Source: MICHIGAN STATE UNIV submitted to NRP
GENOMIC SELECTION AND HERD MANAGEMENT FOR IMPROVED FEED EFFICIENCY OF THE DAIRY INDUSTRY
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
0224899
Grant No.
2011-68004-30340
Cumulative Award Amt.
$4,788,043.00
Proposal No.
2015-03329
Multistate No.
(N/A)
Project Start Date
May 1, 2011
Project End Date
Apr 30, 2018
Grant Year
2015
Program Code
[A5101]- Global Food Security: Improving Sustainability by Improving Feed Efficiency of Animals
Recipient Organization
MICHIGAN STATE UNIV
(N/A)
EAST LANSING,MI 48824
Performing Department
Animal Science
Non Technical Summary
SITUATION. The US dairy industry has improved its stewardship in use of feed resources considerably in the past 100 years. In 1910, the average US dairy cow produced 1600 kg milk/year; today the average is 9600 kg/year, and top herds average 15000 kg. With greater productivity, cows eat more feed but the amount needed for body maintenance stays the same; thus, on a percentage basis, the amount of feed needed for maintenance is diluted out by that needed for milk. Per unit of milk produced, today's dairy farms use 70% less feed, excrete 70% less nitrogen and phosphorus waste, and emit 75% less greenhouse gasses than those of 1910. Efficiency will continue to improve as production per cow continues to increase beyond 9600 kg/year, although the correlation between the two will gradually decrease. Current models predict that increasing productivity above 15,000 kg milk/cow/year will have no impact on feed efficiency. Thus, in the past, feed efficiency increased as the indirect result of farmers and scientists focusing on how to produce more milk per cow. However, to improve feed efficiency in the future, we must begin to focus specifically on how to produce more milk per unit of feed. Through new developments in the science of genomics, we will conduct research that will enable selection of animals specifically for the trait of feed efficiency. Through new developments in computer modeling, we will implement tools for selection and management that will enable farms to consider the value of feed efficiency when making complex decisions. PURPOSE. Our overall goal is to increase the efficiency and sustainability of producing milk. We have five specific aims to achieve this goal. First, we will develop a feed efficiency database seeded with data from 8000 Holstein cows. The data for these cows will include measures of feed intake and composition, milk output and composition, body weight changes, health and fertility, as well as environment, and information about their genetic pedigree and genotype. We will eventually house this database in a publically available format that can serve as the basis for future experiments. Second, we will determine if the feed efficiency trait is transferred from one generation to the next and if it is correlated with other important traits of cows. We also will identify regions of a cow's DNA that are important for feed efficiency. Third, we will develop genomic breeding values for feed efficiency and facilitate optimal incorporation of the breeding values into the national genetic improvement program for US dairy cattle. Fourth, we will develop and deploy practical state-of-the-art decision support tools for farmers so that feed efficiency is considered when making decisions regarding cow grouping, feeding, culling, and reproduction. Fifth, we will develop new programs and materials to educate K-12 and undergraduate students about key practices in dairy husbandry that promote efficiency and environmental stewardship. Our project will produce more efficient dairy cows, more efficient dairy herds, and a more educated public to promote sustainable dairy production for global food security.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
3023410101030%
3033410108040%
3043410108010%
3073410101020%
Knowledge Area
303 - Genetic Improvement of Animals; 302 - Nutrient Utilization in Animals; 307 - Animal Management Systems; 304 - Animal Genome;

Subject Of Investigation
3410 - Dairy cattle, live animal;

Field Of Science
1010 - Nutrition and metabolism; 1080 - Genetics;
Goals / Objectives
Our goal is to increase the efficiency and sustainability of producing milk. We have 5 specific aims. First, we will develop a feed efficiency database seeded with genotype and phenotype data from 8000 Holstein cows. Our measure of feed efficiency will be Residual Feed Intake (RFI), a measure of how much feed a cow eats after adusting for confounding factors. Cows with low RFI need less feed for the a given amount of milk and are thus more efficient. We will eventually house this database in a publically available format that can serve as the base for future experiments. Second, we will determine the genetic architecture of feed efficiency in lactating dairy cows. This includes estimating heritability of RFI and covariances with other traits, estimating individual and additive effects of SNP alleles, and estimating genetics by environment interactions. Third, to bring our genomic RFI work to fruition, we will facilitate optimal incorporation of our newly developed genomic breeding values for RFI into the national genetic improvement program for US dairy cattle. Fourth, we will develop and deploy practical state-of-the-art decision support tools for farmers so that feed efficiency is considered when making decisions regarding cow grouping, feeding, culling, and reproduction. Along with this, we will use our database to determine the optimal level of milk production per cow to maximize efficiency. Fifth, we will educate K-12 and undergraduate students about key practices in dairy husbandry that promote efficiency and environmental stewardship. Aim 1 will commence in year 1 and continue to the end. Enough data will be collected by year 3 to initiate aim 2, and aim 3 will be performed during years 4 and 5. Aims 4 and 5 will begin immediately with most of the outputs in years 3, 4, and 5. EXPECTED OUTPUTS. Our plan is to have a database with enough cows by year 3 to use in genetics and nutrition work, 2) to make this database publicly available in year 5 for use by other researchers, 3) to provide genomic breeding values for feed efficiency that can be used in selecting sires in the US dairy industry by year 5, 4) to provide practical tools for improving herd feed efficiency by year 3 and test their efficacy by year 5, and 5) to provide new curriculum and materials for use in K-12, 4-H, and college education by year 4. An increase in feed efficiency is expected to be attained by year 4 with the on-farm tools. The impact of aim 3 (improved genetics for feed efficiency) is not expected within the life of the project, because the genetically-improved animals will not begin lactating until almost 3 years after the new selection index has been initiated.
Project Methods
AIM 1. We will collect data on feed composition and intake, milk composition and output, body weight (BW), change in BW, health, and fertility in 5300 Holstein cows. Of these cows, 2800 will be observed specifically for our project for 2 months in peak lactation. This new data, along with suitable data for another 2500 cows that are part of other experiments, will be combined with feed efficiency data that already exists for 2700 cows. Half of the cows will be genotyped with a genotyping platform of 50,000 single-nucleotide polymorphisms (SNP) and half with a 3000 SNP platform. The primary measure of feed efficiency will be Residual Feed Intake (RFI), which identifies the most efficient cows in a group after adjusting for confounding factors. Cows with negative RFI are most efficient. AIM 2. Employing standard methods, the heritability of RFI and covariances among RFI, production, health, and fertility traits will be determined, and then combined with genotype data to estimate individual and additive effects of SNP alleles. We then will identify loci in the genome that influence RFI, begin to identify causal genes, and determine if RFI is altered by interactions between genetics and diet composition or environment. AIM 3. We will work with the USDA-ARS Animal Improvement Programs Laboratory and with AI companies to include genomic breeding values for RFI into the Lifetime Net Merit Index used in selecting the best sires and cows for future generations of dairy cattle. We will be careful to ensure that improved RFI does not cause negative impacts on health, fitness, and fertility. The final impact of aims 1, 2, and 3 will not be observed within the life of the project, because the genetically-improved animals will not begin lactating until almost 3 years after the new selection index has been initiated. Thus, we will rely on simulation studies coupled with data on actual usage of genomic RFI values to predict expected impact. AIM 4. We will use the feed database to determine the optimal level of milk production per cow to maximize whole herd feed efficiency. Working with stakeholders, we will use dynamic programming techniques to develop and deploy user-friendly herd decision support tools that enhance feed efficiency of whole herds. These tools will enable identification of farm-specific major impediments to better feed efficiency and provide expected returns from management changes in cow grouping, feeding, culling, and reproduction. We will deliver workshops and educational materials and demonstrate these tools on commercial dairy farms. We will survey farms in years 1 and 5 to discover the current situation and the adoption and impact of our new tools. AIM 5. We will develop and implement new educational programs for K-12 and undergraduate students. We will work with stakeholders and make use of existing courses and programs whenever possible to maximize cost-effectiveness. Undergraduate students will be mentored and involved in all aspects of the project so that they have a deeper appreciation for methods to enhance feed efficiency and environmental stewardship. Evaluation of impact will be developed in conjunction with stakeholders.

Progress 05/01/11 to 04/30/18

Outputs
Target Audience:Target audience includes other researchers as well as dairy industry leaders, extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. Scientists and leaders in the USDA Animal Genomics Improvement Laboratory, the Council for Dairy Cattle Breeding, and the US National Holstein Association have been primary targets and partners in the past year. Changes/Problems:Our original intent was to make our database public and easily accessible. However, we have since realized that our European colleagues have no immediate intention of doing the same. Thus, US data would be used to benefit European companies that market semen to the US, which would put US companies at a competitive disadvantage. Instead, we now will use our database as leverage to try to enhance international cooperation on developing a larger global reference population for genomic estimates of the breeding value of dairy cattle for feed efficiency. What opportunities for training and professional development has the project provided?Previous reports documented this. At least 7 graduate students and one post-doctoral scientist received hands-on training on the value of residual feed intake as a tool for identifying lactating cows that use feed more efficiently. How have the results been disseminated to communities of interest?Over the course of the project, we have published our findings in the Journal of Dairy Science and presented our findings at the annual meetings of the American Dairy Science Association (ADSA). We also presented our findings and general information on feed efficiency at nutrition, genetics, management, and veterinary conferences. We proposed and led a Discover Conference on dairy feed efficiency, and a symposium on "The cow of the Future" at the ADSA meetings. Websites were developed to host information on feed efficiency, tools for improving feed efficiency on farms, and educational curricula to teach the importance of feed efficiency for sustainable food production. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? This report focuses on publications and accomplishments that had direct collaboration from Michigan State University. Thus, some work at subcontracting institutions that was supported in part with funds from this project may not be included. Over the life of this project, we developed a database of 7500 cows with phenotypes for feed efficiency; of these, 6100 also have "good" genotypes, and of these, 4700 are from locations in the North America. We examined feed efficiency using 3 different traits. Gross feed efficiency is the energy captured in milk and body tissues divided by feed intake. Residual feed intake (RFI) is the actual feed intake of a cow minus her predicted intake based on milk production, body weight (BW), BW change, and the intake of her cohorts. Feed saved is the RFI of a cow plus the amount of feed saved if her BW is smaller than average. Efficient cows have greater gross feed efficiency, lower RFI, and greater feed saved. We had several important findings. The pedigree-based heritability for RFI based on 5000 cows was moderate at 0.17; this was the most complete dataset ever compiled to estimate the true heritability of feed efficiency (Tempelman et al, 2015). Although the heritability was lower than expected, traits with moderate heritability are still good candidates for genetic improvement through genomic selection. The genomic variation in RFI based on 3000 cows was 0.14. (Hardie et al., 2017). We expected this value to be similar to the pedigree-based heritability. Again, moderate heritability traits are good candidates for genomic selection. However, a genomic heritability of 0.14 likely means that more than 10,000 cows will be needed in the reference population for reasonable confidence in the reliability of the genomic-estimated breeding values (GEBV) for individual animals. We found that cow height and BW are negatively correlated with Gross Feed Efficiency, r = -0.7 and -0.3, respectively (Manzanilla-Pech et al., 2015; VandeHaar et al., 2014). Using our US reference population of cows, genomic estimated breeding values for RFI were calculated for 16,000 US Holstein sires. The 20% most efficient sires (lowest RFI) should produce daughters that require 400 kg less feed per year than the 20% least efficient (highest RFI) for the same level of milk production at same BW, and when coupled with variation in expected maintenance costs due to differences in BW, the difference was 635 kg of Feed Saved per year (Yao et al., 2016). At an average feed cost of $0.25/kg, this equates to $160 per year in saved feed. Based on its projected economic value to the dairy industry, we estimate that RFI should receive 16% of total emphasis in the US Net Merit Index (Van Raden et al., 2018). However, the current reliabilities for the GEBV of RFI for young sires are less than 20%. These low reliabilities will limit genetic progress and dampen the enthusiasm for the industry to include RFI GEBV in Net Merit at this time. Our group is currently working with the Council for Dairy Cattle Breeding on ways to move forward with more data collection and with US breeding companies on ways to increase the genetic relationships of top young sires to cows in our research herds. We expect that feed efficiency will be incorporated into the Net Merit Index by 2020. Our database is being turned over to the USDA Animal Genomics Improvement Laboratory and will be accessible by US scientists and dairy breeding companies. We will share data with international groups if they share their data with us. In addition, we developed on-farm management tools for making decisions on grouping cows and educational tools for teaching about the importance of feed efficiency for sustainable food production. These can be found at and at .

Publications

  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hardie, L.C., M.J. VandeHaar, R.J. Tempelman, K.A. Weigel, L.E. Armentano, G.R. Wiggans, R.F. Veerkamp, Y. de Haas, M.P. Coffey, E.E. Connor, M.D. Hanigan, C. Staples, Z. Wang, J.C.M. Dekkers, D.M. Spurlock. 2017. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. J Dairy Sci. 100: 9061-9075.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Lu, Y., M.J. VandeHaar, D.M. Spurlock?, K.A. Weigel, L.E. Armentano, E.E. Connor, M. Coffey, R. F. Veerkamp, Y.de Haas, C. R. Staples, Z. Wang, M. Hanigan, and R.J. Tempelman. 2018. Genome wide association analyses based on a multiple trait approach for modeling feed efficiency. J. Dairy Sci 101:3140-3154.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: de Souza, R.A., R. J. Tempelman, M. S. Allen, W. P. Weiss, J. K. Bernard, and M. J. VandeHaar. 2018. Predicting nutrient digestibility in high-producing lactating dairy cow. J Dairy Sci. 101:1123-1135.
  • Type: Book Chapters Status: Published Year Published: 2017 Citation: VandeHaar, M.J., and R.J. Tempelman. 2017. Feeding and breeding to improve feed efficiency and sustainability. Pages 61-68 (Ch. 1-05) in Beede, D.K. (editor), Large Dairy Herd Management Handbook, Am. Dairy Sci. Assoc., Oak Brook, IL.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Cabrera, V. E. 2018. What are the economic advantages of grouping and feeding dairy cows by nutritional need? Proceedings of 29th Annual Florida Ruminant Nutrition Symposium. Gainesville, FL 5-7 February 2018.


Progress 05/01/16 to 04/30/17

Outputs
Target Audience:Target audience includes other researchers as well as dairy industry leaders, extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. Scientists and leaders in the USDA Animal Genomics Improvement Laboratory, the Council for Dairy Cattle Breeding, and the US National Holstein Association have been primary targets and partners in the past year. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Four graduate students and 10 undergraduate students received training in dairy cattle nutrition and/or breeding and in research. How have the results been disseminated to communities of interest?Research publications, conference proceedings, scientific presentations, phone conversations, and meetings with industry professionals. VandeHaar made presentations to the US Holstein Association, the National Dairy Herd Improvement Association, leaders of the Council for Dairy Cattle Breeding, and several nutrition and management conferences. What do you plan to do during the next reporting period to accomplish the goals?Research is continuing on 1) repeatability of RFI across different types of diets with a focus on protein, 2) methods to predict feed intake based on animal characteristics within a group using activity and temperature sensor technologies, and 3) methods to incorporate feed efficiency into a new breeding index. Discussions with industry leaders are ongoing.

Impacts
What was accomplished under these goals? This report includes only publications and accomplishments that had direct collaboration from Michigan State University. Thus, some work at subcontracting institutions that was supported in part with funds from this project may not be included. In the past year, we continued to analyze and report genomic relationships for feed efficiency, as can be seen in the publications list, and we showed that residual feed intake was repeatable across diets sufficient or marginally deficient in protein. In collaboration with scientists at the USDA Animal Genomics Improvement Laboratory, we showed that including genomic predictions for residual feed intake in the US national Net Merit Index would improve the goals of the US dairy industry to improve feed efficiency and profitability. However, we also found that the reliability of the genomic predictions for young sires was low, and the dairy breeding companies are concerned about this. We hope that by the end of the project we can alleviate this concern. Our data has been useful in convincing the US dairy industry to decrease its preference for larger cows in breeding schemes.

Publications

  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hardie, L.C., M.J. VandeHaar, R.J. Tempelman, K.A. Weigel, L.E. Armentano, G.R. Wiggans, R.F. Veerkamp, Y. de Haas, M.P. Coffey, E.E. Connor, M.D. Hanigan, C. Staples, Z. Wang, J.C.M. Dekkers, D.M. Spurlock. 2017. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. J Dairy Sci. 100: in press
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Yao, C., G. De Los Campos, M.J. VandeHaar, D.M. Spurlock, L.E. Armentano, M. Coffey, Y. de Haas, R.F. Veerkamp, C.R. Staples, E.E. Connor, Z. Wang, M.D. Hanigan, R.J. Tempelman, and K.A. Weigel. 2017. Use of genotype � environment interaction model to accommodate genetic heterogeneity for residual feed intake, dry matter intake, net energy in milk, and metabolic body weight in dairy cattle. J Dairy Sci. 100:2007-2016. doi:10.3168/jds.2016-11606.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Lu, Y., M.J. VandeHaar, D.M. Spurlock?, K.A. Weigel, L.E. Armentano, C. R. Staples, E.E. Connor, Z. Wang, M. Coffey, R. F. Veerkamp, Y.de Haas, and R.J. Tempelman. 2017. Modeling Genetic and Non-Genetic Variation of Feed Efficiency and its Partial Relationships between Component Traits As a Function of Management and Environmental Factors. J. Dairy Sci. 100:412-427.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Potts, S. B., J. P. Boerman, A. L. Lock, M. S. Allen, and M. J. VandeHaar. 2017. Relationship between residual feed intake and digestibility for lactating Holstein cows fed high and low starch diets. J. Dairy Sci. 100:265-278. doi:10.3168/jds.2016-11079.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: VandeHaar, M.J. 2017. Improving feed efficiency in the dairy industry. Proc Lely FMSNA Dairy Conference. Fair Oaks, IN.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: VandeHaar, M.J.. 2017. New (and old) technologies to improve feed efficiency. Proc 5th Intl Symp on Dairy Cow Nutr Milk Quality. Beijing, China.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: VandeHaar, M.J.. 2017. Alternative strategies for improving feed efficiency and sustainability. Proc 53rd Florida Dairy Prod Conf. Gainesville, FL.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: VandeHaar, M.J., and K.A. Weigel. 2017. Breeding for Feed Efficiency: Yes We Can! Proc. 13th Western Dairy Mgt Conf. Mar. 2, Reno, NV, pp. 212-219.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: VandeHaar, M.J. 2016. Improving feed efficiency to promote a sustainable dairy industry. Proc Biomin World Nutr Conf. Oct. 14, Vancouver, BC.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Bart, E.M., M.D. Hanigan, D.M. Spurlock, M.J. VandeHaar, and R.R. Cockrum. 2017. Feed efficiency and reproductive performance are genomically independent in lactating Holstein cows. J. Dairy Sci.100(suppl.2):15 (abstr M25).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: VanRaden, P.M., J.R. Wright, E.E. Connor, M.J. VandeHaar, R.J. Tempelman, J.S. Liesman, L.E. Armentano, and K.A. Weigel. 2017. Preliminary genomic predictions of feed saved for 1.4 million Holsteins. J. Dairy Sci.100(suppl.2):200-201 (Abstr. 209).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: VandeHaar, M.J. 2017. The Dairy Cow in 50 Years: A symposium for all ADSA members and especially for graduate students in dairy production. J. Dairy Sci.100(suppl.2):337 (Abstr 272).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Liu, E., and M.J. VandeHaar. 2017. Repeatability of residual feed intake across diets with two levels of dietary protein content. J. Dairy Sci.100(suppl.2):359 (Abstr. 332).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Chen, C., K.A. Weigel, E.E. Connor, D.M. Spurlock, M.J. VandeHaar, C.R. Staples, and R.J. Tempelman. 2017. Bayesian whole-genome prediction and genome-wide association analysis with missing genotypes using variable selection. J. Dairy Sci.100(suppl.2):412 (Abstr 469).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hardie, H., K. Maxwell1, M. VandeHaar, and D. Spurlock. 2017. Relationship of mid-lactation feed efficiency with early and late lactation body condition score in Holstein dairy cows. J. Dairy Sci.100(suppl.2):432 (Abstr 519).


Progress 05/01/15 to 04/30/16

Outputs
Target Audience: Target audience includes other researchers as well as extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. The target audience also includes members of the Council for Dairy Cattle Breeding, the USDA-ARS Animal Genomics and Improvement Laboratory, and the dairy subcommittee of the National Research Council. Changes/Problems:Because the heritability of RFI was lower than expected, more than 8000 cows are needed to develop reliable genomic breeding values for the trait. Thus, we are continuing to collect data as long as possible. What opportunities for training and professional development has the project provided?Undergraduate students were given research and extension training and experience in year 5, as in previous years. They were involved in collecting feed intake and feed composition data, conducting DM analyses, collecting milk, feces, and blood samples, and processing and analyzing samples. Four minority students at NC A&T were mentored and participated in the Dairy Challenge. In addition, ten graduate students were trained in the past year. How have the results been disseminated to communities of interest?Nine manuscripts resulting from the project were published in year 5 from members of our group related to aims 2, 3, and 4. Some of these publications resulted from joint efforts with others, and some were partly funded by other external sources. In addition, 12 presentations, accompanied by publication, were presented in year 5 at the annual meetings of the American Dairy Science Association and at various nutrition and management conferences. What do you plan to do during the next reporting period to accomplish the goals?Progress will continue to meet the final goals of the project. We expect to exceed our goals for number of cows phenotyped but fall short on number of cows genotyped. We expect and exceed to meet our goals for analyzing genetic and genomic relationships. However, based on the data of this project, the accuracy of genomic breeding values will be lower than expected. Thus, we will continue to collect data from as many cows as possible of partner institutions as long as funds are available. Work also will continue on aims 4 and 5, and we expect to meet the goals of those aims.

Impacts
What was accomplished under these goals? Year 5 of our project started May 1, 2015, so are able to give a complete report for year 5. Abbreviations in this report are: Michigan State University (MI), University of Wisconsin (WI), Iowa State University (IA), Wageningen UR in the Netherlands (NL), University of Florida (FL), Virginia Tech (VA), and North Carolina A&T (NC). Aim 1: Development of feed efficiency database. Original plans for our 5-year project were to compile a database of 8000 cows with a phenotype for feed efficiency and genotypes with 60% 3k-density and 40% 50k-density SNP platforms. We are on target with our goals for acquiring feed efficiency phenotype traits. We currently have feed efficiency phenotypes on 8761 unique cows with 13,768 lactation records. The last compilation of the phenotype database was on Dec 22, 2015. At that time, in which we accepted only cows that met strict criteria in the original grant, we had recorded 7010 cows with at least one phenotype (>28-d record for feed efficiency) in our database (271 MI, 886 WI, 507 FL, 952 IA, 90 VA, 1975 NL, 1036 United Kingdom, 816 USDA-Dairy Forage Center, 518 USDA-ARS Beltsville, 237 Alberta, and 144 Purina). Of these, 4916 are currently linked to genotypes. Approximately 1000 of the cows are from NL or UK and no longer have DNA available, and the remaining cows are yet to be genotyped or linked to genotypes. We likely will be short of our goal of 8000 cows with genotypes and phenotypes linked, but we will exceed the original goals for the project in several areas related to Aim 1. All of our genotypes are with SNP platforms of 50K or greater, whereas we originally planned to genotype 60% of the cows at only 3K. Moreover, we have been working with Dr. George Wiggans at USDA Beltsville to ensure accuracy of pedigrees and genotype data and to impute genotypes to even higher levels. In addition, although some of our cows do not have genotypes, recent methodological advances will enable us to impute 50k genotypes for some of them by using genotypes of sires, maternal grandsires, and maternal great-grandsires. Finally, new genomic predictions have moved to an "H matrix" approach that allows inclusion of all phenotyped animals, regardless of whether or not they have genotypes. Thus, we may be able to use data from 9000 cows in our final genomic predictions of feed efficiency. The bigger challenge we face is that based on the data we have collected to date, we now know that we will need more than 8000 cows that to achieve the desired level of accuracy in our genomic prediction. We currently are working with potential partners to ensure continuation of the project after the end data for USDA funding. Aim 2: Determine the genetic architecture of feed efficiency in lactating dairy cattle and build a foundation for genomic selection of more efficient animals. During the past year, we continued analysis on the genetic architecture of feed efficiency. We are currently on target for analyzing data and reporting results of aim 2, and we have done additional work related to aim 2 on repeatability of efficiency. A genomic analysis of the first 4000 cows estimated the heritability of residual feed intake at 0.15, slightly below the pedigree-based heritability of 0.17. Candidate genes for the RFI trait that are independent of the related traits of milk production, body weight, and feed intake were identified. However, none of these were of remarkable effect, indicating that feed efficiency is under the control of many genes in coordination. Aim 3: Facilitate genomic selection tools. In our original timeline, activity for Aim 3 was scheduled for years 4 and 5. We used RFI along with feed saved for maintenance from smaller BW to develop a Feed Saved index. Genomic Breeding Values for Feed Saved on 16,000 Holstein AI bulls in North America were predicted from a reference population of 3,500 cows using 57,000 SNP markers per animal. The range in Feed_Saved from top to bottom bulls was 2000 kg per lactation (10% above and below the mean for DMI). The reliability of the EBV for RFI was 0.3. The data looks promising but more data are needed to improve the reliability. In the past year, meetings were held with members of the USDA Animal Genomics and Improvement Laboratory and the Council for Dairy Cattle Breeding on how to build upon our foundational database into the future. Aim 4: Development of decision-support tools. Aim 4a was to examine and refine current nutrition models using data from our study and published data. Three model evaluations are in review for publication, and further evaluations are on-going using data from published literature sources and from this project. Aims 4b to 4d were to develop decision-support tools. Year 5 was devoted to promotion of the online decision support applications released in year 4, 1) Grouping strategies for feeding lactating dairy cattle, which assists with nutritional grouping decisions, and 2) FeedVal, which assists with diet decisions. We have also begun farm audits to evaluate the effectiveness of these on-line tools. In addition, several presentations were made to farmers, consultants, and feed industry personnel in year 5 to show the benefits of nutritional grouping and feed efficiency for sustainable agriculture and receive feedback on our plans. These are listed in publications and presentations below. We are on schedule to achieve the goals set forth in Aim 4. Aim 5: Development of educational resources. Several undergraduate students were given research and extension training and experience in year 5, as in previous years. They were involved in collecting feed intake and feed composition data, conducting DM analyses, collecting milk, feces, and blood samples, and processing and analyzing samples. Four minority students at NC A&T were mentored and participated in the Dairy Challenge. Educational materials were developed to promote understanding of key issues in efficiency and sustainability of dairy farming. These include materials with teacher's guides for K-12 education divided into grades K-2, 3-5 and middle school. Electronic materials were developed for college undergraduate students, including a resource of historic milk production and feed efficiency data and a spreadsheet to calculate feed efficiency and income over feed cost. A hand book was also prepared for the general public. Team meetings. In the past year, a team meeting was held in July in Florida in conjunction with the annual meetings of the American Dairy Science Association. The focus of the meeting was on methods for analysis of phenotype and pedigree-based heritability, collaborations with USDA Beltsville for genotyping, and sharing of data (all Aims 1 and 2). Discussions were also held for Aims 3, 4, and 5.

Publications

  • Type: Journal Articles Status: Published Year Published: 2016 Citation: VandeHaar, M. J., L. E. Armentano, K. Weigel, D. M. Spurlock, R. J. Tempelman, and R. Veerkamp. 2016. Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency. J. Dairy Sci. 99:4941-4954.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Manzanilla-Pech, C., R.F. Veerkamp, R.J. Tempelman, M.L. van Pelt, K.A. Weigel, M.J. VandeHaar, T.J. Lawlor, D.M. Spurlock, L.E. Armentano, E.E. Connor, C.R. Staples, M. Hanigan, Y. De Haas. 2016. Genetic parameters between feed-intake-related traits and conformation in 2 separate dairy populations-the Netherlands and United States. J. Dairy Sci. 99(1):443-57. doi: 10.3168/jds.2015-9727.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Boerman, J. P., S.B. Potts, M.J. VandeHaar, and A.L. Lock. 2015. Effects of partly replacing dietary starch with fiber and fat on milk production and energy partitioning. J. Dairy Sci. 98:7264-7276.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Hardie,L., L. E. Armentano, R. D. Shaver, M. J. VandeHaar, D. M. Spurlock, C. Yao, S. J. Bertics, F. E. Contreras-Govea, and K. A. Weigel. 2015 Considerations when combining data from multiple nutrition experiments to estimate genetic parameters for feed efficiency. J. Dairy Sci. 98:2727-2737.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2016 Citation: VandeHaar, M.J. 2016. Understanding the physiological aspects to improving feed efficiency in dairy cows. Tri-State Dairy Nutr Conf., Fort Wayne, IN, April 19.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2016 Citation: VandeHaar, M.J. 2016. Harnessing the drivers of feed efficiency to improve sustainability of the dairy industry. Ontario Dairy Symposium. Toronto. Mar 22.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Lu, Y., M. VandeHaar, D. Spurlock, K. Weigel, L. Armentano, D. Staples, E. Connor, Z. Wang, N. Bello, and R. Tempelman. 2015. An alternative approach to modeling genetic merit of feed efficiency in dairy cattle. J Dairy Sci 98:6535-6551.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Boerman, J. P., S.B. Potts, M.J. VandeHaar, M.S. Allen, and A.L. Lock. 2015. Milk production responses to a change in dietary starch concentration vary by production level in dairy cattle. J. Dairy Sci. 98:4698-4706.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2016 Citation: VandeHaar, M.J. 2016. How nutritionists can influence breeding goals for improved feed efficiency. Pacific NW Animal Nutr Conf., Boise, ID, Jan. 19.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Tempelman, R.J. An alternative approach to modeling genetic merit of feed efficiency. Presented at NCERA-225 (Implementation and Strategies for National Beef Cattle Genetic Evaluation), North Dakota State University, Fargo, ND., October 22-23,2015.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Kalantari, A. S., L. E. Armentano, R. D. Shaver, and V. E. Cabrera. 2015. Economic impact of nutritional grouping in dairy herds. Journal of Dairy Science 98 (Suppl. 2): M279.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Pech Cervantes, A. A.*, K. G. Arriola, J. E. Zuniga*, I. M. Ogunade*, Y. Jiang*, T. F. Bernardes*, C. R. Staples, and A. T. Adesogan. 2015. Effect of an exogenous fibrolytic enzyme on the performance of dairy cows consuming a diet with a high proportion of bermudagrass silage. J. Dairy Sci. 98 (Suppl. 2):143.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Kalantari A. S., L. E. Armentano, R. D. Shaver, and V. E. Cabrera. 2016. Economic impact of nutritional grouping in dairy herds. Journal of Dairy Science 99:16721692.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Cabrera, V. E., and A. S. Kalantari. 2016. Economics of production efficiency: Nutritional grouping. Journal of Dairy Science 99:825841.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Cabrera, V. E. 2015. Economics of production efficiency: Nutritional grouping. Journal of Dairy Science 98 (Suppl. 2): 350.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2016 Citation: Cabrera, V. E. Impact of Nutritional grouping on the economics of dairy production efficiency. Tri-State Dairy Nutrition Conference. Grand Wayne Center, Fort Wayne, Indiana, April, 2016.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Cabrera, V. E. Critical aspects of profitability  nutritional grouping & feed pricing. University of Barcelona. Barcelona, Spain. November, 2015.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Kalantari, A. S., L. E. Armentano, R. D. Shaver, and V. E. Cabrera. 2015. Economic impact of nutritional grouping in dairy herds. Dairy Cattle Reproduction Council Annual Meeting, Buffalo, NY. November, 2015.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Cabrera, V. E. Fundamentals of profitability  nutritional grouping & best feed pricing. Fiere Zootecniche Internazionali di Cremona 2015. Cremona, Italy, October 2015.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Cabrera, V. E. Decisions of profitability - nutritional grouping. Rio Cuarto, Cordoba, Argentina. Workshop, September 2015.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Hardie, L. C. and D. M. Spurlock. 2015. Thermal imaging as an indicator of feed efficiency in mid-lactation Holstein cows. J. Dairy Sci. 98(Suppl. 2):526 (Abstr.)
  • Type: Other Status: Published Year Published: 2016 Citation: Hardie, Lydia C. and Spurlock, Diane M. (2016) "Regions of the Genome Associated with Mid-Lactation Feed Efficiency in Dairy Cattle," Animal Industry Report: AS 662, ASL R3070. Available at: http://lib.dr.iastate.edu/ans_air/vol662/iss1/31


Progress 05/01/14 to 04/30/15

Outputs
Target Audience:Target audience includes other researchers as well as extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. Changes/Problems:Because of a lower heritability than expected, our goal is now to collect data on 10,000 cows instead of 8000. What opportunities for training and professional development has the project provided?Forty five undergraduate students were given research and extension training and experience in year 4 (15 at Florida, 6 at ISU, 10 at MSU, 4 at NCAT, and 10 at VT). They were involved in collecting feed intake and feed composition data, conducting DM analyses, collecting milk, feces, and blood samples, and processing and analyzing samples. Of these, four were minority students. How have the results been disseminated to communities of interest?Eight manuscripts resulting from the project were published in year 4 from members of our group related to aims 2, 3, and 4, and several more were submitted. Some of these publications resulted from joint efforts with a European consortium to leverage funds, and some were partly funded by other external sources. In addition, 34 presentations, accompanied by 30 publications, were presented in year 4 at the annual meetings of the American Dairy Science Association, at the 10th World Congress on Genetics Applied to Livestock Production, and at several nutrition and management conferences. An online decision support application, Grouping strategies for feeding lactating dairy cattle, was developed to assist with nutritional grouping decisions for improved efficiency and income over feed cost. The application has been used >2200 times since May 1, 2014. The other online support tool, FeedVal, has been used 3360 times since May 1, 2014. In addition, several presentations were made to farmers, consultants, and feed industry personnel in year 4 to show the benefits of nutritional grouping and feed efficiency for sustainable agriculture and receive feedback on our plans. A series of presentations were given across the state of WI to educate farmers on new developments to improve feed efficiency. What do you plan to do during the next reporting period to accomplish the goals?Project is proceeding as per original timeline. By leveraging funds, we have been able to incorporate more than one diet into some of our studies and thus have opportunity for direct analysis of genetics x diet interactions. In addition, we have been able to include some mechanistic measures such as digestibility in new cow studies.

Impacts
What was accomplished under these goals? Aim 1: Development of feed efficiency database. Original plans for our 5-year project were to compile a database of 8000 cows with a phenotype for feed efficiency and genotypes with 60% 3k-density and 40% 50k-density SNP platforms. We are on target with our goals for acquiring feed efficiency phenotype traits. As of January 28, 2015, we have recorded 6885 cows with at least one phenotype (>28-d record for feed efficiency) in our database (205 MI, 857 WI, 391 FL, 832 IA, 120 VA, 2188 NL, 1038 United Kingdom, 289 USDA-ARS Beltsville, 287 Alberta, 174 Purina, and 58 Cargill). Of these, about 4700 are currently linked to genotypes. Approximately 1000 of the cows are from NL or UK and no longer have DNA available, and the remaining cows are yet to be genotyped or linked to genotypes. In the past year, we added 569 cows from the University of Alberta and USDA-ARS, and set up relationships with both places to continue to receive data in the next year at very low cost (supplies and technical support time). We will exceed the original goals for the project in several areas related to Aim 1. All of our genotypes are with SNP platforms of 50K or greater, whereas we originally planned to genotype 60% of the cows at only 3K. Moreover, we have been working with Dr. George Wiggans at USDA Beltsville to ensure accuracy of pedigrees and genotype data and to impute genotypes to even higher levels. In addition, although some of our cows do not have genotypes, recent methodological advances will enable us to impute 50k genotypes for some of them by using genotypes of sires, maternal grandsires, and maternal great-grandsires. Finally, new genomic predictions have moved to an "H matrix" approach that allows inclusion of all phenotyped animals, regardless of whether or not they have genotypes. Thus, we expect that all 8000 cows will be used in our genomic predictions of feed efficiency. The bigger challenge we face is that based on the data we have collected to date, we now know that we will need more than 8000 cows that to achieve the desired level of accuracy in our genomic prediction. This challenge is addressed later in the report. Aim 2: Determine the genetic architecture of feed efficiency in lactating dairy cattle and build a foundation for genomic selection of more efficient animals. During the past year, we continued analysis on the genetic architecture of feed efficiency. We are currently on target for analyzing data and reporting results of aim 2, and we have done additional work related to aim 2 on repeatability of efficiency. A pedigree-based genetic analysis of the first 5000 cows estimated the heritability of residual feed intake at 0.18. This foundational paper for our project was published in March, 2015. We also began analysis of SNP data of the first 4000 cows with results presented in summer of 2014. Aim 3: Facilitate genomic selection tools. In our original timeline, activity for Aim 3 was scheduled for years 4 and 5. However, initial discussions on how to implement efficiency into breeding goals were held in year 3 in Wageningen in conjunction with our European partners (gDMI group) and in Chicago at Discover Conference #26. These discussions have continued and will take place again in summer of 2015 and in the spring of 2016. Aim 3 is on schedule. Aim 4: Development of decision-support tools. Aim 4a was to examine and refine current nutrition models using data from our study and published data. The model evaluation work is ongoing and we anticipate submitting a publication summarizing our work in May of 2015. Additional work to address identified problems will proceed in concert with NRC committee efforts and the help of Robin White from the National Animal Nutrition Program. This work is on schedule and will be completed late in 2015. Evaluations of the revised model using the project data will occur in early 2016. A new M.S. student has been identified to work at VT on this aim in year 5. Aims 4b to 4d were to develop decision-support tools. Results of our survey tool on herd management related to feed efficiency were published in year 4. The survey demonstrated that many farms do not optimally groups cows to enhance efficiency. An online decision support application, Grouping strategies for feeding lactating dairy cattle, was developed to assist with nutritional grouping decisions for improved efficiency and income over feed cost. The application has been used >2200 times since May 1, 2014. The other online support tool, FeedVal, has been used 3360 times since May 1, 2014. In addition, several presentations were made to farmers, consultants, and feed industry personnel in year 4 to show the benefits of nutritional grouping and feed efficiency for sustainable agriculture and receive feedback on our plans. These are listed in publications and presentations below. A series of presentations were given across the state of WI to educate farmers on new developments to improve feed efficiency. We are on schedule to achieve the goals set forth in Aim 4. Aim 5: Development of educational resources. Meetings were held to discuss for classes, workshops, study-abroad programs, tool-development, and research internships; Increased emphasis on feed efficiency was given in courses at all partner universities. Forty five undergraduate students were given research and extension training and experience in year 4 (15 at Florida, 6 at ISU, 10 at MSU, 4 at NCAT, and 10 at VT). They were involved in collecting feed intake and feed composition data, conducting DM analyses, collecting milk, feces, and blood samples, and processing and analyzing samples. Of these, four were minority students. In addition, key connections were made between our 1890s partner, North Carolina A&T, and other partners with NCAT students doing summer research at Iowa State University. A module was developed at NCAT for use in teaching students about assessing genetic variation at the genome level. Efforts to develop new resources for teaching have been renewed for the remainder of year 4 and for year 5, this effort has been renewed. This renewed effort is summarized in the section on Plans for Year 5. To date, a new post-doctoral scientist has been hired at WI under the direction of Co-PD Wattiaux, and the team has begun developing a "national curriculum" for K-12 on the importance of feed efficiency for the "sustainability" of the dairy industry.

Publications

  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Akins, M.S., K. L. Perfield, H. B. Green, S. J. Bertics, and R. D. Shaver. 2014. Effect of monensin in lactating dairy cow diets at two starch concentrations. J. Dairy Sci. 97:917-929.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Berry, D., M. Coffey, J. Pryce, Y. de Haas, P. Lovendahl, N. Krattenmacher, J. Crowley, Z. Wang, D. Spurlock, K. Weigel, K. Macdonald, and R. Veerkamp. 2014. International genetic evaluations for feed intake in dairy cattle through the collation of data from multiple sources. J. Dairy Sci. 97:3894-3905.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Contreras-Govea, F. E., V. E. Cabrera, L. E. Armentano, R. D. Shaver, P. M. Crump, D. Beede, and M. VandeHaar. 2015. Constraints for nutritional grouping in Wisconsin and Michigan dairy farms. J. Dairy Sci. 98:1336-1344.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Greco, L. F., J. T. Neves Neto, A. Pedrico, R. A. Ferrazza, F. S. Lima, R. S. Bisinotto, N. Martinez, M. Garcia, E. S. Ribeiro, G. C. Gomes, J. H. Shin, M. A. Ballou, W. W. Thatcher, C. R. Staples, and J. E. P. Santos. 2015. Effects of altering the ratio of dietary n-6 to n-3 fatty acids on performance and inflammatory responses to a lipopolysaccharide challenge in lactating Holstein Cows. J. Dairy Sci. 98:602-617.
  • Type: Journal Articles Status: Accepted Year Published: 2015 Citation: Hardie,L., L. E. Armentano, R. D. Shaver, M. J. VandeHaar, D. M. Spurlock, C. Yao, S. J. Bertics, F. E. Contreras-Govea, and K. A. Weigel. 2015 Considerations when combining data from multiple nutrition experiments to estimate genetic parameters for feed efficiency. J. Dairy Sci. 98:xxx. (in press).
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Tempelman, R. J., D. M. Spurlock, M. Coffey, R. F. Veerkamp, L. E. Armentano, K. A. Weigel, Y. de Haas, C. R. Staples, Y. Lu, and M. J. VandeHaar. 2015. Heterogeneity in genetic and non-genetic variation and energy sink relationships for residual feed intake across research stations and countries. J. Dairy Sci. 98:2013-2026.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Yao, C., L. E. Armentano, M. J. VandeHaar, and K. A. Weigel. 2015. Short communication: Use of single nucleotide polymorphism genotypes and health history to predict future phenotypes for milk production, dry matter intake, body weight, and residual feed intake in dairy cattle. J. Dairy Sci. 98:2027-2032.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Boerman, J.P., S. E. Burczynski, M. J. VandeHaar, and A. L. Lock. 2014. Effects of diets differing in starch, fiber, and fatty acid concentrations on milk production and energy partitioning. Abstract 604 at the Fed Animal Sci Soc. J Dairy Sci 97(E-Suppl)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Burczynski, S.E., J. P. Boerman, A. L. Lock, M. S. Allen, and M. J. VandeHaar. 2014. Relationship Between digestibility and residual feed intake in lactating Holstein cows fed high and low starch diets. Abstract 346 at the Fed Animal Sci Soc. J Dairy Sci 97(E-Suppl)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Contreras-Govea, F. E. V. E. Cabrera, L. E. Armentano, R. D. Shaver, and P. M. Crump. 2014. Constraints for nutritional grouping in Wisconsin dairy farms. J. Animal Science 91 (E-Suppl. 2):TH192.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Potts, S. B., J. P. Boerman, A. L . Lock, M. S. Allen, and M. J. VandeHaar. 2015. Residual feed intake is repeatable for lactating Holstein dairy cows fed high and low starch diets. J Dairy Sci 98:4735-4747.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: de Haas, Y., J. E. Pryce, M. P. L. Calus, I. Hulsegge, D. M. Spurlock, D. Berry, E. Wall, P. Lovendahl, K. A. Weigel, K. Macdonald, F. Miglior, N. Krattenmacher, and R. F. Veerkamp. 2014. Genomic predictions for dry matter intake using the international reference population gDMI. Proc. 10th World Congress on Genetics Applied to Livestock Production, August 17-23, Vancouver, BC.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Hagen, A. L., L. F. Ferraretto, R. D. Shaver, and R. Martin. 2014. Effect of dietary monensin supplementation and amino acid balancing on lactation performance by dairy cows. J. Dairy Sci. 97(E-Suppl. 1): (Abstr.).
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Klingensmith, E. E., L. Harthan, and M. D. Hanigan. 2014. The Effect of Starch Digestibility of Two Corn Silage Varieties on Lactation Performance in Dairy Cows. J. Dairy Sci. 97 (E. Suppl. 1): 304.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Lu, Y.F., M. J. Vandehaar, K. A. Weigel, L. E. Armentano, D. M. Spurlock, C. R. Staples, E. E. Connor, and R. J. Tempelman. 2014. An Alternative Approach to Modeling Genetic Merit of Feed Efficiency in Dairy Cattle. Proc. Of 10th World Congress of Genetics Applied to Livestock Production. Abstr. 112.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Romero, J. J., E. G. Macias, Z. Ma, R.M. Martins, Y. Coy, F. M. Silva, D. H. Garbuio, I. A. Brody, C. L. Curry, K. J. Mills, M. G. Zenobi, C. R. Staples, and A. T. Adesogan. 2014. Improving the performance of dairy cattle with a xylanase-rich exogenous enzyme preparation. J. Dairy Sci. 97E(Suppl. 1):326.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Spurlock, D. M., R. J. Tempelman, K. A. Weigel, L. E. Armentano, G. R. Wiggans, R. F. Veerkamp, Y. de Haas, M. P. Coffey, M. D. Hanigan, C. Staples, and M. J. VandeHaar. 2014. Genetic architecture and biological basis of feed efficiency in dairy cattle. Proc. 10th World Congress on Genetics Applied to Livestock Production, August 17-23, Vancouver, BC (Abstr. 287).
  • Type: Other Status: Other Year Published: 2014 Citation: Cabrera, V. E., L. Armentano, and R. D. Shaver. 2014. FeedVal v. 6.0 (former FeedVal 2012). Estimates the market value of dairy feed ingredients. Online application. Video demonstration (5:12 minutes). Decision support tool completely re-programmed and updated to comply with user demands.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: VandeHaar, M.J., Y. Lu, D. M. Spurlock, L. E. Armentano, K. A. Weigel, R. F. Veerkamp, M. Coffey, Y. de Haas, C. R. Staples, E. E. Connor, M. D. Hanigan, R. J. Tempelman. 2014. Phenotypic and genetic correlations among milk energy output, body weight, and feed intake, and their effects on feed efficiency in lactating dairy cattle. Abstract 157 at the Fed Animal Sci Soc. J Dairy Sci 97(E-Suppl)
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Weigel, K. A., C. Yao, P. C. Hoffman, L. E. Armentano, D. M. Spurlock, R. J. Tempelman, and M. J. VandeHaar. 2014. Improving biological and economic aspects of feed efficiency through genetic selection and genome-guided replacement management. Proc. 10th World Congress on Genetics Applied to Livestock Production, August 17-23, Vancouver, BC (Abstr 285).
  • Type: Other Status: Other Year Published: 2014 Citation: Cabrera, V. E. 2014. Grouping strategies for feeding lactating dairy cattle. Calculates the value of nutritional grouping. Online application. Video demonstration (7:18 minutes). Decision support tool completely re-programmed to improve design and to become content layout responsive.
  • Type: Other Status: Other Year Published: 2014 Citation: Cabrera, V. E. and F. Contreras-Govea. 2014. Nutritional grouping in Wisconsin and Michigan dairy farms. This tool is a live summary of data collected from a survey sent to 1,771 farms from Wisconsin and Michigan (WI=971, MI=800) in 2012.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Armentano, L.E. and K. Weigel 2014. Considerations for improving feed efficiency in dairy cattle. ExpoLeche San Marcos Simposium Inernational Lechero. April 23-25. Aguas Calientes Mexico. Oral presentation and prepared paper.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Armentano L. E. and R Shaver. 2015 The cost of success: examining feed cost, feed efficiency and Income over feed costs at Rosy Lane Dairy. Blanca International Dairy Workshop. Els Hostalets de Tost 27595 Lleida, Spain January 13-14. (Including paper updated from previous extension talks).
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Cabrera, V. Strategies to improve economic efficiency. Shur-Gain Dairy Seminar. Stratford, Canada. 11/18-19 2014
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Cabrera, V. Group feeding management in dairy farming. XIX International Congress of Bovine Medicine. Oviedo, Spain 06/26/2014
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Cabrera, V. Group feeding. Improvement of the dairy farm enterprise. Continued Professional Development. Blanca from the Pyrenees. Lleida, Spain. 06/12/14
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Cabrera, V. Strategies to improve economic efficiency of the dairy. Western Dairy Canadian Dairy Seminar. Red Deer, Canada.3/12/2014
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Yao, C., X. Zhu, and K. A. Weigel. 2014. Semi-supervised learning algorithm for improving genomic prediction accuracy in residual feed intake. Proc.10th World Congress on Genetics Applied to Livestock Production, August 17-23, Vancouver, BC.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Contreras-Govea, F.E., V.E. Cabrera, R.D. Shaver, D.K. Beede, L.E. Armentano and M.J. VandeHaar. 2015. Nutritional grouping bolsters feed efficiency. Hoards Dairyman. Feb. 10th issue; Page 92
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: VandeHaar MJ 2014 Feeding for maximum efficiency throughout the lactation. Dairy Influencers Meeting, Sept 20, Hawley, PA
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: VandeHaar MJ 2014 Improving feed efficiency in dairy cattle. Proc 4-State Dairy Nutr Mgt Conf, June 11-12, Dubuque, IA, pp. 27-33.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: VandeHaar MJ, Weber Nielsen MS 2014 Intensified calf feeding programs. Proc 4-State Dairy Nutr Mgt Conf, June 11-12, Dubuque, IA, pp. 44-46
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: VandeHaar MJ 2014 Dietary strategies to improve feed efficiency. Proc XIX ANEMBE Internatl Congress, June 25-27, Oviedo, Spain
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: VandeHaar MJ 2014 Opportunities to create a more efficient cow through genomic selection. Proc XIX ANEMBE Internatl Congress, June 25-27, Oviedo, Spain
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: VandeHaar MJ 2014 Opportunities for improving feed efficiency. Proc Tri-State Dairy Nutr Conf., April 14-16, Fort Wayne, IN, pp. 133-144.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: VandeHaar MJ 2014 Feeding and breeding for a more efficient cow. Proc West Canada Dairy Seminar, March 12, Red Deer, Alberta, Canada.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Weigel, K. A. 2014. Integration of feed efficiency into a selection index, Holstein Association USA Type Advisory Committee, Mar 4-5, Madison WI.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Weigel, K. A. 2014. Will genomic selection be the key to improving feed efficiency in dairy cattle? Four-State Dairy Nutrition and Management Conference, June 11-12, Dubuque, IA.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Weigel, K. A. 2014. Will genomic selection be the key to improving feed efficiency in dairy cattle? Progressive Dairyman, June issue.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2014 Citation: Weigel, K. A, and C. Yao. 2014. Exploring feed efficiency in dairy cattle from the genetic side. CRI/Genex Research Workshop, July 8, Shawano, WI.
  • Type: Other Status: Other Year Published: 2014 Citation: Contreras, F. Agricultural and Natural Resources Extension Dairy Team Annual Meeting. October 20th, 2014, Wisconsin Dells. A 10 min presentation was given to WI Extension County Agents about the Feed Efficiency project. The main goal of this presentation was to encourage the Extension County Agents to organize a workshop in their county about feed efficiency. The response was very successful, and workshop is in its way in 6 counties on 2015 where Drs. Victor Cabrera, Randy Shaver, and Francisco Contreras-Govea, are giving talks about feed efficiency. (see below)
  • Type: Other Status: Other Year Published: 2015 Citation: Contreras, Cabrera, and Shaver. Improving feed efficiency. Ongoing roadshow during Jan and Feb (2015) in Wisconsin with 8 locations across the state with about 20 participants per location. Jan-Feb 2015. Speakers include Contreras-Govea, F.: Survey results Cabrera, V. E.: Nutritional grouping strategies Shaver, R. D.: Feed efficiency on dairy cattle


Progress 05/01/13 to 04/30/14

Outputs
Target Audience: Target audience includes other researchers as well as extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. Discover Conference #26 on Dairy Feed Efficiency was initiated and organized mostly by our project group, as per our original proposal, and had 150 attendees, including scientists, farm consultants, and industry leaders from several countries as well as throughout the US. Changes/Problems: Minor changes to the overall grant were described in the accomplishments section. What opportunities for training and professional development has the project provided? Increased emphasis on feed efficiency was given in courses at all partner universities. Fifty one undergraduate students were given research and extension training and experience in year 3. Of these, five were minority students. Discover Conference #26 on Dairy Feed Efficiency was held September 23-26 in Napierville, IL. This conference was part of our original project proposal. Dr. VandeHaar co-chaired the conference and 4 of the 6 conference committee members were members of our grant. Of the 17 presentations, 7 were from members of our NIFA project. Almost all members of our project team were present. This conference gave us the opportunity to present our work and ideas to an audience of 160 key leaders in dairy nutrition, genetics, and management from universities and companies across the US and world. In addition, members of our grant team have given 29 additional presentations related to the scope of this project to professional groups. How have the results been disseminated to communities of interest? Results were disseminated in 6 refereed journal articles and 14 conference proceedings or professional abstracts. Our team initiated and provided most of the programmatic leadership for Discover Conference #26 on Dairy Feed Efficiency. Of the 17 presentations, 7 were from members of our NIFA project. This conference gave us the opportunity to present our work and ideas to an audience of 160 key leaders in dairy nutrition, genetics, and management from universities and companies across the US and world. In addition, members of our grant team have given 29 additional presentations related to the scope of this project to professional groups. What do you plan to do during the next reporting period to accomplish the goals? Plans for year 4 include phenotyping and genotyping an additional 860 new cows to bring our dataset to 5500 cows of the grant Co-PIs. Although we are currently behind on genotyping cows, we are on target for phenotyping. The addition of the University of Alberta will help us achieve our goals for animal numbers, and we are in discussions with Zoetis to provide partial support to attract new data from research farms in Georgia and Wisconsin. Combined with additional existing and new international partners from Europe and Australia, we should have ~7000 cows for use in our analysis of the genomics of feed efficiency at the end of year 4, as originally planned. During year 4, we will continue to examine heritability of feed efficiency and genetic relationships to other traits using new tools created by co-PI Tempelman. We also will continue characterizing inheritance at the genomic level and identifying SNP associated with efficient phenotypes. We will further our efforts to develop a new breeding index that incorporates feed efficiency. Whether a new index includes genomic breeding values for RFI or DMI is yet to be determined, but at the least, our project will help to determine the appropriate weighting factors to use for cow size versus milk yield. We will work closely with USDA scientists at the Animal Improvement Program Laboratory in Beltsville. As per our original plan for aim 4, we will improve the farm decision tools developed by co-PI Cabrera that integrate management of reproduction, culling, grouping, and feeding to enhance feed efficiency, and we will test these on farms, along with new concepts in nutritional grouping. We will also begin including ration data with individual cow data to examine nutritional models which might be useful for the next NRC Dairy committee. This commitee is currently being formed and we expect the new committee will include at least one of our NIFA project team and that data from the current project will be an important tool for use in developing the next Dairy NRC. For aim 5, we will continue to mentor undergraduates in research, and we will renew our efforts to develop educational resources and to train undergraduates as advocates for the role of efficiency in sustainable dairy farming. Although we are currently behind in developing teaching resources, co-PI Worku at NCAT has developed resources she will share with othe co-PIs, and we are renewing our efforts with leadership from Co-PIs Nielsen and Beede (Beede previously was involved mostly in Aim 4). We anticipate achieving our Year 4 plans in a timely fashion (see original attached table of our management plan).

Impacts
What was accomplished under these goals? Abbreviations in this report are: Michigan State University (MI), University of Wisconsin (WI), Iowa State University (IA), Wageningen UR in the Netherlands (NL), University of Florida (FL), Virginia Tech (VA), and North Carolina A&T (NC). Aim 1: Development of feed efficiency database. To date, we are on target with our planned goals for phenotyping but behind on genotyping. As of January 20, 2014, we had recorded 5380 individual cow phenotypes in our databases (161 MI, 506 WI, 255 FL, 699 IA, 73 VA, 1832 NL, 1052 United Kingdom, 292 Beltsville, 178 Purina, and 58 Cargill). Of these, about 1000 are cows for which DNA is no longer available. For the remaining cows, some are either not yet linked to genotype or not yet genotyped. Thus, we currently are ahead of schedule for phenotyping but about 30% behind on genotyping. Reasons for this delay include 1) a 6% budget cut in year 1, 2) unanticipated difficulties in accurately linking genotype and phenotype data from so many sources, and 3) difficulty obtaining quality data from cooperator herds–those herds that were receiving almost no compensation for data. To obtain more data from cooperator herds, we are changing our approach. We are freeing up funds from some co-PIs when possible, and we are in discussions with Zoetis to help fund data collection and summarization from additional research herds. We also established a collaboration with the University of Alberta to provide data on 280 cows to us at almost no cost. We anticipate this will help us catch up with our goals for the end of year 4. On the positive side, all of our genotypes are with 50K or greater SNP chips, which exceeds the goals laid out in our original project. We have been working with Dr. George Wiggans at USDA Beltsville to ensure accuracy of pedigrees and genotype data and to impute genotypes to higher levels. Aim 2: Determine the genetic architecture of feed efficiency in lactating dairy cattle and build a foundation for genomic selection of more efficient animals. During the past year, we continued analysis on the genetic architecture of feed efficiency. Six manuscripts were published or accepted for publication to date in year 3 from members of our group related to this aim, and at least two more will be submitted before the end of year 3. Some of these publications were only partly funded through NIFA as we joined efforts with a European consortium to leverage funds. In addition, several abstracts were presented in year 3 at the annual meetings of the American Dairy Science Association. Thus, we are currently ahead of our targets for analyzing data and reporting results of aim 2. A pedigree-based genetic analysis of the first 5000 cows found that the heritability of residual feed intake was ~0.16. This foundational paper for our project will be published in year 4. We also began initial analysis of SNP data of the first 3000 cows with results to be presented in summer of 2014. In addition, we found RFI to be a repeatable trait across diets, lactation, and day within lactation. In general, we are ahead of schedule for aim 2. Aim 3: Facilitate genomic selection tools. Activity for aim 3 was scheduled for years 4 and 5. However, initial discussions on how to implement efficiency into breeding goals were held in Wageningen and in Chicago at Discover Conference #26. Thus, we are ahead of schedule on aim 3. Aim 4: Development of decision-support tools. Methodology was developed to conduct Aim 4a using SAS and an excel version of the dairy NRC. Initial analyses were conducted on data from the literature to examine adequacy of the NRC model, this methodology can easily be adapted to conduct the same evaluations with the individual animal observations collected in the project. Aims 4b to 4d were to develop decision-support tools. A survey tool was sent to 1800 farmers in WI and MI in year 2 to evaluate herd management related to feed efficiency. In our original grant proposal, we planned to also survey farms in CA, FL, IA, and VA, but we decided the responses from those states (where we did not have paid personnel in place to conduct the surveys) would be inadequate to be meaningful. Results from 400 farms (200 MI, 200 WI)) have now been analyzed. The survey demonstrated that many farms do not optimally groups cows to enhance efficiency. An online decision support application, Grouping strategies for feeding lactating dairy cattle, was developed to assist with nutritional grouping decisions for improved efficiency and income over feed cost. The application was used 1500 times from May 1, 2013, to February, 2014. In addition, at least 6 presentations were made to farmers, consultants, and feed industry personnel in year 3 to show the benefits of nutritional grouping and feed efficiency for sustainable agriculture and recieve feedback on our plans. We are on schedule for most of Aim 4. Aim 5: Development of educational resources. Meetings were held to discuss for classes, workshops, study-abroad programs, tool-development, and research internships; Increased emphasis on feed efficiency was given in courses at all partner universities. Fifty one undergraduate students were given research and extension training and experience in year 3. They were involved in collecting feed intake and feed composition data, conducting DM analyses, collecting milk, feces, and blood samples, and processing and analyzing samples. Of these, five were minority students. In addition, key connections were made between our 1890s partner, NCAT, and other partners with NCAT students doing summer research at VA and IA. A module is being developed at NCAT for use in teaching students about assessing genetic variation at the genome level. However, we are behind schedule in developing new resources for teaching. For year 4, we are shifting more of the leadership for teaching objectives to Drs. Nielsen and Beede at MI. We are partnering with MI Farm Bureau to develop a dairy ag advocacy training program and to develop resources for use in undergraduate courses, the Dairy Challenge, and K-12 educational materials. Web Page. The project web page was completed and can be seen at dairy-efficiency.org. Team meetings. In the past year, a team meeting was held in July in Indianapolis in conjunction with the annual meetings of the Am Dairy Sci Assoc. The focus of the meeting was on methods for analysis of phenotype and pedigree-based heritability, collaborations with USDA Beltsville for genotyping, and sharing of data (all aims 1 and 2). In September, team meetings were held before and during Discover Conference 26 to discuss progress and challenges on all aims. We made decisions related to analyzing RFI, learned about the work of our European partners in the genetics of feed intake project, strategized about how to use RFI or DMI in a breeding index, updated each other on the work of our students, gave feedback to those working on aim 4, and discussed plans for aim 5. In November, we also met with researchers at Zoetis to discuss how we could collaborate to obtain more data for Aim 1 and to identify possible mechanisms underlying feed efficiency that were not proposed in the initial grant. Discover Conference. DC26, Dairy Feed Efficiency, was held September 23-26 and was part of our original project proposal. We received important feedback that will be used as we revise our plans in Aims 3 and 4 for building extension tools. For example, we realized that RFI is poorly understood by even those in academia and that we must be careful in framing how we use it to describe efficiency in any breeding goal tool. We foresee major changes in rankings of dairy bulls in the next few years due to the enhanced focus on feed efficiency associated with our NIFA-funded project.

Publications

  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Yao, C., D. M. Spurlock, K. A. Weigel, L. E. Armentano, C. D. Page, Jr., and M. J. VandeHaar. 2013. Random Forest Approach for Identifying Additive and Epistatic SNPs Associated with Residual feed Intake in Dairy Cattle. J Dairy Sci 96:6716-6729.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Berry, D.P., M.P. Coffey, J.E. Pryce, Y. de Haas, P. Lovendahl, G. Thaller, J.J. Crowley, D. Spurlock, K. Weigel, K. MacDonald, and R.F. Veerkamp. 2013. International genetic evaluations for feed intake in dairy cattle. Pages 15-22 in Proc. of the 47th Interbull meeting, Nantes, France, 23-25 August.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Burczynski, S.E., J.S. Liesman, R.J. Tempelman, J.C. Ploetz, M.S. Allen, A.L. Lock, and M.J. VandeHaar. 2013. Residual feed intake is repeatable when high and low starch diets are fed to lactating Holstein dairy cows. J. Dairy Sci. 96(E-Suppl.):397. Abstr 331 presented at Fed Anim Sci Soc, Indianopolis, July 8-10.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Burczynski, S.E., J.S. Liesman, R.J. Tempelman, J.C. Ploetz, M.S. Allen, A.L. Lock, and M.J. VandeHaar. 2013. Residual feed intake is repeatable when high and low starch diets are fed to lactating Holstein dairy cows. Page 168 in Proc Tri State Dairy Nutr Conf., April, Fort Wayne, IN.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2012 Citation: Cabrera, V. E., F. Contreras, R. D. Shaver, L. E. Armentano. 2012. Grouping strategies for feeding lactating dairy cattle. Pages 40-44 in Proceedings Four-State Dairy Nutrition and Management Conference, Dubuque, IA, 13-14 June.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Contreras-Govea, F. E., V. E. Cabrera, L. E. Armentano, R. D. Shaver, and P. M. Crump. Constraints for nutritional grouping in Wisconsin dairy farms. Journal of Animal Science 91 (E-Suppl. 2):TH192.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: de Haas, Y., Jennie Pryce, Jan Dijkstra, Eileen Wall, Roel Veerkamp. 2013. Genetic solutions to improve resource efficiency in dairy cattle. Pages 303-306 in the 20th Proc. Assoc. Adv. Animal Breeding and Genetics (AAABG) conference, Napir, New Zealand, October 20-23.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Hanigan, M. D., C. R. Angel, C. F. M. de Lange, E. Kebreab, J. P. McNamara, L. O. Tedeschi, N. L. Trottier, and M. J. VandeHaar. 2013. The National Animal Nutrition Program (NANP): Modeling Subcommittee goals and progress. J. Dairy Sci. 96(E-Suppl.):21-22. Abstr T55 presented at Fed Anim Sci Soc., Indianapolis, July 8-10.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Ploetz, J.C., S. E. Burczynski, M. J. VandeHaar, M. S. Allen, and A. L. Lock. 2013. Milk production responses to a change in dietary starch concentration vary by production level in dairy cattle. J. Dairy Sci. 96(E-Suppl.):452. Abstr 471 at Fed Anim Sci Soc.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Shonka, B. and D. Spurlock. 2013. Genetic regulation of feed efficiency in lactating Holstein cows. ISU Department of Animal Science Animal Industry Reports, AS Leaflet-R2796.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: VandeHaar, M.J. 2013. Challenges and opportunities to enhance feed efficiency in dairy cattle. Proc Can East Nutr Conf., Quebec City.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: VandeHaar, M.J. 2013. Improving the conversion of feed to milk: challenges and opportunities. Proc XVII Curso Novos Enfoques na Produ��o e Reprodu��o de Bovinos Uberl�ndia, MG, Brazil.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Veerkamp, R., J. Pryce, D. Spurlock, D. Berry, M. Coffey, P. Lovendahl, R. van der Linde, J. Bryant, F. Miglior, Z. Wang, M. Winters, N. Buttchereit, N. Charfeddinne, J. Pedersen, and Y. de Haas. 2013. Selection on feed intake or feed efficiency: gDMI breeding goal discussion. 47th Proceedings of the 2013 Interbull meeting, Nantes, France. 23-25 August.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Veerkamp, R.F., J. E. Pryce, D. Spurlock, D. Berry, M. Coffey, P. Lovendahl, R. van der Linde, J. Bryant, F. Miglior, Z. Wang, M. Winters, N. Krattenmacher, N. Charfeddine, J. Pedersen, and Y. de Haas. 2013. Selection on feed intake or feed efficiency: A position paper from gDMI breeding goal discussions. Interbull Bulletin No. 47. Nantes, France, Aug 23-25.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Armentano, L. 2013. Optimizing Dietary Energy and Protein to Maximize Feed Efficiency. Presented at the 26th ADSA Discover Conference: Dairy Feed Efficiency. September 23-26. Naperville, IN.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Cabrera, V. E. 2013. Grouping strategies to improve feed efficiency. Presented at the 26th American Dairy Science Association Discover Conference: Dairy Feed Efficiency. Naperville, IL. 23-26 September 2013.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Hanigan, M. 2013. Efficiency of Producing Milk Components. Presented at the 26th ADSA Discover Conference: Dairy Feed Efficiency. September 23-26. Naperville, IL.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Spurlock, D. 2013. Molecular and Physiological Basis of Residual Feed Intake (RFI) and Feed Efficiency. Presented at the 26th ADSA Discover Conference: Dairy Feed Efficiency. September 23-26. Naperville, IL.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Tempelman, R., R. Veerkamp, M. Coffey, D. Spurlock, L. Armentano, K. Weigel, Y. de Haas, C. Staples, M. Hanigan, and M. VandeHaar. 2013. Heterogeneity across research stations in genetic variation and energy sink relationships for feed efficiency in lactating dairy cattle. J. Dairy Sci. 96(E-Suppl.):389. Abstr 310 presented at Fed Anim Sci Soc. meetings, Indianapolis, July 8-10.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: VandeHaar MJ. 2013. Keynote address: What are our Opportunities for Improving Dairy Feed Efficiency? Presented at the ADSA Discover Conference #26, Naperville, IL, Sept 23-26.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Veerkamp, R.F., R. Tempelman, Y. de Haas, J. Pryce, D. Berry. 2013. Global Efforts to Understand the Genetics of Feed Efficiency. Presenteed at the 26th DISCOVER Conference on Food Animal Agriculture: Dairy Feed Efficiency, Naperville, IL, September 23-26.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Weigel, K. 2013. Integration of Feed Efficiency into a Selection Index. Presented at the 26th ADSA Discover Conference: Dairy Feed Efficiency. September 23-26. Naperville, IL.
  • Type: Other Status: Other Year Published: 2012 Citation: Cabrera, V. E., R. D. Shaver, and P. C. Hoffman. 2012. Feed management decision-making tools for Wisconsin dairy farms. Presented at the 2012 Agricultural and Natural Resources Conference from UW-Extension, Wisconsin Dells, 10-12 October.
  • Type: Other Status: Other Year Published: 2013 Citation: de Haas, Y., J. Pryce, C.P. Manzanilla, R. Veerkamp. 2013. Genetics of feed efficiency. Presented at the European Association of Animal Production (EAAP), Nantes, France, August 25-30.
  • Type: Other Status: Other Year Published: 2013 Citation: de Haas, Y. 2013. Feed efficiency - more than animal nutrition. Presented at the CRV-day for young farmers, Bathmen, NL, April 5.
  • Type: Other Status: Other Year Published: 2013 Citation: de Haas, Y. 2013. Update on global collaborative research in the area of genetics of feed efficiency. Presented at the FCE-workshop, Melbourne, Australia, 28-29 October.
  • Type: Other Status: Other Year Published: 2013 Citation: de Haas, Y., and J. Pryce. 2013. Genomic breeding values for improved feed efficiency in dairy cattle. Melbourne. Presented at the Australian Association of Ruminant Nutrition (AARN). October 14-15.
  • Type: Other Status: Other Year Published: 2013 Citation: Manzanilla, C.P., R. Veerkamp, J. Pryce, M. Calus, and Y. de Haas. 2013. Genetic parameters for DMI and predictor traits in Holstein cattle. Presented at the European Association of Animal Production (EAAP), Nantes, France, August 25-30.
  • Type: Other Status: Other Year Published: 2013 Citation: Spurlock, D. 2013. Feed Efficiency Research at Iowa State University. Presented at the S-1040 Regional Project Meeting, October 21-22, 2013. Chicago, IL.
  • Type: Other Status: Other Year Published: 2013 Citation: Spurlock, D. 2013. Biological Regulation of Feed Efficiency. Presented at Zoetis Workshop on Dairy Feed Efficiency. October 30, 2013. Kalamazoo, MI.
  • Type: Other Status: Other Year Published: 2013 Citation: Spurlock, D. 2013. Studies of Energy Utilization in Lactating Dairy Cows. Iowa State University Animal Breeding and Genetics Seminar Series, April 16. Ames, IA
  • Type: Other Status: Other Year Published: 2013 Citation: VandeHaar. 2013. Opportunities to improve dairy feed efficiency. Presented at Zoetis Workshop on Dairy Feed Efficiency. October 30, 2013. Kalamazoo, MI.
  • Type: Other Status: Other Year Published: 2013 Citation: Spurlock, D. 2013. Genetics of Feed Efficiency in Dairy Cattle. Presented at the Select Sires Sire Committee Meeting. March 18. Columbus, OH.
  • Type: Other Status: Other Year Published: 2013 Citation: Spurlock, D. 2013. Genomic Selection and Herd Management for Improved Feed Efficiency of the US Dairy Industry. Presented at the International Breeding Goal Meeting: Selection for Improved Feed Efficiency. February 25-26, 2013. Wageningen, Netherlands.
  • Type: Other Status: Other Year Published: 2013 Citation: McGill, T.M., M. J. VandeHaar, R. Patterson, and M. D. Hanigan. 2013. An evaluation of the Dairy NRC 2001 and Papillon Prep10 nutrient requirement models. Presented at the Modeling Workshop, Fed Anim Sci Soc, Indianapolis, July 7.
  • Type: Other Status: Other Year Published: 2013 Citation: VandeHaar MJ, and MD Hanigan. 2013. Considerations for a new dairy NRC. Presented at the Midwest ARPAS meeting, Fed Anim Sci Soc, Indianapolis, July 9.
  • Type: Other Status: Other Year Published: 2013 Citation: Weigel, K. 2013. Integrating efficiency into selection tools. Presented at Zoetis Workshop on Dairy Feed Efficiency. October 30, 2013. Kalamazoo, MI.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Calus, M.P.L., Y. de Haas, and R.F. Veerkamp. 2013. Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies. J. Dairy Sci. 96:6703-6715.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Maltz, E., L.F. Barbosa, P. Bueno, L. Scagion, K. Kaniyamattam, L.F. Greco, A. De Vries, J.E.P. Santos. 2013. Effect of feeding according to energy balance on performance, nutrient excretion, and feeding behavior of early lactation dairy cows. J. Dairy Sci. 96: 5249-5266.
  • Type: Journal Articles Status: Accepted Year Published: 2014 Citation: Pryce, J., J. Johnston, B. Hayes, G. Sahana, K. Weigel, S. McParland, D. Spurlock, N. Krattenmacher, R. Spelman, E. Wall, and M. Calus. 2014. Imputation of genotypes from low density (50k) to high density (700k) of cows from research herds in Europe, North America and Australasia using 2 reference populations. 2014. J. Dairy Sci. in press.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Pszczola, M., R. F. Veerkamp, Y. de Haas, E. Wall, T. Strabel, and M. P. L. Calus. 2013. Effect of predictor traits on accuracy of genomic breeding values for feed intake based on a limited cow reference population. Animal 7:1759 - 1768.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Spurlock, D.M., and M.J. VandeHaar. 2013. Genetics of feed efficiency in dairy cattle. CAB Reviews 8,039:1-8.


Progress 05/01/12 to 04/30/13

Outputs
Target Audience: Target audience includes other researchers as well as extension specialists, farmers, and farm consultants, graduate and undergraduate students, and the general populace. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Students in a study-abroad program in the Netherlands took pictures to use in developing K-12 teaching programs. Undergraduate students were mentored in research in feed efficiency, with 51 students directly involved in the work of Co-PDs. Of these, 3 students were interns from 1890s institutions working with other Co-PDs. In addition, 12 graduate students have been working on the project and learning about the genetics and management of feed efficiency. How have the results been disseminated to communities of interest? Results were disseminated in 1 journal article, 8 regional or international management conferences with proceedings, 5 presentations at the annual meetings of the Am Dairy Sci Assoc with corresponding journal abstracts, and several extension, university, and project seminars without proceedings. What do you plan to do during the next reporting period to accomplish the goals? Project is proceeding as per original timeline. By leveraging funds, we have been able to incorporate more than one diet into some of our studies and thus have opportunity for direct analysis of genetics x diet interactions. In addition, we have been able to include some mechanistic measures such as digestibility in new cow studies.

Impacts
What was accomplished under these goals? Aim 1: In the past year, we added 2700 phenotypes to our database to bring the total to 5300 individual cow phenotypes. This includes mostly cows from Co-PIs: 164 cows from MI, 726 from WI, 510 from IA, 190 from FL, 36 from VA, and 2450 from Wageningen UR; the total also includes 1240 cows from Scottish collaborators. Of the 5300 phenotyped cows, 3600 have been genotyped. Agreements are ongoing to secure an additional 1100 cow phenotypes and genotypes and studies are continuing at grant co-PI research farms. Thus, we are progressing as planned to reach our goal of 8000 cows during year 5. In addition, all of our genotypes are with the 50K or 80K SNP chip, which exceeds the goals laid out in our original project. Aim 2: Initial work during year 2 using only Wisconsin cows revealed heritabilities for residual feed intake (RFI) of 0.03 to 0.12 and was submitted for publication. In a seminal work for the project, we have now examined pedigree-based genetic relationships for RFI from all stations, which includes 6,113 lactations from 4,376 Holstein cows from 12 research stations in Scotland, the Netherlands, and the United States. Weekly dry matter intake (DMI) was fitted as a function of milk energy output (MilkE), metabolic body weight (metBW, BW0.75), body condition score (BCS), and change in BW (ΔBW), parity, and its interaction with parity on days in milk (DIM) ranging from 50 to 200 d as a 5th order polynomial. The residuals from this analysis are a measure of feed efficiency; i.e., RFI. Heritabilities for country-specific RFI were based on fitting random regression models and ranged from 0.08 to 0.22 depending on DIM; residual variances were particularly heterogeneous across research stations likely due in part to differences in data recording protocols. The overall heritability from 60 to 90 DIM across all research stations was 0.14 ± 0.03. Hence future genomic selection programs on feed efficiency appear to be promising. We also examined the repeatability of RFI when cows are fed high vs low starch diet on 90 MI cows. As we develop genomic selection tools for efficiency, our goal is to identify animals that are efficient on many different diets. Holstein cows averaging 670 kg of BW, 40 kg of milk/d, and 125 d postpartum at experiment start, were fed diets of high or low starch content in 3 crossover experiments with 4-wk periods. High starch diets were approximately 27% NDF and 30% starch and low starch diets were about 40% NDF and 12 to 16% starch. These differences were achieved mostly by replacing corn grain with soyhulls.High starch diets increased milk energy output by 7%, DMI by 3%, and percentage of gross energy captured as milk and body tissue (GEcap) by 9% (P < 0.01) across experiments and parity. The mean absolute difference in RFI between treatments across experiments was 0.9 kg (SD = 0.7). The correlation between RFI when cows were fed the high starch diets and RFI when cows were fed the low starch diets was 0.79 (P<0.01) and was similar within each parity and experiment. The feed efficiency measures of milk/feed, GEcap, and Income over feed cost for individual cows also were repeatable across high and low starch diets (r=0.78, 0.72, and 0.85, respectively). We concluded that RFI is reasonably repeatable for a wide range of dietary starch concentrations so that cows that are most efficient when fed high corn diets are likely also most efficient when fed diets high in non-forage fiber sources. Another goal within Aim 2 was to characterize the genomic architecture of feed efficiency and search for significant SNP relationships. The data from 400 Iowa cows were analyzed in year 2 using a random forest (RF) algorithm. Among the 15 SNPs identified as significant, 7 are located within reported quantitative trait locus intervals for RFI in beef cattle, 6 are associated with annotated genes, and 5 are located in the introns of known genes. This finding was accepted and will be published within the next year. Under the leadership of Co-PD Veerkamp, an international group began meeting in 2012 to compile a large database to examine the genetics and genomics of feed intake. Aim 4: Aim 4 included the evaluation of current nutrition models. We evaluated the Dairy NRC 2001 model using production data from 99 published studies from 1983 through 2011, using 374 diets, of which 305 included milk production data. SAS 9.3 was used to individually write each diet into a spreadsheet containing equations of the NRC model.In our preliminary analyses, we found the error of prediction for AA- and MP-allowable milk exceeds NEL-allowable milk prediction errors. Mean bias associated with NEL-allowable milk was positive (underprediction), whereas MP-allowable milk predictions tended to be negative (overprediction). A survey tool on grouping practices was developed and sent to almost 2000 farms in MI and WI. The objective was to quantify the percentage of dairy farmers that feed a single ration and identify existing constraints to grouping and precision feeding of lactating cow groups. Preliminary data are based on 200 responses from WI. Average farm size was 600 lactating dairy cows with an average of 11,700 kg milk/cow per yr. Herds with more than 250 cows gave more importance to the need for keeping pens full (P<0.03) and having a fresh cow group (P<0.01). Criteria for feeding more than one ration were not different among herd size categories. A quarter of respondents (25%) reported feeding the same ration to all lactating herd. The main constraints for feeding more than one ration were a desire to keep feeding simple (48%) and the perception that milk decreases when cows are moved to a different group (52%). We concluded that >25% of WI farms could increase feed efficiency by enhancing some management tools of grouping and nutritional feeding.A management tool, “Grouping strategies for feeding lactating dairy cattle”was developed (dairymgt.info/tools/cluster/clustering_lact1.php); it was presented in at least 1 Wisconsin, 2 national, and 2 international extension meetings, and had 2500 uses in the past year. Another tool, “FeedVal2012”, (dairymgt.info/tools/feedval_12/index.php) was developed to calculate the value of feeds; it had 4000 uses in the past year. Nine presentations were made in year 2 to educate farmers and consultants about the benefits of selecting, feeding, and managing cows for efficiency. Aim 5: Several universities have added teaching activities on genomics and feed efficiency. Most notably, at North Carolina A&T University, a genetics course incorportated more material on genomics, including a presentation by Dr. Jason Lilly from Geneseek, and laboratory modules were developed for teaching students the use of genomic tools to improve traits like efficiency. These opportunities are being shared with other 1890s institutions. A half day workshop on genotyping was held at NCAT on July 5, 2013, for 8 Agricultural education teachers and 2 high school students. General : A website for the project (dairy-efficiency.org) was developed to educate the public and other researchers, serve as a repository for publications and resources, and provide a means for interaction among collaborators using a private discussion forum with threads. An ADSA Discover Conference on Dairy Feed Efficiency was suggested by the project investigators to facilitate interaction with industry stakeholders. Most of the planning committee and many of the speakers are members of the project. Planning is complete and the conference will occur Sept 23-26, 2013. In addition, 10 presentations were made to other scientistis in year 2 at several US and international locations.

Publications

  • Type: Journal Articles Status: Published Year Published: 2012 Citation: Spurlock, DM, JC Dekkers, R Fernando, DA Koltes, and A Wolc, A. 2012. Genetic parameters for energy balance, feed efficiency, and related traits in Holstein cattle. J Dairy Sci. 95:5393-5402
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Armentano, L. 2013. Feed Efficiency of Dairy Cattle. Proc Mid-Atlantic Nutr Conf, Timmonium, Md. Mar 28. manc.umd.edu/Abstracts%202013/2013%20MANC%20Armentano%20ABSTRACT.pdf
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Armentano, L., and K. Weigel. 2013. Considerations for improving feed efficiency in dairy cattle. Proc 24th Florida Ruminant Nutr. Conf., Feb 5, 2013. dairy.ifas.ufl.edu/rns/2013/1_armentano.pdf
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Burczynski, S.E., J.S. Liesman, R.J. Tempelman, J.C. Ploetz, M.S. Allen, A.L. Lock, and M.J. VandeHaar. 2013. Residual feed intake is repeatable when high and low starch diets are fed to lactating Holstein dairy cows. J. Dairy Sci. 96(E-Suppl.):397. Abstr 331 at Fed Anim Sci Soc.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Burczynski, S.E., J.S. Liesman, R.J. Tempelman, J.C. Ploetz, M.S. Allen, A.L. Lock, and M.J. VandeHaar. 2013. Residual feed intake is repeatable when high and low starch diets are fed to lactating Holstein dairy cows. Proc Tri State Dairy Nutr Conf., April 22, p. 168.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Contreras-Govea, F.E., S. Bertics, G. A. Broderick, A. Faciola, and L. E. Armentano. 2013. Lactation performance of cows fed soybean meal or canola meal supplements. J. Dairy Sci. 96(E-Suppl.):34. Abstr T94 at Fed Anim Sci Soc.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Contreras-Govea, F. E., V. E. Cabrera, L. E. Armentano, R. D. Shaver, and P. M. Crump. 2013. Constraints for nutritional grouping in Wisconsin dairy farms. J. Dairy Sci. 96(E-Suppl.):540. Abstr TH192 at Fed Anim Sci Soc.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2012 Citation: Cabrera, V. E., F. Contreras, R. D. Shaver, L. E. Armentano. 2012. Grouping strategies for feeding lactating dairy cattle. Pp. 40-44 in Proceedings Four-State Dairy Nutrition and Management Conference. Dubuque, IA, 13-14 June 2012.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Ferraretto, L., M. Akins and R. Shaver. 2012. Dietary carbohydrate impacts on lactation efficiency. Proc. Pacific NW Anim. Nutr. Conf., Oct 24, 2012, Pasco, WA.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: McGill, T.M. and M. D. Hanigan. 2013. Improvements in feed efficiency via rumen protected amino acid supplementation limited by ration balancing software. J. Dairy Sci. 96(E-Suppl.1):264. Abstr W107 at Fed Anim Sci Soc.
  • Type: Other Status: Published Year Published: 2013 Citation: Shonka, B. and D Spurlock. 2013. Genetic regulation of feed efficiency in lactating Holstein cows. Iowa State University Animal Industry Report, R2796. ans.iastate.edu/report/air/2013pdf/R2796.pdf.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Tempelman, R., R. Veerkamp, M. Coffey, D. Spurlock, L. Armentano, K. Weigel, Y. de Haas, C. Staples, M. Hanigan, M. VandeHaar. 2013. Heterogeneity across research stations in genetic variation and energy sink relationships for feed efficiency in lactating dairy cattle. J. Dairy Sci. 96(E-Suppl.):389. Abstr 310 at Fed Anim Sci Soc.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: VandeHaar MJ 2013 Challenges and opportunities to enhance feed efficiency in dairy cattle. Proc Canadian East Nutr Conf., Quebec City, May 15.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: VandeHaar MJ 2013 Improving the conversion of feed to milk: challenges and opportunities. Proc XVII Curso Novos Enfoques na Produ��o e Reprodu��o de Bovinos Uberl�ndia, MG, Brazil, March 15.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2012 Citation: VandeHaar MJ 2012 Feeding and breeding dairy cattle to improve efficiency. Proc Pacific NW Animal Nutr Conf, Oct 24, Pasco, WA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2012 Citation: Armentano, L. 2012. What is feed efficiency? Defining it, measuring it, and improving it. Presented at Arlington Dairy Day, Arlington Research Station in Wisconsin. Dec 6, 2012. dysci.wisc.edu/events/dairyday12/What%20is%20Feed%20Efficiency%20-%20Armentano.pdf
  • Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: McGill, T.M., M. J. VandeHaar, R. Patterson, and M. D. Hanigan. 2013. An evaluation of the Dairy NRC 2001 and Papillon Prep10 nutrient requirement models. Presented at Modeling Workshop, Fed Anim Sci Soc, Indianapolis.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: Spurlock, DM. 2013. Genetics of Feed Efficiency in Dairy Cattle. Presented to Select Sires Sire Committee Meeting. March 18, 2013. Columbus, OH.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: Spurlock, DM. 2013. Genomic Selection and Herd Management for Improved Feed Efficiency of the Dairy Industry. Presented to the International Breeding Goal Meeting: Selection for Improved Feed Efficiency. February 25-26, 2013. Wageningen, Netherlands.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2013 Citation: Spurlock, DM. 2013. Station Report: Feed Efficiency Research at Iowa State University. Presented to the S-1040 Regional Project Meeting, October 29-30, 2012. Indianapolis, IN.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2012 Citation: VandeHaar M. 2012. Considerations in feed efficiency for dairy cattle. Presented to the International Breeding Goal Meeting: Selection for Improved Feed Efficiency. Wageningen, Netherlands. May 24.


Progress 05/01/11 to 04/30/12

Outputs
OUTPUTS: As of May, 2012, we have recorded 2580 individual cow phenotypes in our databases of 110 cows at MSU, 570 at UWM, 510 at ISU, 220 at UF, 70 at VT, and 1100 at WUR. Of these, 740 are new phenotypes collected in the past year. These cows have all been genotyped or will be genotyped within the next 3 months. We also have identified an additional 300 cows phenotyped at cooperator farms in the past year, and this data is being compiled. Thus, we are well on our way toward our database goal for year 2, and by the end of year 2, we expect to add an additional 1600 cows to our database to bring the total number of phenotyped and genotyped cows to 4200. In addition, all of our genotypes will be with the 50K SNP chip, which exceeds the goals laid out in our original project. The structure of our database was defined in year 1 as per our original proposal. We are currently working with the Biomedical Research and Informatics Core at MSU to consolidate and maintain our database of cows. This will facilitate analysis of data for additional aims of the project. Under the leadership of Co-PD Veerkamp, an international group met in May, 2012, to compile a database of thousands of cows to examine the genetics and genomics of feed intake. This set the groundwork for international cooperation in identifying genomic relationships in feed efficiency with collaborators from several European countries as well as Australia and Canada. This is critical as we consider effective development of genomic breeding values for feed efficiency. A website for the project was developed to educate the public and other researchers and serve as a repository for publications and resources . A survey tool was developed, and is being sent to 400 farmers in MI, WI, IA, VA, FL, and CA. See . A draft of a decision support tool for determining benefits of nutritional grouping on farms was developed as well as tool for feed values . At least 6 presentations were made to farmers and consultants in year 1 at several US locations (including WI, AZ, CA, VA) to show the benefits of nutritional grouping and feed efficiency for sustainable agriculture. A web page outlining educational programs was developed after meeting with Wisconsin Farm Bureau. Increased emphasis on feed efficiency was given in at least 6 undergraduate courses at MSU, UWM, NCAT, and VT. Students in a study-abroad program in the Netherlands took pictures to use in developing K-12 teaching programs. Undergraduate students were mentored in research in feed efficiency, with 42 students directly involved in the work of Co-PDs and at least 10 more with cooperators. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Target audience includes other researchers at FASS meetings, farmers and farm consultants at outreach programs and through web tools, and students through curricular activities. PROJECT MODIFICATIONS: Dr. Barry Simpson of GeneSeek was added as a Co-PD for the project to facilitate and improve genotyping.

Impacts
Major outcomes and impacts were not expected for year 1 of the project, especially in research. For our research aims, we are using residual feed intake (RFI), a measure of actual versus predicted intake for an individual cow, as our indicator of feed efficiency. However, if used incorrectly, selection based on RFI could result in phenotypes that are not actually the most efficient at converting feed resources into products for human consumption. Predicted intake can be determined from nutritional models, or it can be determined statistically as the deviation from average intake of cohorts, after adjustment for differences in production, body weight (BW), and/or BW changes. A cow with negative RFI is more efficient than her cohorts because she has lower maintenance requirements, digests feed more efficiently, or uses digested feed more efficiently for maintenance, gain, or milk. Decisions about whether and how to adjust for differences in BW or BW change are critical to selection strategies focused on improving feed efficiency. Inappropriate adjustment for BW and body energy change may cause inadvertent bias toward cows that are larger, lose body condition to support milk output, or gain body condition when fed a high energy diet. Moreover, adjustment for BW change requires accurate measures of BW that are not unduly influenced by gut fill. To date, based on preliminary data with 500 cows, we found that metabolic BW was a significant contributor to variation in intake. However, it accounted for only 10% of the variation whereas milk energy output accounted for 60%. BW change accounted for even less variation in intake, but its consideration likely is essential to ensure improvement in feed efficiency does not occur at the expense of health and fertility. Our conclusion to date is that careful consideration of all factors affecting feed efficiency, including RFI, maintenance requirements, and production, will be necessary to achieve continued improvement of feed efficiency. This information will be used as we test and develop genomic breeding values to ensure that our selection methods enhance our long-term ability to feed people sustainably and are consistent with animal welfare. In addition, about ten presentations were made to farmers and farm consultants on the value of feed efficiency, and >300 undergraduate students learned more about research and feed efficiency. Thus, the outcomes from year 1 will have long-term impact to improve the efficiency with which feed resources are used to produce milk.

Publications

  • Aguilar, M. and M. D. Hanigan. 2012. Effect of simultaneous reduction of ruminally degradable protein and ruminally undegradable protein in dairy cattle. J. Animal Sci. 90(E-Suppl.1). Abstract. In press.
  • Cabrera, V.E., F. Contreras-Govea, R.D. Shaver, and L.E. Armentano. 2012. Grouping strategies for feeding lactating dairy cattle. Proc Four State Dairy Nutrition and Management Conference.
  • de Haas, Y., J. E. Pryce, M. P. L. Calus, E. Wall, M. P. Coffey, H. D. Daetwyler, B. J. Hayes, and R. F. Veerkamp. 2012. Genomic selection for dry matter intake using a combined European and Australian reference population. J. Animal Sci. 90(E-Suppl.1). Abstract 607. In press.
  • VandeHaar, M.J., L. Armentano, D. M. Spurlock, J. Patience, and J. Taylor. 2012. Feed efficiency: Basic principles and opportunities for improvement. J. Animal Sci. 90(E-Suppl.1). Abstract 316. In press.
  • VandeHaar, M.J., D.M. Spurlock, and L.E. Armentano. 2012. Searching for a more efficient cow. Proc Southwest Nutrition and Management Conference.
  • VandeHaar, M.J., D. M. Spurlock, L. Armentano, R. Tempelman, K. Weigel, and R. Veerkamp. 2012. Considerations in using residual feed intake to define feed efficiency in dairy cattle. J. Animal Sci. 90(E-Suppl.1). Abstract T44. In press.