Brief Summary of Minutes of Annual Meeting

Summary of Minutes of Annual Meeting (October 21-22, 2008): A. Administration: Introductions and administrative details 1. Election of new officers. Promotion of Current Secretary to Chair 2008-2009: Jim Fadel New Secretary 2008-2009: Barry Bradford Next years meeting for NC-1040: Chicago, near Ohare, October 26 and 27, 2009. If these dates are unavailable, October 19 and 20 will be considered. Gale Bateman will work with Jim Fadel to organize next years venue and meeting. 2. USDA representative, Charlotte Kirk-Baer News from the US Department of Agriculture. The current budget is under continuing resolution. Under the new Farm bill, CSREES no longer exists, and will be replaced with the National Institute of Food and Agriculture (NIFA). Agriculture and Food Research Initiative (AFRI) now replaces the National Research Institute, and essentially combines the NRI and Initiative for Future Agriculture and Food Systems (IFAFS) programs into one. Funding under NIFA will be split 60% to fundamental and 40% to applied research. Authorization has been given for up to $700 M annual funding, with not less that 30% for integrated projects The new NIFA Agency head will be appointed by the President for a 6 year term. One advantage of this new funding organization is that applied, fundamental and extension research can be applied for as integrated or individual project proposals, which was not available before. 3. NC Administrative Advisor, David Benfield NIFA replaces CSREES but ARS will remain as is for the present. Integrative proposals may get higher funding although funding is usually $350,000. In the NC annual report, it is recommended to add leverage or grant funds acquired outside of the project which support research conducted under project objectives. B. Station Reports 1. Lou Armentano (University of Wisconsin, Objective 1) Study One: Dry fractionation products. Dry milling ethanol plants where the endosperm is extracted for ethanol production, often leaves behind starch contamination in the bran and germ. Diets were formulated with high and low forage, and either corn or carn brad from the dry mills, and milk production and diet component digestibility estimated: HFC, High forage corn HFCB, High forage corn bran [HFC plus corn bran minus corn] LFC, Low forage corn LFCB, Low forage plus corn bran (minus corn) [LFC plus corn bran minus corn] Diets were fed to cows and heifers in six Latin Squares (½ cows and ½ heifers). NFC (DM-cp-ash-fat-ndf) was lower with corn bran vs corn; ADF was higher with corn bran. Linear factors were used to determine digestibility, which assumes no associative effects, starch is low in corn bran. Digestibility estimates are not yet complete. Study Two: Conducted to evaluate the effect of dietary supplementation of free vegetable oil with or without a commercial antioxidant. (Agrado plus). Used different plants with oil compositions. Lou would have liked to use pure oils. Treatments were: Linseed (LNSD) oil, palm (PALM), Corn oil (CORN), high-oleic safflower (OSAF); high-linoleic safflower (LSAF), control (CTRL) with and without the antioxidant. Cow performance: Fat yield decreased from CTRL to OSAF to LNSD to CORN to LSAF but not all significantly different. CORN and LSAF are the most fat depressing. No effect of anti-oxidant. No main effects. Planned Research: We want to use in situ bags to predict flow of digestible protein and digestible lysine to small intestine. In the past others have selected the 16 hr time point to get a bag where total cp in bag represents RUP flow and digestible cp in bag (based on enzymatic digestion) is an estimate for digestible protein flow to small intestine. We questioned the use of 16 h based on NRC kp estimates and the effect of kd on what time bag would give a residue equal to the predicted RUP. The chart shows the relationship and is based on the equation that the time of equivalence for a bag residue to equal predicted RUP = (ln (kp/(kp+kd))/-kd which is derived from setting C+B*exp(-kd*t) = C + B (kp/kp+kd) and solving for time. The take home message is that the bag residue that gives a value the same as predicted RUP is always at a time less than 1/kp and is dependent on the kd of the sample. We plan to concentrate samples in the time periods that the range of kd and kp cover, which would be less than 20 h in most cases but to be able to adjust for time within this time range. 2. Gale Batemam (Akey, Objective 1) Physically effective NDF (peNDF) is a physical property that (partially) defines the role of a feed in maintaining rumen function. Objective: Develop a method for estimating peNDF that yields values that are comparable to those from Yang and Beauchemin (2006). In other words, develop a reference method to quantify peNDF. TMR samples (n = 26) from the Upper Midwest and New England states were evaluated. Particle size was determined using the Penn State Particle separator (PSPS) (4 screen, not 3 screen). DM content of each PSPS fraction was determined. peNDF was calculated from the Yang and Beachemin (2006) equations and this would be the response or dependent variable. Excel Solver was used to determine coefficients of multiple regressions. The 4 screen PSPS reduced the variation around the prediction of the peNDF over that when the 3 screen PSPS was used. The Z-box was not used because Akey only has data from one location and they used the PSPS because they have data across the US. 3. Jong-Su Eun (Utah State University, Objective 1) Research focus: Investigate the impact of various ingredients and feed additives; Development of supplementary strategies, Use of low quality forage; Development of nutritional management plan to reduce nutrient excretion. Uses in vitro culture systems. Study: Safflower seed for dairy cow diets. Safflower seed gas a higher digestibility than cottonseed. Nutrasaff is a new variety which has higher fat and lower fiber, and wsa used to substitute for cottonseed. MUN was depressed by feeding the Nutrasaff, but no change in total tract protein digestibility was observed. Trans-11 18:1 percent in milk fat was increased by addition of safflower to the diet. A linear increase in CLA cis-9, trans-11 percent in milk was observed with safflower addition. Current research: Effects of condensed tannins on microbial metabolism using continuous culture. Effects of Clinoptilolite zeolite on ruminal fermentation and lactation performance will be evaluated. 4. Jeff Firkins (The Ohio State University, Objective 1) Protozoa Work: How much are actually in the rumen? Maybe just 20% of the total microbial mass compared to traditional literature values of 50%. Aim is to understand the mechanisms of chemotaxis by comparing Isotrichs (holitrichs) to entodinomorphs. Holotrichs vary chemotaxis towards gradients of glucose and amino acids via the phosphatidylinositol 3-P kinase (PI3K) signaling pathway which is well described in parasitic protozoa or environmental free-living ciliates. PI3K is also a component in insulin signaling. Thus, the chemotaxic mechanisms of protozoa functions similar to the insulin mediate mechanism of glucose uptake in eukaryotic systems. Wortmannin is an inhibitor to PI3K, and PI3K works through the TOR signaling pathway to stimulate transcription in protozoa. Study One. The idea is that holotrichs possess this chemotactic mechanism whereby they rise to the top of the rumen, take up glucose and then descend to the bottom of the rumen. This mechanism would mean that the holotrichs stay in the rumen longer and that the entodinomorphs leave the rumen quicker. To test this mechanism, a substrate gradient system was developed using glass capillary tubes. Treatment tubes contain different concentrations of glucose, and protozoa swim into the tube where they are enumerated. As negative control, tubes contain only saline. Both species of protozoa have the same opportunity to swim into the tube and holotrichs were much higher in number than entodinomorphs as the glucose levels were increased (to 100 mM). It is thought that the holotrichs take up the glucose so the entodinomorphs are left without substrate. Study Two. Wortmannin was added as an inhibitor of PI3K to test the role of PI3K in the glucose sensing and transport of glucose by protozoa. Holotrichs (Isotrichs) have chemotaxic and stay in rumen longer and Entodinomorphs leave with the feed while Isotrichs migrate upward to feed on glucose and then sink ventrally. They preferentially stay in the rumen. Study Three. Dose-response with Insulin to test recovery from Wortmannin inhibition. Future Questions: Is chemotaxic mechanism really due to glucose? Could it be due to amino acids? What about maltose since it is similar to glucose? 5. Arnold Hippen (South Dakota University, Objectives 1 and 2) Corn co-products and milk fatty acid responses. Comparison of oil availability on milk fatty acids. Treatments were: Control, corn germ, dry distillers grains with soluble, and corn oil. Feeding the corn germ at 21% of diet did not reduce milk fat compared to control. No differences in milk yield. For milk fatty acids, the CLA isomers t10, c12 and c9, t11 were progressively increased by feeding CG, DG, and oil compared with control. It was concluded that the lack of milk fat depression when corn germ was added may be attributed to the protection of the oil in the germ whereas a decrease in milk fat percentage for cows fed DG demonstrated a greater ruminal availability of oil in DG . Corn germ from pre-distillation fraction of corn grain for ethanol production may be fed at 14% of diet DM without negative effects on milk fat and minimal production of milk trans and CLA isomers. Feeding equivalent amounts of oil in distiller grains or as free oil will decrease milk fat production and increased trans and CLA isomerization of fatty acids. Replacing starch from corn with fiber and fat from corn distillers grains in diets of lactating dairy cows did not effect milk yield or milk components. An increase in feed efficiency was noted when dietary starch was decreased from 29 to 20% of DM and inclusion of DG increased proportionally. 6. Shawn Donkin (Prudue, Objectives 1 and 2) Objective 1: Determine the feeding value of wet distillers grains (WDGS) for lactating dairy cows when co-ensiled with corn silage or haycrop silage. Co-ensiling appeared to work well but was difficult to do because of mixing issues. Objective 2 Studies. Identification of a glycerol transporter in rumen epithelium. Urea is not dependent on a transporter but glycerol has a transporter. Some glycerol appears to be transported across the rumen wall but the proportion transported across the membrane without a transporter is unknown. Effects of propionate supply in vivo on PEPCK expression. The role of propionate in regulation of PEPCK gene expression in the liver was investigated. Using heifer calves, either acetate, propionate, phlorizin, or saline was infused into the jugular vein. Role of Vitamin D in insulin resistance and adipose tissue metabolism of transition dairy cows. 7. Donald Beitz (Iowa State University  Objective 2) Genetic regulation of the healthfulness of beef and dairy cow milk fatty acid composition. Single nucleotide polymorphisms (SNPs) in the thioesterase (TE) domain of fatty acid synthetase (FAS) and in diglycerol acyltransferease-1 (DGAT1) were found to relate to fatty acids and profiles that have healthful benefits. Future work will try to identify SNPs that could be used in a breeding program to change the genetic profile and hence the fatty acid profile of milk fat. 8. Brian Bequette (University of Maryland, Objective 2) Determine methionine and choline methyl group metabolism in lactating dairy cows supplemented with or without the protected choline product Reashure@. Question: Does supplemental dietary choline spare methionine by increasing homocysteine methylation to reform methionine, and thus increase the net supply of methionine for milk protein synthesis. Results: Not much methyl-group labeling of methionine from infused labeled choline. Remaining Questions: How much methionine gets remethylated? How much of methionine methyl groups derive from choline? Determine the limiting factors the prevent urea N recycling and capture of N in the rumen. 9. Barry Bradford (Kansas State University, Objectives 1 and 2) Objective 1 Study. Determine if molasses can prevent milk fat depression when added to distillers grains (with solubles) diets. Milk fat % increased with molasses substitution, but milk yield was not affected. Short and medium chain fatty acid milk yields increased but no difference in yields on C16 and long chain fatty acids were observed. Molasses addition appears to enhance ruminal biohydrogenation because trans 10-C18:1, and total trans C18:1 were decreased. Milk protein, milk lactose and MUN were decreased with molasses addition. Objective 2 Study: Understanding the mechanisms that lead to fatty liver formation. Effects of exogenous tumor necrosis factor (TNF) alpha on hepatic nutrient metabolism. Why do animals with higher triglycerides in livers have lower glucose production? Fatty livers are associated with lower glycogen. Is TNF a factor causing or involved in initiating bovine fatty liver? TNF is a cytokine that is released from the adipose and acts on the liver. To investigate these questions, 15 late-lactation Holstein cows were infused IV with TNF or saline. TNF did not cause lipolysis. TNF did cause increase in lipid accumulation in liver. In the liver of TNF infused cows, gene expression of CD36 increased 220%, CPT1 decreased 30%, AGPAT increased 550%, and PEPCK decreased by 40%; all are consistent with an increase in liver triglyceride storage and decreased gluconeogenesis. Measurement of glucose turnover showed a non-significant decrease of 18% with TNF infusion. Preliminary data supports the idea that inflammatory pathways can lead to fatty liver. 10. Mike VandeHaar (Michigan State University, Objectives 2 and 3) Sustainable agriculture. Sabbatical at Wageningen University. Learned about life cycle analysis and optimization for sustainability. Conventional dairies were just as environmentally sustainable per kg milk as organic farms and used less land. Objective 2 Study. The MSU station has done some work on trying to understand the molecular controls of the efficiency of N use in lactating cows. Samples of liver tissue from cows fed 11, 15, or 19% CP diets for 12 days in a replicated 3 x 3 Latin square were analyzed with the bovine metabolism focused microarray and by Q-PCR for transcripts of 20 different proteins. No changes in transcripts, even for the urea cycle enzymes, were seen, despite major changes in the efficiency of protein use. The MSU station would next like to determine if some cows use protein more efficiently than others and if this is a heritable trait. For the past 50 years, MSU has mostly selected cows for high milk production in an environment where protein is almost never the limiting nutrient. The group is looking for other stations who would be interested in partnering in this effort. Methods would be to feed low protein diets to determine which cows were more efficient. Most semen companies have started using SNP chips for early selection of sires. SNP chips would enable us to also select for animals that use protein efficiently if protein efficiency is a heritable trait. Bioinformatics likely will be an important part of this project. Objective 3 Work. Spartan Dairy 3 program is a stand-alone database program that has been used in classes for past year but is not yet released. A decision was made to have a linear program and this will delay release. The program is based on an excel model that includes the complete NRC feed library, NRC nutrition model accompanied by edits to the NRC model (both can be viewed), and a working linear program. Among some of the changes to the NRC model are lower digestibility discount at high intakes, a lower energy value for digestible protein, adjustments to NDF digestibility that are independent of lignin concentration, lower digestibility of fat for most feeds, a smaller fat-correction for TDN in estimating microbial protein synthesis, a lower RDP requirement, and lysine and methionine supply based on the sum of microbial and RUP supplies. In most cases, the original 2001 NRC calculations can also be observed. Additions to the model include tracking of Forage NDF, Effective NDF, carbohydrate fractions, lipid fractions for saturated, mono-, and poly-unsaturated fatty acids and biohydrogenation potential, estimated N and P excretion, environmental adjustments, and the 1989 NRC energy and protein system. Some of the equations in the NRC 2001 have not been thoroughly investigated and little support is given for them. The excel model format allows easy comparison of different systems. For example, the N-potential MCP yield in NRC 2001 is simply 0.85*RDP Supply. In the 1989 NRC, it was 0.9*(RDP supply + 0.15*CPSupply. Thus, the 1989 NRC essentially did a double counting for RDP, presumably to account for recycling of N to the rumen. Consequently, the RDP requirement in NRC 2001 is Energy-potential MCP/0.85, whereas in NRC 1989 it was Energy-potential MCP/0.9-0.15*CPsupply. This results in a substantial increase in the RDP requirement of the NRC 2001 system, from 1.75 kg/d to 2.40 kg/d for a cow producing 40 kg of milk. The Spartan Excel spreadsheet is now in its 200th iteration and would be available for the NC-1040 group as a resource for testing new ideas. Maybe we can find cows that use protein more efficiently. We have never selected for protein efficiency. Need to feed low protein diets to determine which cows were more efficient and maybe over long period of time&maybe six weeks. In Netherlands they are using SNP chips to choose sires. Bioinformatics will be important in the future. 11. Mark Hanigan (Virginia Polytechnic Institute & State University, Objectives 2 & 3) Objective 2 Study. Effects of insulin and essential amino acid on protein synthesis signaling. Energy efficiency does not seem to work as you increase CP intake. NRC over predicts response to MP intake. When MP intake is suboptimal, cows lose milk but not as much as the NRC predicts. Cows will respond to energy intake even when they are deficient in protein which is not consistent with the single limiting nutrient paradigm used in the NRC and most other requirement models. Mammalian target of rapamycin (mTOR) seems to be central in amino acid utilization (Ruis et al., 2008). Cell culture work has been conducted to examine the effects of individual amino acids and insulin on mTOR and S6 phosphorylation in MAC-T Cells. These in vivo results are similar to in vitro in that the phosphorylation state of protein synthesis initiator complex proteins are phosphorylated in response to insulin even when a single AA is clearly limiting. Objective 3 Work. Added better representation of gestation in the Molly model and a better way to represent hormones. Prediction errors for Molly 2007 after fitting to an extended Lactation data set (Hanigan et al., 2007). High slope bias for glucose and high RMSPE for Blood NEFA. Molly, no reproductive tract per se and used only energy but not amino acids. Hormonal representation in Molly is a ratio of current glucose concentration to reference value. Revised forms: H anab1 = Cgl/Kanb1 ^Theat1 H cat2= Kcat1/Cgl^Theat2 Subtract off uterus and fetus. Gestation equations based on Koong et al., 1975 and used Alan Bells data, then adjusted amino acid equations by subtracting the costs from fetus. This required re-estimation of some of parameters. Better improvement but mainly from the hormone improvement not from fetal development. Insulin sensitivity of adipose tissue. Now you just need to change the sensitivity over lactation or over time because it does not stay the same over the lactation. John has been doing something like this. Maybe we need to use a dataset to measure the new sensitivity over time in adipose. Ruminal starch, fiber, and protein digestion parameter estimates for Molly. Objective was to derive better rate constants in model. Problem of having different vectors for to account for experiment to experiment variation to account for different experiments as St-Pierre suggested in his meta-analyses. 1) Find out bias for input and then correct input for model; decreased in bias by about 50% with NRC data 2) Then determine bias from duodenal flow 3) Kd = 24/RRT * ln(F_RuNut,Fd/F_Nut,Fd)+Adjk RRT = 8 hours for concentration and 18 hours for forages Problem is a huge mean bias in pH. Used the readjusted pH, but this resulted in large slope bias in pH. The ruminal VFA concentration predictions were much better. So the pH prediction is apparently due to an inadequate representation of pH. 12. Jim Fadel (University of California  Davis, Objective 3) Two areas of research were undertaken during the last year related to this project. We are trying to develop better partitioning of maintenance using new ATP yields based on several datasets. The current progress in this project is mainly working with a software company to develop a method to do global sensitivity analyses using acslXtreme. Much progress has been made over the last 6 months and hopefully within the next year a beta version will be out. The global sensitivity analyses will be one of the first steps in identifying important parameters prior to working with the various datasets to estimate new parameters. This tool will be a valuable asset for anyone modeling in acslXtreme and hopefully will help detect important parameters that will aid in the direction of future research. Different versions of Molly will be evaluated during the process of incorporating the new ATP yields. The second area of research is a follow up to what was presented last year. Ammonia emissions were measured from flux chambers where the manure was from a previous animal experiment. We found ammonia N emissions increased linearly as CP in the diet increased. Also, milk urea nitrogen concentration was a good predictor of maximal ammonia N emissions. Surprisingly, urine specific gravity was not a good predictor for urine urea N concentration unless the diets were evaluated separately. Jeff Firkins suggested to plot this as a three dimensional graph to see the importance of crude protein in the diet. Mike VandeHaar questioned why NH3 N/UUNg (g/g) decreases as crude protein in the diet increased. One would expect this to be more constant. The reason for this is unknown but possibly the amount of NH3 + NH4+ in the slurry is increasing but there is not a direct increase in NH3 emitted. Several asked about the effects of pH and although the pH was taken it was not included in this report.

NC 1040 5-year Accomplishments and Impact: The need as indicated by stakeholders. Over 55% of the calcium, 17% of the protein, and 15% of the energy in the US diet are supplied by dairy products; thus, the US consumer is a major stakeholder for the NC-1040 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 (in addition to Calcium) such as conjugated linoleic acids (CLA). Yet at its core the NC-1040 committee functions to do basic and applied research on the feeding and nutritional biology of dairy cattle. Major stakeholders include other scientists, practicing nutritionists, veterinarians, and farmers. The needs of these stakeholders have been addressed by the Food Animal Integrated Research group in the FAIR 2002 document. The goals of FAIR 2002 are to strengthen global competitiveness, enhance human nutrition, protect animal health, improve food safety and public health, ensure environmental quality, and promote animal well-being. Because feed inputs are a major determinant of milk yield, cow health, feed efficiency, profitability, and waste output, the work of the NC-1040 committee is critical for most of these goals. The concentration of dairy animals into larger units is an established and continuing trend. This concentration makes some waste management issues more prominent but also more manageable. The importance of our work. Natural resources are used 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-1040 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 470,000 metric tons per year and save US dairy farmers $1 billion 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. Integration of results. This committee has a proven track record of making significant impacts in our knowledge dairy cattle nutrition and metabolism and in the way that dairy cattle are fed and managed nationwide. We use the same approach that has proven effective in the past: that is to challenge and refine our models of dairy nutrition and metabolism. Computer-based, mechanistic, and quantitative metabolic models are useful in two ways: first, they help us determine critical needs in research and second they enable practical improvements in dairy cow feeding. Critical research needs are determined by using existing data from NC-1040 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 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. Need for Cooperative Work. 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 feed supply, nutrient use, genetic capability, 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, gene array work, 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 the complex interrelationships of nutrient digestion and metabolism in lactating dairy cows and to apply this knowledge. Impacts on Science and Other 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 and have led to practical feeding recommendations used worldwide. Project Leaders for the NC-1040 regional project have received numerous awards for research, both basic and practical, from the American Dairy Science Association, the American Society of Animal Sciences, and industry groups. Most of the Project Leaders are in continuous demand as speakers for scientific and industry conferences in nutrition. The impact on basic and practical nutrition from Project Leaders has been profound in the areas of starch and protein chemistry and nutrition, feed processing, nutrient metabolism, and lactation biology. This group provided a major contribution to the 2001 version of the National Research Councils (NRC's) Nutrient Requirements of Dairy Cattle. Four of the 10 scientists on the NRC panel were from the NC-1040 committee (IL, MD, NH, PA), and a significant portion of the data used in the latest edition came from NC-1040 committee members. In 2005, the group presented a symposium at ADSA/FASS on regulation of nutrient use in dairy cattle. Thus, this committee has had a major impact on improving the biological, economical, and environmental efficiency of the US dairy industry. D. Summary of Progress: Funds Leveraged to Support Work on Project in 2008. The research conducted year-on-year of this project could not be possible without significant funding support from various avenues. Members of the committee have a long history of acquiring competitive funds from federal and state agencies, and indeed, not a year has gone by over the last 20 years that at least one member of the project has not held a USDA-NRI grant. In 2008, members of the committee leveraged a total of $2,297,892 from various agencies and private industry to support research activities. This total breaks down into the categories of: Federal funds: $1,299,232 State funds: $279,491 College funds: $139,286 International agencies: $9,000 Boards/Councils/Association funds: $77,300 Private Industry funds: $493,583 Research Activities and Progress. One overriding 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 ability given by the genotype of the cow or herd. This is a major challenge because of the tremendous variety of feedstuffs available, their 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 bacterial fermentation and intestinal digestion. Feed particles and microbes that escape the rumen can be digested in the small intestine to produce amino acids, monosaccharides, and lipids for absorption. The chemical and physical properties of feeds determine the rumen bacterial and protozoal populations and the end-products they produce, and, relatedly, the availability of nutrients critical to the production of milk and milk components in a variety of ways. For example, the chemical composition (including total protein, nonprotein nitrogen, amino acid balance, organic acids, lipids, fiber, and non-fiber carbohydrate) dictates directly the availability of nutrients to support rumen microbial growth and the absorbed nutrients available to the animal to support milk synthesis. The physical properties of feeds, either inherent in the plant structure or altered by various processing methods, alters degradability in the rumen, and thus determines the proportion of feed fermented and used for rumen microbial growth and the proportion that passes to the small intestine. The cow is a fully integrated metabolic system in which one, even minor, change in nutrient input may lead to a variety of downstream events that alters function at the tissue and whole animal levels. Since the last revision, we now understand more fully that this also includes changes in gene expression, and endocrine responses that were unknown or just discovered 5 years ago (IGF-1, leptin, perilipin, cytokines and ghrelin from the adipose tissue, for example). (KS, MI, WA) Dietary carbohydrate fractions differ in the profiles of glucogenic and lipogenic metabolites they yield upon rumen bacterial metabolism and intestinal absorption. The amount and types of carbohydrates also impact rumen pH, which, in turn, alters fermentation and can alter the yield of nutrients, even amino acids, for absorption. Thus the various carbohydrate fractions have differential effects on the yield and composition of milk. Recent improvements in methods will allow more accurate prediction of optimal amounts and ruminal availability of non-fiber carbohydrates for efficient production of milk and milk components. More importantly, because of the integrative modeling approach of this committee, we have a quantitative knowledge of the maximal percentage contribution of these fractions to overall yield and efficiency on different diets, and can move on to further work. The amount and balance of absorbed amino acids also helps determine milk yield, not just milk protein synthesis. This availability of amino acids, in turn, is a function of the amount of feed protein which passes undegraded through the rumen and the amount of ruminally synthesized microbial protein that reaches the small intestine. Because microbial protein has a better amino acid profile than many feed proteins, this remains an important area of study. Microbial protein yield is also a function of the amount and type of organic matter fermented. Thus, microbial protein yield varies by source of carbohydrate and protein, and rate of fermentation. This is a classic example of the need for an integrated approach to dairy cattle nutrition-we must continue to design experiments across state lines that allow a full scope of study of the key variables. We need to continue to build a comprehensive model that explicitly includes these types of interactions. Synthesis of milk and milk components is a function of both the synthetic potential of the mammary gland and the supply of metabolites to the mammary gland. Supply of metabolites comes from dietary components, some of which are modified in other tissues, and from mobilization of body lipids and amino acids. There is an interaction between metabolism of body tissues, the supply of dietary nutrients and the milk production potential of the cow (as well as other animals) which has been recognized for quite some time which provide an extreme range of response of animals to even the same diet. While many dairy scientists have been slow to recognize the importance of these interactions, several stations in this project have been studying these interactions across a range of diets, genetic potentials, and stages of lactation (AL, CA, IA, IN, KS, MI, PA,WA and more recently OH, MD, VA). Data has been used to refine our feeding recommendations on a wide variety of feedstuffs. New concepts on the interactions of nutrition and gene expression is exemplified with work from several stations: At IN new information on molecular control of enzymes that modulate hepatic gluconeogenesis reveal specific differences between the cow and other animals. At WA, work with supplemental chromium, a nutrient known to be required for many years, a positive feed intake and milk production response was obtained with supplemental chromium, along with a reduction in lipolysis and an increase in lipogenesis in adipose tissue, removing the negative effects of fatty acid mobilization on feed intake in early lactation. Many nutritionists have now recognized that we cannot do relevant nutritional research without integrating this work with genetics and gene expression. Many nutrients are now known to affect gene expression in several organs, which then alters the animal response to the diet or further changes in the diet. Newer additions to the committee (KS) as well as adapting previous members (AL, IA, IN, MD, MI, OH, VA, WA) have begun serious efforts in identifying genetic responses to diet and to lactation. This work falls presently into the basic aspect-providing hard data to other scientists and advanced professionals on the key interactions of genetics and diet. This holds future promise in even more efficient feeding management and breeding programs. Major advancements have occurred in our knowledge of the interaction of metabolism and the endocrine system. Studies at AL, IN, and MI, in collaboration with other NC-1040 members, have illustrated the role of nutrition in the IGF-I system of dairy cattle. At IA, the role of glucagon in lipid metabolism has shown its potential for treatment for fatty liver while recent work at KS has begun to provide a mechanistic basis for the involvement of adipose derived cytokines in initiation of fatty liver. Work has also been done on the role of leptin in mammary gland development and regulation of feed intake (MI). If we are to improve the accuracy and precision of predicting nutrient use, we must continue to improve mechanistic, dynamic models of metabolism. The newer Dairy Nutrient Requirements book (NRC, 2001) was based in large part on data from this committee. In the 7 years since its publication, it has gained great respect in the industry. However, the process of revision of this document, and the model within it, also pointed out many of the shortcomings in our current knowledge base. The new version is limited especially in predicting dietary nutrient interactions, which consequently hamper our ability to predict rumen microbial metabolism and microbial protein yield and therefore responses to rumen-undegraded protein, carbohydrate, and fat supplements. Other significant limitations are the ability to predict short term versus long-term nutritional responses and changes in body fat and protein use. More mechanistic modeling of the metabolism of the lactating dairy cow will allow for evaluation of these interactions. The most comprehensive mechanistic and dynamic model of metabolism in the dairy cow is called 'Molly', developed at CA with inputs from most NC-1040 members. Members of this project (IL, MD, NH, PA) also have been instrumental in developing the new NRC model (NRC, 2001), which serves as the standard for dairy ration formulation and evaluation in the US. These different computer nutrition programs are currently in use for predicting nutrient requirements and productivity of lactating dairy cows. While all of these systems are soundly based on available data, all have weaknesses in the areas defined by Objectives 1 and 2. The rate of degradation of feedstuffs, the effect of various dietary carbohydrates on rumen fermentation and microbial protein synthesis, and quantitative data on metabolic interchanges among nutrients and body tissues limit the accuracy of these systems. New collaborative efforts by the NC-1040 project are needed to remove these inaccuracies. Molly is limited in its ability to describe the rapid changes in nutrient use that occur in early lactation and in predicting physiological responses to high feed intakes or diets with atypical amino acid, fiber, or starch contents. This is not surprising, given the paucity of these types of data when the model was originally constructed in the 1970 and 1980s. The modeling work done spurred new research into getting those data. Work done by several members of the committee (VA, MD, OH) is being used to challenge Molly for its description of energy use in the viscera and mammary gland. Visceral metabolism can account for the majority of maintenance requirements and can be highly variable. Errors in the model reflected a lack of knowledge of visceral metabolism in early and mid lactation. Using data generated, challenges and improvements to the model describing energy use have been made, further increasing its utility in research and application (McNamara, 2005, 2006). Quantitative data are still needed on the supply of milk component precursors available under different metabolic and nutritional conditions, such as early lactation. Data also are needed on the metabolic interconversions of nutrients, such as the use of amino acids for gluconeogenesis and thus milk lactose synthesis (MD, VA), and the partitioning of body fat and fat derived from the diet or lipogenesis for milk fat synthesis (WA). These data will enable further refinement of current nutrition recommendations and aid in interpretation of feeding experiments. E. Other Specific accomplishments: Reductions in feeding levels for ruminally degradable protein would reduce nitrogen losses in manure and improve animal efficiency (VA). As ammonia emissions from manure are driven by the amount of urinary N deposited in manure, such changes would lead to reduced ammonia emissions from animal and manure storage facilities. Improved knowledge of the mechanisms that regulate milk protein synthesis will allow development of models that better predict the requirements for milk protein synthesis. This in turn will allow more refined estimates of N requirements and reduced safety margins in feeding systems. Such an outcome will also work to reduce ammonia emissions from animal and manures storage facilities. Phosphorus availability in the digestive tract is an important determinant of the amount that must be fed and the amount that is lost in feces. Model development has helped identify key aspects of P digestion that warrant further examination and must be considered in requirement models to achieve greater reductions in P feeding levels (VA). This research evaluates the relationships between milk urea nitrogen, plasma urea nitrogen and urine urea nitrogen. Milk urea N can be a used to predict UUN excretion and may be extended to estimate NH3 emissions from dairy cattle manure because there is a strong relationship between UUN excretion and NH3 emissions. The information from this research is being used to test metabolic models for urine urea excretion (CA). Greater use of flax in the nutrition of dairy cattle can supplement lactation diets with not only protein and energy, but compliment the growing interest in designer foods with milk enriched with omega-3 and omega-6 from such grains as flax seed. Furthermore, preliminary evidence suggests that dairy cow fed flax also have improved reproductive health with improved pregnancy rates. It has been estimated that if dairy cow pregnancy rates could be increased, an estimated cost savings to the dairy enterprise of $8.73 per cow per year could be realized for every percentage unit gained (ND).

Refereed publications of NC-1040 Committee members during 2008 reporting year (does not include papers in press or abstracts) Project collaborative Publications: Bateman, II, H.G., M. D. Hanigan, and R.A. Kohn. 2008. Sensitivity of two metabolic models of dairy cattle digestion and metabolism to changes in nutrient content of diets. Anim. Feed Sci. Tech. 140:272-292. Cyriac, J., A. G. Rius, M. L. McGilliard, R. E. Pearson, B. J. Bequette, and M. D. Hanigan. Lactation performance of mid-lactation dairy cows fed ruminally degradable protein at concentrations lower than NRC recommendations. J. Dairy Sci. 91: 4704-4713. El-Kadi, S.W., McLeod, K.R., Elam, N.A., Kitts, S.E., Taylor, C.C., Harmon, D.L., Bequette, B.J., and Vanzant, E.S. (2008) Nutrient net absorption across the portal-drained viscera of forage-fed beef steers: Quantitative assessment and application to a nutritional prediction model. J. Anim. Sci. 86: 2277-2287. Huang, Y., J.P. Schoonmaker, B.J. Bradford, and D.C. Beitz. 2008. Response of milk fatty acid composition to dietary supplementation of soy oil, conjugated linoleic acid or both. J. Dairy Sci. 91:260-270. Individual station publications Bach, A., M. Ruiz Moreno, M. Thrune and M. D. Stern. 2008. Evaluation of fermentation dynamics of soluble crude protein from three protein sources in continuous culture fermenters. J. Anim. Sci. 86:1364-1371. Beauchemin, K. A., J.-S. Eun, and L. Holtshausen. Enzymes as additives to improve feed usage by cattle. 2008. Pages 261-280 in Recent Research Developments in Food Biotechnology: Enzymes as Additives or Processing Aids. R. Porta, P. D. Pierro, and L. Mariniello, ed. Research Signpost, Kerala, India. Bharathan, M., D. J. Schingoethe, A. R. Hippen, K. F. Kalscheur, M. L. Gibson, and K. Karges. 2008. Conjugated linoleic acid increases in milk from cows fed condensed corn distillers solubles and fish oil J Dairy Sci. 91:2796-2807. Bhatti SA, Bowman JG, Firkins JL, Grove AV, Hunt CW. (2008) Effect of intake level and alfalfa substitution for grass hay on ruminal kinetics of fiber digestion and particle passage in beef cattle. J Anim Sci. 86: 134-45. Bionaz, M., C. R. Baumrucker, E. Shirk, J. P. Vanden Heuvel, E. Block, and G. A. Varga. 2008. Characterization of Mardi-Darby bovine kidney cell line for PPARs: temporal response and sensitivity to fatty acids. J. Dairy Sci. 91:2802-2813. Bobe, G., V.R. A min, A.R. Hippen, P. She, J.W. Young, and D.C. Beitz. 2008. Non-invasive detection of fatty liver in dairy cows by digital analyses of hepatic ultrasonograms. J. Dairy Res. 75:84-89. Bobe, G., J.A. Minick Bormann, G.L. Lindberg, A.E. Freeman, and D.C. Beitz. 2008. Short Communication: Estimates of genetic variation of milk fatty acids in U.S. Holstein cows. J. Dairy Sci. 91:1209-1213. Broderick, G. A., N. D. Luchini, S. M. Reynal, G. A. Varga, and V. A. Ishler. 2008. Effect on production of replacing dietary starch with sucrose in lactating dairy cows. J. Dairy Sci. 91: 4801-4810. Carriquiry, M., W. J. Weber, L. H. Baumgard, and B. A. Crooker. 2008. In vitro biohydrogenation of four dietary fats. Anim. Feed Sci. Technol.141:339-355. Carriquiry, M., W. J. Weber, and B. A. Crooker. 2008. Administration of bovine somatotropin in early lactation: A meta-analysis of production responses by multiparous Holstein cows. J. Dairy Sci. 91:2641-2652. Chung, Y.-H., M. M. Pickett, T. W. Cassidy, and G. A. Varga. 2008. Effects of prepartum dietary carbohydrate source and monensin on periparturient metabolism and lactation in multiparous cows. J Dairy Sci. 91: 2744-2758. Davis Rincker, L.E., M.S Weber-Nielsen, L.T. Chapin, J.S. Liesman, and M.J. VandeHaar, M.J. (2008) Effects of feeding prepubertal heifers a high-energy diet for three, six, or twelve weeks on feed intake, body growth, and fat deposition. J Dairy Sci 91: 1913-1925. Davis Rincker, L.E., M. S. Weber-Nielsen, L. T. Chapin, J. S. Liesman, K. M. Daniels, R. M. Akers and M. J. VandeHaar (2008) Effects of feeding prepubertal heifers a high-energy diet for three, six, or twelve weeks on mammary growth and composition. J. Dairy Sci. 91:1926-1935. Dekking, L., F. Koning, D. Hosek, T.D. Ondrak, S.L. Taylor, J.W. Schroeder, and M.L. Bauer. 2008. Intolerance of celiac disease patients to bovine milk is not due to the presence of T cell stimulatory epitopes of gluten. Nutr. 25: 122  123. Eun, J.-S., and K. A. Beauchemin. 2008. Assessment of the potential of feed enzyme additives to enhance utilization of corn silage fibre by ruminants. Can. J. Anim. Sci. 88:97106. Firkins JL, Oldick BS, Pantoja J, Reveneau C, Gilligan LE, Carver L. (2008) Efficacy of liquid feeds varying in concentration and composition of fat, nonprotein nitrogen, and nonfiber carbohydrates for lactating dairy cows. J Dairy Sci. 91: 1969-84. Firkins, J.L., S.K.R. Karnati, and Z. Yu. 2008. Linking rumen function to animal response by application of genomic function. Aust. J. Exp. Agr. 48:711-721. Galbreath, C.W., E.J. Scholljegerdes, G.P. Lardy, K.G. Odde, M.E. Wilson, J.W. Schroeder, K.A.Vonnahme. 2008. Effect of feeding flax or linseed meal on progesterone clearance rate in ovariectomized ewes. Domest. Anim. Endocrinol. 35:164-169. Hazelton SR, Koser SL, Bidwell CA, Donkin SS. (2008) Translational efficiency of bovine pyruvate carboxylase 5' untranslated region messenger ribonucleic acid variants. J Anim Sci. 86:3401-8. Hazelton SR, Spurlock DM, Bidwell CA, Donkin SS. (2008) Cloning the genomic sequence and identification of promoter regions of bovine pyruvate carboxylase. J Dairy Sci. 91: 91-9. Hill, T.M., H. G. Bateman, II, J. M. Aldrich, R. L. Schlotterbeck, and K. G. Tanan, 2008. Optimal concentrations of lysine, methionine, and threonine in milk replacers for calves less than five weeks of age. J. Dairy Sci. 91: 2433-2442. Hill, T.M., H. G. Bateman, II, J. M. Aldrich, and R. L. Schlotterbeck. 2008. Effects of the amount of chopped hay or cottonseed hulls in a textured calf starter on young calf performance. J. Dairy Sci.91: 2684-2693. Hill, T.M., H. G. Bateman, II, J. M. Aldrich, and R. L. Schlotterbeck. 2008. Effects of feeding different carbohydrate sources and amounts to young calves. J. Dairy Sci. 91: 3128-3137. Hill, T. M., H. G. Bateman, II, J. M. Aldrich, and R. L. Schlotterbeck. 2008. Oligosaccharides for dairy calves. Prof. Anim. Sci. 24: 460-464. Hill, T. M., H. G. Bateman, II, J. M. Aldrich, and R. L. Schlotterbeck. 2008. Effects of using wheat gluten and rice protein concentrate in dairy calf milk replacers. Prof. Anim. Sci. 24: 465-472. Hill, S. R., Knowlton, K. F., Kebreab, E., France, J., and Hanigan, M. D. 2008. A model of phosphorus digestion and metabolism in the lactating dairy cow. J Dairy Sci. 91:2021-2032. Hollmann, M., K. F. Knowlton, and M. D. Hanigan. 2008. Evaluation of solids, nitrogen, and phosphorus excretion models for lactating dairy cows. J. Dairy Sci. 91:1245-1257. Kadegowda, A.K.G., Piperova, L.S., Delmonte, P. and Erdman, R. A. (2008) Abomasal infusion of butterfat increases milk fat in lactating dairy cows. J. Dairy Sci. 91:2370-2379. Kadegowda, A.K.G., Piperova, L.S., and Erdman, R. A. (2008) Principal component and multivariate analysis of milk long-chain fatty acid composition during diet-induced milk fat depression. . Dairy Sci. 2008. 91:749-759. Kebreab, E., N. E. Odongo, B. W. McBride, M. D. Hanigan, and J. France. 2008. Phosphorus utilization and environmental and economic implications of reducing phosphorus pollution from Ontario dairy cows. J. Dairy Sci. 91:241-246. Markantonatos, X., M.H. Green, and G.A. Varga. 2008. Use of compartmental analysis to study ruminal volatile fatty acid metabolism under steady state conditions in Holstein heifers. Anim. Feed Sci. Techn 143:70-88. Osman, M.A., P.S. Allen, N.A. Mehyar, G. Bobe, J.F. Coetzee, K.J. Koehler, and D.C. Beitz. 2008. Acute metabolic responses of postpartal dairy cows to subcutaneores glucogan injections, oral glycerol, or both. J. Dairy Sci. 91:331-3322. Riasi, A., M. Danesh Mesgaran, M. Ruiz Moreno, M. D. Stern. 2008. Chemical composition, in situ ruminal degradability and post-ruminal disappearance of dry matter and crude protein from the halophytic plants Kochia scoparia, Atriplex dimorphostegia, Suaeda arcuata and Gamanthus gamacarpus Anim. Feed Sci. Technol. Vol. 141/3-4:209-219. Sasikala-Appukuttan, A. K., D. J. Schingoethe, A. R. Hippen, K. F. Kalscheur, K. Karges, and M. L. Gibson. 2008. The feeding value of corn distillers solubles for lactating dairy cows. J. Dairy Sci. 91:279-287. Socha, M. T., C. G. Schwab, D. E. Putnam, N. L. Whitehouse, B. D. Garthwaite, and G. A. Ducharme. 2008. Extent of methionine limitation in peak-, early-, and mid-lactation dairy cows. J. Dairy Sci. 91:1996-2010. Silva, L.F.P., B.E. Etchebarne, M.S. Weber-Nielsen, J.S. Liesman, M. Kiupel, and M. J. VandeHaar (2008) Intramammary infusion of leptin decreases proliferation of mammary epithelial cells in prepubertal heifers. J. Dairy Sci. 91: 3034-3044. Toshniwal, J. K., C. D. Dechow, B. G. Cassell, J. A. D. R. N. Appuhamy, and G. A. Varga. 2008. Heritability of electronically recorded daily body weight and correlations with yield, dry matter intake and body condition score. J Dairy Sci. 91:3201-3210. Wilcox, C. S., M. M. Schutz, S. S. Donkin, D. C. Lay, Jr. and S. D. Eicher. 2008. Short Communication: Effect of Temporary Glycosuria on Molasses Consumption in Holstein Calves. J Dairy Sci. 91:3607-3610. White HM, Richert BT, Radcliffe JS, Schinckel AP, Burgess JR, Koser SL, Donkin SS, Latour MA. (2008) Feeding CLA partially recovers carcass quality in pigs fed dried corn distillers grains with solubles. J Anim Sci. 91: 3607-10. Conference Proceedings, Theses and Popular Press articles: Beauchemin, K. A., L. Holtshausen, and J.-S. Eun. 2008. Use of enzymes in beef and dairy cattle diets. Pages 60-71 in Proc. 44th Eastern Nutrition Conf., University of Guelph, Guelph, ON, Canada. Bobe, G., S. Zimmerman, E.G. Hammond, G. Freeman, P.A. Porter, C.M.Luhman, and D.C. Beitz. 2008. Butter composition and texture from cows with different milk fatty acid compositions fed fish oil or roasted soybeans. A.S. Leaflet R2302. Bobe, G., G.L. Lindberg, and D.C. Beitz. 2008. Regulation of periparturient milk composition in Jersey cattle. A.S. Leaflet R2307. Bobe, G., G.L. Lindberg, J. Young, and D.C. Beitz. 2008. Changes in milk protein and amino acid composition of dairy cows in response to fatty liver and intravenous glucagon. A.S. Leaflet R2308. Boucher, S. E. 2008. Evaluation of In Vitro Methods to Estimate Digestibility of Amino Acids in the Rumen Undegraded Protein Fraction of Feedstuffs. Ph.D. thesis. University of New Hampshire, Durham. 244 p. Garcia, A., K. Kalscheur, A. Hippen, D. Schingoethe, and K. Rosentrater. 2008. Mycotoxins in Corn Distillers Grains: A concern in ruminants? South Dakota State University, Cooperative Extension Service. ExEx4038. Mpapho, G. S. 2008. Feeding wet corn distillers grains to transition and lactating cows. Ph.D. Dissertation, South Daktoa State University, Brookings. 105 pp. Ranathunga, S.D. 2008. Replacement of starch from corn with non- forage fiber from distillers grains in diets of lactating dairy cows. M.S. Thesis, South Dakota State University, Brookings. Varga, G. A. 2008. Use of metabolizable protein in ration formulation. Ontario Bovine Practioners Conference, Guelph, Ontario.