accurate. These qualities enable us to improve practical feeding recommendations for dairy cattle in a variety of environmental and feeding conditions.
Advantages for Doing the Work as a Multistate Effort. Important and complex problems require coordinated effort of many personnel. Considerable progress has been made in dairy nutrition, but practical problems remain, and no single research group has the skills and resources needed to solve them alone. Only through cooperation can State Experiment Stations address the complex interactions among environment, feed supply, nutrient use, microbial ecosystems, animal genetics, and milk composition. Our committee is comprised of dairy scientists with a broad base of specialties that encompass feed analysis, feeding management, ruminal microbial metabolism, intestinal digestion, physiology and metabolism of splanchnic, adipose, muscle, and mammary tissues, endocrine regulation, molecular and cellular biology, and mathematical modeling. Furthermore, in testing and refining nutrition models for the whole country, we must consider the variation in forages and environment that exist among regions. Thus, we have scientists from every dairy region in the country. In addition, the explosion of new information in genomics, gene expression, metabolomics and proteomics requires that we integrate this knowledge into our understanding of metabolic efficiency. Cooperation among stations is required to deal with this information and to solve problems and will have a national impact in understanding and managing the complex interrelationships of nutrient digestion and metabolism in lactating dairy cows.
Likely Impacts. This project exemplifies the proven effectiveness of the cooperative regional approach. As detailed in the "Related Current and Previous Work" section below, results of this cooperative effort have become benchmarks of scientific progress in our discipline and have led to practical feeding recommendations used worldwide. As noted above, this group provided a major contribution to the 2021 version of the National Academies of Sciences, Engineering, and Medicine’s (NASEM's) Nutrient Requirements of Dairy Cattle. Eight of the 12 scientists on the NASEM panel were current or former NC-2040 committee members, and a significant portion of the data used in the latest edition was generated through the collaborative work of NC-2040 committee members. Thus, this committee has had a major impact on improving the biological, economical, and environmental efficiency of the US dairy industry. We continue to recruit and support young scientists to keep the committee current and effective year to year.
Related, Current and Previous Work
General Introduction
Cattle can be extremely efficient producers of quality human food, particularly when considering their ability to utilize feedstuffs that would otherwise be a loss from the food system (Takiya et al., 2019). A major goal in feeding cattle is to find the optimal combination of chemical and physical properties of feeds that provides the proper amount and balance of absorbed nutrients to match the genotype of the cow or herd. This is a challenge because of the tremendous variety of feedstuffs available, the complexity of interactions among feed particles, nutrients and organisms in the rumen, genetic variance within and among herds, and the rapidly changing nutrient requirements of a cow around the time of parturition. The amount and profile of absorbed nutrients in dairy cattle are a function of rumen fermentation and intestinal digestion. What follows is a brief summary of advancements since the last revision in 2017 and plans for continued work.
Primarily under Theme 1
Quantify properties of feeds that determine the availability and utilization of nutrients critical to milk production
A cornerstone of the recent achievements is the 2021 publication of the Eighth Revised Revision of the NASEM Nutrient Requirements of Dairy Cattle (NASEM, 2021). Through painstaking work spanning more than 6 years, this guide was developed by a committee with more than half of members who are current or retired NC-2040 members. This reference has guided nutritionists and other professionals in academia and the dairy and feed industries in developing and implementing nutritional and feeding programs for dairy cattle for many years. Since the Seventh Revision, a great deal of new research was published and a large amount of new information for many nutrients was incorporated in the Eighth Revision (Albornaz et al., 2019; Albornaz et al., 2020; Daley et al., 2020; Daley et al., 2022; Moraes et al., 2018; White et al., 2017a; White et al., 2017b. This book represents a comprehensive review of the most recent information available on efficient, profitable, and environmentally conscious dairy cattle nutrition and ingredient composition.
Work from the CA station showed how rumen microbes ferment carbohydrates in feed. It continues previous work from the CA and OH stations. Specifically, this work showed new biochemical pathways that microbes use when fermenting glucose to acetate, propionate, or butyrate. It found bacteria can use two previously unrecognized enzymes (succinyl-CoA:acetate CoA-transferase and succinyl-CoA synthetase) in forming acetate. Additional work showed importance of two other enzymes (Rnf and Ech) in forming butyrate or propionate. This work involved several techniques, including growth experiments, genomics, proteomics, and enzyme assays. The enzymes revealed by this work are important targets for manipulating fermentation. By overexpressing or knocking out these enzymes, we can control the production of acetate, propionate, or butyrate in the rumen.
WI, MI, IA, FL, and USDA Beltsville have been working on a collaborative, inter-disciplinary effort to improve feed efficiency (Hardie et al., 2017; Lu et al., 2018). The primary overall goal of this project is to improve genomic selection for feed efficiency, towards which we are making notable progress (Khanal et al., 2022). Additionally, as a part of these efforts, we are using sensors and infrared milk spectrum analysis to predict feed intake and determine the relationship between feed efficiency and metabolic health (Martin et al., 2021), feed bunk competition, feeding behavior (Cavani et al., 2022b) and parity (Cavani et al., 2022a). We are also collaboratively working to elucidate tissue-level sources of individual animal variation in feed efficiency through nutrient use efficiency and are working on that collaboratively with Mike VandeHaar and Zhou Zhang at MSU (USDA Foundational grant funded in 2022). Thus far, the collaborative team has identified circulating markers of nutrient use that differ in high and low residual feed intake cows and have identified target pathways (Martin et al., 2021) that will be examined at the tissue level during the USDA-funded project.
DE and Purina collaborated to determine the effects of two prototype feeds to buffer hindgut pH. 10 ruminally cannulated lactating Holstein cows were abomasally infused with either tap water (control) or cornstarch mixed with tap water. Cows received either no dietary buffer (control) or products to buffer hindgut pH. Fecal pH and total VFA, fecal score, and total-tract apparent digestibility were analyzed (Cronin et al., 2022).
Primarily under Theme 2
Quantify metabolic and molecular interactions that alter synthesis of milk components
To identify the unique differences in metabolic efficiency and metabolite profiles among animals, a joint project at MI, WI, IA, and FL collected blood concurrently from the mammary vein and the tail vessel to determine mammary nutrient uptake. We found that Low RFI (feed efficient) cows had enhanced mammary gland proteogenic amino acid (AA; i.e. threonine) extraction and higher mammary gland AA utilization efficiency. Specifically, low RFI cows tended to have a lower ratio of AA uptake to milk output for essential, branched-chain, and total AA. The increase in mammary AA extraction efficiency likely contributes to the improved efficiency of milk protein synthesis in low RFI cows. We also examined the association between feed efficiency and liver function and amino acid (AA) metabolism biomarkers. Using an untargeted metabolomics approach, we quantified 922 metabolite concentrations in the blood from a set of feed efficient (Low RFI) and inefficient (High RFI) dairy cows. From the metabolites identified, concentrations for a biomarker of liver function (bilirubin) and markers of AA metabolism (arginine and creatinine) were distinct between feed efficient and inefficient cows. In conclusion, cows with divergent phenotypes for FE had distinct organ and whole-body metabolism. These metabolic discrepancies between feed efficient and inefficient cattle are impacted by the workload placed on visceral organs and signified by changes in metabolic biomarkers. Therefore, these biomarkers, either alone or combined, could potentially be used as indicators of feed efficiency to differentiate efficient and inefficient lactating dairy cows.
PA, in collaboration with OH, conducted a meta-analysis of the relationship between milk fat concentration and milk fatty acids that are markers of disrupted rumen fermentation and fatty acids made de novo in the mammary gland (Matamoros et al., 2020). This provided mechanistic insight into the impact of diet-induced milk fat depression on variation in milk fat observed in studies and quantitative relationships that can be used to interpret future experiments.
Collaborators at MI and IN evaluated impacts of post-absorptive propionate supply on liver metabolism in an ex vivo system, to better understand impacts of propionate availability on metabolism of other nutrients and energy charge of the liver (Kennedy et al., 2020, 2021).
Primarily under Theme 3
Use knowledge of feed properties and metabolic and molecular quantitative relationships to challenge and refine precision feeding systems for dairy cattle
Mechanistic model development: There is paucity of dynamic, mechanistic model of ruminant digestion and metabolism that can effectively simulate impact of feed additives on methanogenesis. Several members of NC-2040 committee are engaged in conducting experiments under Objectives 1 and 2 to reduce methane emissions from dairy cattle (Vijn et al., 2020). Data collected in those experiments can be integrated into a mechanistic model to a better prediction of the impact of various feed additives. Additionally, continued work with MOLLY, a mechanistic model by members of NC-2040 will aid in development of models that can represent methanogenesis mechanistically.
Assessment of impact of dairy cattle on the environment: The dairy industry has committed to achieving net zero emissions by 2050. This requires assessment of the impact of dairy cattle in a holistic manner taking into consideration the impact from feed production all the way to consumers. Work in CA and PA is analyzing various methods to reduce impacts of dairy on the environment and assess how the industry can achieve net neutrality by 2050 (Appuhamy et al., 2018; Arndt et al., 2022).
Modeling nitrogen, phosphorous, and methane excretion: Empirical model development will continue to predict nutrient and methane emissions from cattle. Work from the CA station in collaboration with PA and other stations will continue to develop models for predicting fecal, urinary, fecal, and milk N output for different classes of cattle (Bougouin et al., 2022).
Objectives
-
Determine how ruminal bacteria can carry out fermentation when they are missing a key enzyme of glycolysis
-
Improve methods for measuring nutrient digestion throughout the gastrointestinal tract in ruminants
-
Evaluate transfer of ruminal bacteria amino acids into milk amino acids
-
Study the impact of feed on production of greenhouse gases and other air emissions
-
Identify mechanisms that explain why some cows are more efficient at using feeds to make milk than others
-
Quantify the impact of Holstein genetics on maintenance energy requirements
-
Improve procedures to quantify mammary uptake of nutrients
-
Evaluate dietary strategies to improve post-absorptive nitrogen efficiency, leading to reduced nitrogen excretion
-
Contribute to development and refinement of database structures to support ongoing modeling efforts
-
Develop mechanistic models describing methanogenesis in the rumen environment
-
Assess how geographic patterns influence dairy management and environmental impact
-
Assess how seasonal patterns influence dairy management and environmental impact
Methods
Methods for Theme 1
Work at the CA and OH stations will continue to show new ways that rumen microbes ferment carbohydrates in feed. Specifically, work is planned to show how bacteria can carry out fermentation when they are missing a key enzyme of glycolysis. The enzyme that is missing is enolase, and previous work from the CA and OH showed many bacteria are indeed missing it. In collaboration with OH, the CA station will use 13C labeled glucose to reveal the biochemical pathway these bacteria use. This work will be important for manipulating fermentation in the rumen to improve digestive efficiency.
Current methods for determining site and extent of nutrient digestion in the ruminant gastrointestinal tract involve cannulation of the rumen and the ileum with collection of digesta from the rumen, the omasum, the ileum (very infrequently done), and the feces. The surgeries are very invasive, which may not be tolerated by the general public in the future, and the resulting data have as much as 20% error of measurement, which hampers scientific progress. Less invasive, more precise methods of assessing absorbed nutrient supplies are needed to address these concerns. One alternative approach that has been used in selected cases is based on the use of isotopic tracers. For the few nutrients assessed in this manner, the errors of measurement are about half of those when using the above classical approaches. Cargill, VA, WI, DE, OH will collaborate to employ isotopic methods to quantify nutrient digestion for several classes of required nutrients that have not yet been evaluated in this manner. Existing and alternative in vitro ingredient digestibility methods will also be evaluated in comparison to in vivo observations.
An isotopic method is the only approach to determine the contribution of bacterial amino acids to milk amino acids. Bacterial amino acids in the rumen can be labeled through ruminal infusion of 15N-isotope, which will result in 15N enrichment of milk amino acids because of utilization of 15N-labeled bacterial amino acids for milk. The labeling of 15N in rumen bacteria and then milk will be conducted under various feeding regimes (OH and PA). The enrichment of 15N in sample amino acids will be used to calculate rumen bacterial contribution to milk amino acids under various feeding conditions. Furthermore, the pattern of 15N enrichment of amino acids over time will be analyzed using compartment modeling to better understand the fate (transfer, utilization, and excretion) of bacterial protein in lactating dairy cows.
CA, PA, VA, MI, OH, Purina, and WI will use individual animal gas flux measurements to determine enteric methane emissions from cattle fed different diets. Methane flux data will be used to assess whether individual cow variation in feed efficiency may be due in part to differences in methane production. It will also be used to determine dietary effects on methane release; for example, differences in fiber digestibility or dietary fat content may alter methane production. Gas emissions from dairy production are closely related to feeds fed to cows. Historically, dairy nutrition has been focused mainly on determining effects of feeds or feed additives on enteric gas emissions (e.g., CH4 and CO2). However, feeds fed to cows also alter manure characteristics and, therefore, gas emissions from manure, which should be considered when environmental impacts of feeds are evaluated in addition to enteric emissions. Diets from various feed ingredients and proportions with feed additives will be evaluated to measure enteric greenhouse gas emissions and manure will be collected and determined for manure characteristics and manure gas emissions. Manure gas emissions (greenhouse gases, ammonia, hydrogen sulfide) will be determined using a laboratory setup of manure incubation. Results from these investigations will contribute to the body of knowledge but will also feed into databases used in theme 3 objectives to improve modeling of greenhouse gas emissions from dairy farms.
Methods for Theme 2
WI and MI will be working collaboratively to elucidate tissue-level sources of individual animal variation in feed efficiency through nutrient use efficiency. Thus far, the collaborative team has identified circulating markers of nutrient use that differ in high and low residual feed intake cows and have identified target pathways (Martin et al., 2021) that will be examined at the tissue level during the USDA-funded project. The team will also attempt to use sensors to enhance our ability to predict the intake of individual cows within a group-fed pen of cows. Dairy cows between 50 and 200 DIM will be enrolled in studies with treatment periods of at least 42 d in length. All cows will be fed to meet or exceed the requirements of a 650-kg lactating cow based on NASEM (2021), and at least 10 cows per diet will be included in a cohort to provide a basis for comparison in determining feed efficiency. Individual dry matter intake (DMI) will be determined daily, as well as milk yield daily, milk composition twice weekly, and body weights (BW) for 3 consecutive days at the beginning, middle, and end of the period. Blood samples will be taken at the beginning and end of the study per specific objectives and when pertinent, liver and muscle biopsy samples are collected by biopsy after the feed intake period has concluded. All methods have been described previously (Martin et al., 2021).
Using data from experiments described above, MI, WI, MN, and NE will also work on quantifying differences in maintenance requirements of modern Holsteins. Maintenance is a fixed cost that reduces overall efficiency and estimates of maintenance energy requirements were increased in the recent NASEM Nutrient Requirement of Dairy Cattle, based on decades-old data. Genetic progress is occurring rapidly and this work is essential to understanding the impacts on fundamental cellular and organism level regulation.
Several approaches will be used to assess post-absorptive disposition of specific amino acids, in an effort to better understand utilization of amino acids and which amino acids might improve overall N efficiency (WI, VA, MI, OH, IA). Combinations of various rumen-protected amino acids and nitrogen free ketoacids will be evaluated under different dietary regimes (e.g., dietary protein and energy concentration) on mammary uptake and utilization for milk to increase nitrogen use efficiency. In addition, various profiles of post-absorptive amino acids will be provided through infusion of amino acids and corresponding ketoacids to understand the ideal amino acid profile for greater milk protein synthesis and less nitrogen excretion in urine.
Mammary aterio-venous difference (AVdiff) approaches provide a direct observation of mammary uptake that is essential to understanding mammary metabolism. Use of the method is limited by technical issues related to sample collection, metabolite analysis, and experimental variation. Investigators at PA, WI, VA, MI will collaborate to develop methodological improvements and establish recommended procedures to allow standardization across experiments and reduce technical variation. WI and MI will collaborate to elucidate differences in mammary nutrient extraction between efficient and inefficient cows. The team will explore circulating concentrations and mammary uptake of individual fatty acids and amino acids to determine if differences in mammary uptake of these key nutrients influence feed efficiency. The team will determine blood flow, which will add precision to crude AVdiff estimates of mammary uptake. This work will provide novel insights on potential contributions of mammary gland uptake to differences between efficient and inefficient cows.
Quantification of amino acids essential for milk protein synthesis in tail vessel, mammary vein, and milk will be used to determine efficiency of AA uptake and incorporation into blood in efficient and inefficient cows. Additionally, quantification of phenylalanine (Phe) and tyrosine (Tyr) in plasma and milk samples by the same method will allow for determination of mammary plasma flow (MPF) across the mammary gland. Calculation of MPF will be done as previously described [12,58]; MPF (L/h) = [milk Phe + Tyr output μmol/h)]/[AV Phe + Tyr difference (μmol/L)] assuming a 3.37% contribution from blood-derived proteins. Mammary AVdiff will be calculated as tail vessel minus the mammary vein concentration and percent disappearance is calculated as the AVdiff divided by the tail vessel concentration. Mammary clearances of metabolites and AA will be calculated as (L/h) = (AV difference × MPF)/venous concentration [59]. Mammary uptakes (mmol/h) of metabolites and AA will be determined as the product of the respective plasma AV differences and MPF. Positive and negative AVdiff represent net mammary and release of metabolites, respectively.
Methods for Theme 3
Mechanistic model development: The NC-2040 committee will use R to develop mechanistic models capable of representing methanogenesis. The R language is a free, universal, and powerful tool, simplifying collaboration across institutions and the private sector. The CA station will use data collected from experiments conducted at CA, PA, VA, MI, Purina, and WI.
Assessment of impact of dairy cattle on the environment: The CA station will use the new FAO guidelines developed under the Livestock Environmental Assessment Performance Partnership (LEAP) to conduct Life Cycle Assessment (LCA) in dairy cattle. Inputs to the LCA will come from data collected by members from PA and other stations. In addition, attributional LCA are planned to assess dairy production systems and how they can move towards net zero.
Modeling nitrogen, phosphorous, and methane excretion: The CA station will develop empirical models to predict nutrient excretion and methane emissions with R statistical software. The metafor package in R in particular will be used to develop meta-analyses.
Development of intake and mitochondrial model: The CA station will use weekly individual cow intakes and milk production over time from members of the NC-2040 committee to develop an intake model. The model is based on the changes in distribution of cows DIM from week to week in the pen. The DIM makeup of the pen is modeled after pen sizes and DIM makeups over seasons from the commercial dairy data mentioned in objective 1. The CA station will use mitochondrial data from objective 2 to identify the most critical mitochondrial enzymes for metabolic processes and current predictions of substrates for mitochondrial energy production to develop a ‘mitochondrial type’ model to be incorporated into the Molly model.
Measurement of Progress and Results
Outputs
- Improved understanding of fundamental metabolic processes (including methane production) in ruminal bacteria and the utilization efficiency of transfer of specific amino acids to milk production in the cow
- Data on enteric methane production as influenced by cow genetics and dozens of diets
- Improved techniques for accurately determining gut absorption and mammary uptake of specific nutrients that limit productivity and health of dairy cattle
- Mechanistic insights into what physiological differences explain genetic differences in feed efficiency among dairy cattle
- Unique data on how diets influence efficiency of amino acid use post-absorption
- Robust model of methane production, developed from studies carried out at numerous research facilities
- Models describing regional and seasonal impacts on environmental impacts of dairy production
Outcomes or Projected Impacts
- In combination, the model providing mechanistic predictions of enteric methane production and the models describing regional and seasonal impacts on greenhouse gas production will dramatically improve our ability to predict how diets will influence the global warming potential of diets on specific farms.
- Development of better methods to assess the disposition of nutrients fed to cattle (manure vs. urine vs. milk vs. retention) will allow us to continue to refine requirements and recommendations for precision nutrition of dairy cattle, improving economic and environmental sustainability of the dairy industry.
- Understanding the physiological basis for genetic variability in feed efficiency will lead to new testable hypotheses around dietary factors that may be tailored to cows with different genotypic and phenotypic make-up.
Milestones
(2024):An initial round of studies assessing methane production and partitioning of environmentally sensitive nutrients will be carried out in 2023-2024. At the same time, work will begin on a formal database structure to simplify collaborative data sharing. These efforts early in the 5-year period will allow for initial data to flow into modeling efforts described under Theme 3, providing 3+ years for model development to be accomplished by 2028. Once the data pipeline and model structure is developed, new data will be easily incorporated into model testing and iterative improvement efforts.Projected Participation
View Appendix E: ParticipationOutreach Plan
Our first outreach goal is to disseminate novel research findings to a broader scientific audience. Our scientists nearly all disseminate our research results at the American Dairy Science (ADSA) annual meetings to other scientists and technical specialists, including a substantial number who work directly with dairy farms in the US and globally. Members of this committee are frequently invited to speak at national and international conferences; in fact, every major animal nutrition conference in the US (Cornell, Minnesota, California, Tri-State, Four-State, Southwest, Pacific Northwest, Intermountain) routinely has committee members presenting information to consultants, nutritionists and industry members. A crude estimate is that committee members collectively address audiences in excess of 5,000 people annually, and these opportunities provide a key pathway to transmit new insights derived from NC-2040 research to the dairy industry.
In addition, fundamental collaborative research is used to improve and expand the development, refinement and use of nutritional decision support systems, or models, such as the NASEM model or the research model, Molly. This is truly the ultimate goal, that our research leads to specific, definable biomathematical equations that apply to the nutrition, metabolism, and thus efficiency and productivity of dairy cattle.
Finally, each committee member works in a state with extension faculty, and several members also have an extension appointment. The members of this committee routinely engage in conversations with our producers and allied industry members to move forward effective and applicable research and extension programs. Information from this committee has been and will continue to be disseminated to practicing dairy nutritionists, veterinarians, extension specialists, farmers, and other scientists through regional nutrition conferences, trade and extension publications, electronic media, and applied computer ration balancing programs.Organization/Governance
The technical committee will have a chair, secretary, and regional administrative advisor. The executive committee will consist of these three persons and the previous chair and will be the official nominating body. The chair and secretary will be elected by the voting members from within their ranks. The chair is responsible for planning and conducting the annual meeting, for submission of the project annual report, and for facilitating and ensuring effective communication and cooperation among participants. The secretary is responsible for recording minutes and distributing them prior to the chair preparing the annual report. Individual station members are responsible for preparing brief annual reports and distributing them to other participants two weeks prior to the annual meeting. Additional committees, composed of voting and non-voting members, may be appointed as needed to solve particular technical problems, to assist in communication within the project, or to report project findings to other interested parties.
Literature Cited
Committee members (including previous members who have recently retired) bolded
Albornoz RI, Harvatine KJ, Allen MS. Diet starch concentration and starch fermentability affect energy intake and energy balance of cows in the early postpartum period. J Dairy Sci. 2019 Jun;102(6):5161-5171. doi: 10.3168/jds.2018-15634.
Albornoz RI, Sordillo LM, Contreras GA, Nelli R, Mamedova LK, Bradford BJ, Allen MS. Diet starch concentration and starch fermentability affect markers of inflammatory response and oxidant status in dairy cows during the early postpartum period. J Dairy Sci. 2020 Jan;103(1):352-367. doi: 10.3168/jds.2019-16398.
Appuhamy JADRN, Moraes LE, Wagner-Riddle C, Casper DP, Kebreab E. Predicting manure volatile solid output of lactating dairy cows. J Dairy Sci. 2018 Jan;101(1):820-829. doi: 10.3168/jds.2017-12813.
Arndt, C., A. N. Hristov, W. J. Price, S. C. McClelland, A. M. Pelaez, S. F. Cueva, J. Oh, J. Dijkstra, A. Bannink, A. R. Bayat, L. A. Crompton, M. A. Eugene, D. Enahoro, E. Kebreab, M. Kreuzer, M. McGeek, C. Martin, C. J. Newbold, C. K. Reynolds, A. Schwarmm, K. J. Shingfield, J. B. Venemann, D. R. Yanez-Ruiz, and Z. Yu. 2022. 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. PNAS 119:20 e2111294119. DOI: https://doi.org/10.1073/pnas.2111294119.
Bougouin A, Hristov A, Dijkstra J, Aguerre MJ, Ahvenjärvi S, Arndt C, Bannink A, Bayat AR, Benchaar C, Boland T, Brown WE, Crompton LA, Dehareng F, Dufrasne I, Eugène M, Froidmont E, van Gastelen S, Garnsworthy PC, Halmemies-Beauchet-Filleau A, Herremans S, Huhtanen P, Johansen M, Kidane A, Kreuzer M, Kuhla B, Lessire F, Lund P, Minnée EMK, Muñoz C, Niu M, Nozière P, Pacheco D, Prestløkken E, Reynolds CK, Schwarm A, Spek JW, Terranova M, Vanhatalo A, Wattiaux MA, Weisbjerg MR, Yáñez-Ruiz DR, Yu Z, Kebreab E. Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis. J Dairy Sci. 2022 Sep;105(9):7462-7481. doi: 10.3168/jds.2021-20885.
Cavani, L., K. Parker Gaddis, R. Baldwin, J. Santos, J. Koltes, R. Tempelman, M. VandeHaar, M. Martin, H. White, F. Penagaricano, K. Weigel. 2022a. Impact of parity differences on residual feed intake estimation in Holstein cows. JDS Communications. Under Review.
Cavani, L., W. E. Brown, K. Parker Gaddis, R. Tempelman, M. VandeHaar, H. White, F. Peñagaricano, and K. Weigel. 2022b. Estimates of genetic parameters for feeding behavior traits and their associations with feed efficiency in Holstein cows. J. Dairy Sci. 105:7564-7574. doi: 10.3168/jds.2022-22066.
Cronin, S., M. Smith, C.M.K. Bradley, V. Daley, F. Gadeyne, M. Bustos, and T. F. Gressley. 2022. Evaluating hindgut buffers under high-starch diet conditions in lactating Holstein cows. J. Dairy Sci. 105 (Suppl. 1): 329 (Abstr.).
Daley VL, Armentano LE, Hanigan MD. Models to predict milk fat concentration and yield of lactating dairy cows: A meta-analysis. J Dairy Sci. 2022 Oct;105(10):8016-8035. doi: 10.3168/jds.2022-21777.
Daley VL, Armentano LE, Kononoff PJ, Hanigan MD. Modeling fatty acids for dairy cattle: Models to predict total fatty acid concentration and fatty acid digestion of feedstuffs. J Dairy Sci. 2020 Aug;103(8):6982-6999. doi: 10.3168/jds.2019-17407.
Hardie LC, VandeHaar MJ, Tempelman RJ, Weigel KA, Armentano LE, Wiggans GR, Veerkamp RF, de Haas Y, Coffey MP, Connor EE, Hanigan MD, Staples C, Wang Z, Dekkers JCM, Spurlock DM. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. J Dairy Sci. 2017 Nov;100(11):9061-9075. doi: 10.3168/jds.2017-12604.
Kennedy KM, Donkin SS, Allen MS. Effects of propionate concentration on short-term metabolism in liver explants from dairy cows in the postpartum period. J Dairy Sci. 2020 Dec;103(12):11449-11460. doi: 10.3168/jds.2020-18914.
Kennedy KM, Donkin SS, Allen MS. Effect of uncouplers of oxidative phosphorylation on metabolism of propionate in liver explants from dairy cows. J Dairy Sci. 2021 Mar;104(3):3018-3031. doi: 10.3168/jds.2020-19536.
Khanal, P., K. Parker-Gaddis, M. J. VandeHaar, K. A. Weigel, H. M. White, F. Peñagaricano, J. E. Koltes, J. E. P. Santos, R. L. Baldwin, J. F. Burchard, J. W. Dürr, P. M. Van Raden, and R. J. Tempelman. 2022. Multiple trait random regression modeling of feed efficiency in US Holsteins. J. Dairy Sci. 105:5954-5971. doi.org/10.3168/jds.2021-21739.
Lu Y, Vandehaar MJ, Spurlock DM, Weigel KA, Armentano LE, Connor EE, Coffey M, Veerkamp RF, de Haas Y, Staples CR, Wang Z, Hanigan MD, Tempelman RJ. Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. J Dairy Sci. 2018 Apr;101(4):3140-3154. doi: 10.3168/jds.2017-13364.
Martin, M. J., R. S. Pralle, I. R. Bernstein, M. J. VandeHaar, K. A. Weigel, Z. Zhou, and H. M. White. 2021. Circulating metabolites indicate differences in high and low residual feed intake Holstein dairy cows. Metabolites. 11:868. doi: 10.3390/metabo11120868.
Matamoros C, Klopp RN, Moraes LE, Harvatine KJ. Meta-analysis of the relationship between milk trans-10 C18:1, milk fatty acids <16 C, and milk fat production. J Dairy Sci. 2020 Nov;103(11):10195-10206. doi: 10.3168/jds.2019-18129.
Moraes LE, Kebreab E, Firkins JL, White RR, Martineau R, Lapierre H. Predicting milk protein responses and the requirement of metabolizable protein by lactating dairy cows. J Dairy Sci. 2018 Jan;101(1):310-327. doi: 10.3168/jds.2016-12507.
NASEM. 2021. Nutrient Requirements of Dairy Cattle, Eighth Revised Edition. The National Academies Press, Washington, D.C.
Takiya, C.S., C.M. Ylioja, A. Bennett, M.J. Davidson, M. Sudbeck, T.A. Wickersham, M.J. VandeHaar, and B.J. Bradford. 2019. Feeding dairy cows with “leftovers” and the variation in recovery of human-edible nutrients in milk. Front Sustain Food Syst. 3:114. doi: 10.3389/fsufs.2019.00114.
Vijn S, Compart DP, Dutta N, Foukis A, Hess M, Hristov AN, Kalscheur KF, Kebreab E, Nuzhdin SV, Price NN, Sun Y, Tricarico JM, Turzillo A, Weisbjerg MR, Yarish C, Kurt TD. Key considerations for the use of seaweed to reduce enteric methane emissions from cattle. Front Vet Sci. 2020 Dec 23;7:597430. doi: 10.3389/fvets.2020.597430.
White RR, Roman-Garcia Y, Firkins JL, VandeHaar MJ, Armentano LE, Weiss WP, McGill T, Garnett R, Hanigan MD. Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate. J Dairy Sci. 2017a May;100(5):3591-3610. doi: 10.3168/jds.2015-10800.
White RR, Roman-Garcia Y, Firkins JL, Kononoff P, VandeHaar MJ, Tran H, McGill T, Garnett R, Hanigan MD. Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 2. Rumen degradable and undegradable protein. J Dairy Sci. 2017b May;100(5):3611-3627. doi: 10.3168/jds.2015-10801.