ENHANCING THE COMPETITIVENESS AND VALUE OF U.S. BEEF

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: TERMINATED
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 0213643
• Project No.: CA-D-ASC-7776-RR
• Multistate No.: W-3177
• Project Start Date: Oct 1, 2012
• Project End Date: Sep 30, 2017

Project Director
Oltjen, JA, W.

Recipient Organization
UNIVERSITY OF CALIFORNIA, DAVIS
410 MRAK HALL
DAVIS,CA 95616-8671

Performing Department
Animal Science

Non Technical Summary
The U.S. beef industry faces complex challenges that can be addressed through a multi-disciplinary, integrated approach involving participants from animal science, meat science, and economics. Increasing exports, decreased cattle numbers and beef supply, variable (and currently favorable) foreign exchange rates, larger carcasses yet a need for portion control, and growing interest by the public in how beef is produced present both challenges and opportunities. Innovative animal and meat science research can identify the types and qualities of beef that a diverse and international consuming public desire. Economic research can determine the relative strength of consumer preferences across types and qualities of beef products and estimate the market value consumers place on identified product attributes. Integrating research efforts will allow the research team to identify product quality attributes consumers demand and estimate what the market is willing to pay for these attributes in a manner that better captures the growing complexities faced by the U.S. beef industry. Both product price and product quality matter to the consumer. Production and process innovations lower production costs and/or improve product quality, which in turn will enhance beef's competitive position relative to pork and poultry. To better understand the relationship in the beef industry between price and product quality, animal/meat scientists and economists need to work together to explore issues affecting beef demand. Analysis of the interaction between consumer preferences for beef based on product attributes, such as: a) consumption quality of beef products, b) quality-enhancing innovations, and c) food safety, with d) market price is key to improving beef's competitive position in the battle to capture more of the consumer's dollar. This type of research is needed if the beef industry is to recapture lost domestic market share from pork and poultry, and extend U.S. beef's international market share. Product quality and safety are a function of the U.S. beef production and marketing systems. Therefore, consumer demand is also a function of these systems. Failure of these systems in the past to satisfy consumer preference has resulted in the beef industry losing market share to poultry and pork. Product quality is an issue because much of U.S. beef has been marketed and processed as a generic product, but variation in quality reduces the competitiveness of beef. Beef cattle are genetically diverse, produced under a variety of environmental conditions, which leads to differences in meat quality. The industry might improve customer satisfaction and industry competitiveness by targeting the natural variation of beef to niche markets that are willing to pay a premium for specific naturally occurring product attributes. The multi-disciplinary research team has decided to focus on beef value at all levels from production through the supply chain to consumer demand. Animal care and health, production and processing, information transfer and marketing, and factors influencing domestic and international demand all affect beef value and thus its competitiveness.

Animal Health Component

(N/A)

Research Effort Categories

Basic

(N/A)

Applied

(N/A)

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
315	3410	1050	100%

Knowledge Area
315 - Animal Welfare/Well-Being and Protection;

Subject Of Investigation
3410 - Dairy cattle, live animal;

Field Of Science
1050 - Developmental biology;

Keywords

beef

competition

efficiency of production

Goals / Objectives
The multi-disciplinary research team has decided to focus on beef value at all levels from production through the supply chain to consumer demand. Animal care and health, production and processing, information transfer and marketing, and factors influencing domestic and international demand all affect beef value and thus its competitiveness. Our objectives are 1) Measure and improve beef quality, safety and value by assessing impacts of animal health, animal care, and processing management/production strategies; and 2) Improve supply chain management, information transfer and value determination by examining strategies of information collection and dissemination. Our outputs are to provide suggestions for aligning production of beef with consumer preferences, to identify impediments to transmission of information between producers and consumers along with suggested resolution approach alternatives, to identify implications of issues around animal health for individual producer and overall U.S. beef industry competitiveness, to have direct interaction with industry and government groups in at least two of the five annual meetings, and to publish academic papers (peer-reviewed articles, fact sheets, Experiment Station reports, etc.) on issues directly stemming from this project.

Project Methods
Production and processing techniques must continue to evolve to meet the changing demands of beef consumers. Improved healthfulness of products has played greater role in purchasing decisions in recent years and fresh and processed beef products should be developed to meet this demand. While some production practices measurably impact beef physically, others only alter perceived benefits to consumers. Some of these perceptions can be driven by misconceptions of current practices and understanding the gaps in practice/perception is important for beef producers to understand. An increasing portion of beef consumers are demanding alternative production techniques including housing, diet and additives, and uses of vaccines and antibiotics during beef production and limitations on added ingredients during processing. While beef produced in these alternative practices can garner a premium price, increased production costs and changes in product quality and safety can occur and need to be assessed. Research will continue to explore development, consumer acceptance, and overall viability of these alternative practices. Research investigating producer incentives for participation in value-added propositions (e.g., appropriate use of local market needs) will be conducted. The value of animal identification and traceability for the different sectors in the beef industry that affiliate with different alliances will be examined. Additionally, this analysis of animal identification and traceability will include livestock operations of different size (scale), types and types of certification. Issues related to animal health have enormous implications for the U.S. beef industry's competitiveness both domestically and internationally. An important transfer mechanism that will be addressed is the role and value of 3rd party verification (e.g., export verification programs, age and source verification, etc.).

Progress 10/01/16 to 09/30/17

Outputs
Target Audience:Beef producers, their support organizations, and state and federal government. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Developing collaboartions and two journal articles. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Beef production can be improved with more accurate predictions of animal growth and carcass composition with the analysis of modern cattle presented at the International Modelling conference in Cairns.

Publications

• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Carabus, A., R.D. Sainz, J.W. Oltjen, M. Gispert, M. Font-i-Furnols. 2017. Growth of total fat and lean and of primal cuts is affected by the sex type. Animal Feb 10:1-9. doi: 10.1017/S1751731117000039.

Progress 10/01/12 to 09/30/17

Outputs
Target Audience:Beef producers, their support organizations, and state and federal government. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Developing collaboartions and two journal articles. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Beef production can be improved with more accurate predictions of animal growth and carcass composition with the analysis of modern cattle presented at the International Modelling conference in Cairns.

Publications

• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Carabus, A., R.D. Sainz, J.W. Oltjen, M. Gispert, M. Font-i-Furnols. 2017. Growth of total fat and lean and of primal cuts is affected by the sex type. Animal Feb 10:1-9. doi: 10.1017/S1751731117000039.

Progress 10/01/15 to 09/30/16

Outputs
Target Audience:Beef producers, their support organizations, and state and federal government. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Developing collaboartions and one journal article. What do you plan to do during the next reporting period to accomplish the goals?Further analysis of additional data in a wider range of environments will provide more robust estimates to be used in later models.

Impacts
What was accomplished under these goals? Beef production can be improved with more accurate predictions of animal growth and carcass composition with the analysis of modern cattle presented at the International Modelling conference in Cairns.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Oltjen, J.W., L.C. Forero and J.W. Stackhouse. 2015. Beeftracker mobile appfor tracking and analysis of beef herd pasture use and location. Proc. 6th Nat. Conf. on Grazing Lands. December 13-15, Dallas, Texas.
• Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Oltjen, J.W., J.W. Stackhouse, L.C. Forero and K. Stackhouse-Lawson. 2015. Beeftracker: Spatial tracking and geodatabase for beef herd sustainability and lifecycle analysis. American Geophysical Union Fall Meeting. December 14, San Francisco, California.
• Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Werth, S.J., J.W. Oltjen, E. Kebreab and F.M. Mitloehner. 2016. A life cycle assessment of a beef feedlot finishing ration supply chain in California. Journal of Animal Science 94(E-Suppl. 5):568.
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Davy, J., L. Forero, T. Tucker, C. Mayo, D. Drake, J. Maas and J. Oltjen. 2016. Efficacy of selenium supplementation methods in California yearling beef cattle and resulting effect on weight gain. California Agriculture 70:188-194.

Progress 10/01/14 to 09/30/15

Outputs
Target Audience:Beef producers, their support organizations, and state and federal government. ? Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Developing collaborations and one journal article. What do you plan to do during the next reporting period to accomplish the goals?Further analysis of additional data in a wider range of environments will provide more robust estimates to be used in later models.

Impacts
What was accomplished under these goals? Beef production can be improved with more accurate predictions of animal growth and carcass composition with the analysis of modern cattle presented at the International Modelling conference in Cairns.

Publications

• Type: Journal Articles Status: Published Year Published: 2015 Citation: Carabus, A., R.D. Sainz, J.W. Oltjen, M. Gispert, M. Font-i-Furnols. 2015. Predicting fat, lean and the weights of primal cuts for growing pigs of different genotypes and sexes using computed tomography. J. Anim. Sci. 93:1388-1397.

Progress 10/01/13 to 09/30/14

Outputs
Target Audience: Beef producers, their support organizations, and state and federal government. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest? Thus far only to scientists for their feedback. What do you plan to do during the next reporting period to accomplish the goals? Further analysis of additional data in a wider range of environments will provide more robust estimates to be used in later models.

Impacts
What was accomplished under these goals? Beef production can be improved with more accurate predictions of animal growth and carcass composition with the analysis of modern cattle presented at the International Modelling conference in Cairns.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Oltjen, J.W., R.D. Sainz, L.B. Barioni, D.P. Lanna and T.Z. Albertini. 2014. Evolution of parameter changes for beef cattle growth in the Davis Growth Model over 40 years. In: Modelling Nutrient Digestion and Utilization in Farm Animals (K.J. Harper, D.M. McNeill and A.W. Bell, Eds.) pp.75. September 15-17, 2014, Cairns, Australia.

Progress 01/01/13 to 09/30/13

Outputs
Target Audience: Beef producers, their support organizations, and state and federal government. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Beef production efficiency is improved and competitiveness enhanced when animals are fed optimally. TAURUS, our beef rationing and performance prediction software has been developed and submitted and accepted for publication.

Publications

• Type: Journal Articles Status: Published Year Published: 2013 Citation: Oltjen, J.W. and A. Ahmadi. 2013. Taurus: a ration formulation program for beef cattle. Nat. Sci. Educ. 42:1-15. Doi:10.4195/nse.2011.00003

Progress 01/01/12 to 12/31/12

Outputs
OUTPUTS: Beef production is a recognized source of greenhouse gas (GHG) and ammonia (NH3) emissions; however, little information exists on the net emissions from beef production systems. A partial life cycle assessment (LCA) was conducted using a whole farm model to estimate GHG and NH3 emissions from representative beef production systems in California. The model simulates crop growth, feed production and use, animal growth, and the return of manure nutrients back to the land to predict the environmental impacts and economics of production systems. Ammonia emissions are determined by summing the emissions from animal housing facilities, manure storage, field applied manure, and direct deposits of manure on pasture and rangeland. All important sources and sinks of methane, nitrous oxide, and carbon dioxide are predicted from primary and secondary emission sources. Primary sources include enteric fermentation, manure, cropland used in feed production, and fuel combustion. Secondary emissions occur during the production of resources used on the farm, which include fuel, electricity, machinery, fertilizer, and purchased animals. The carbon footprint is the net exchange of all GHG in carbon dioxide equivalent (CO2e) units per kg of HCW produced. Simulated beef production systems included cow-calf, stocker, and feedlot phases for the traditional British beef breeds and calf ranch and feedlot phases for Holstein steers. We also hypothesized that increased animal performance is one of the most effective means to decrease greenhouse gas (GHG) and ammonia (NH3) emissions from livestock production per unit of product produced. Little information exists, however, on the effects of increased animal productivity on the net decrease in emission from beef production systems. We used the model to compare 1) Angus-natural, with no use of growth-enhancing technologies, 2) Angusimplant, with ionophore and growth-promoting implant (e.g., estrogen/trenbolone acetate-based) application, 3) Angus-B 2-adrenergic agonists (BAA; e.g., zilpaterol), with ionophore, growth-promoting implant, and BAA application, 4) Holstein-implant, with growth implant and ionophore application, and 5) Holstein-BAA, with ionophore, growth implant, and BAA use. PARTICIPANTS: L.J. Butler, Extension Specialist, Agricultural and Resource Economics, University of California, Davis is a co-PI on the project to determine costs and benefits associated with animal identification. R.D. Sainz, Professor, Animal Science, University of California, Davis is a collaborator on beef growth and composition work. F.M. Mitloehner, Professor, Animal Science, University of California, Davis is a collaborator on beef emission and simulations. TARGET AUDIENCES: Beef producers, their support organizations, and state and federal government. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
An evaluation of differing production management strategies of beef production in California resulted in ammonia emissions ranging from 98 to 141 g/kg HCW and carbon footprints of 10.7 to 22.6 kg CO2e/kg HCW. Within the British beef production cycle, the cow-calf phase was responsible for 69 to 72% of total GHG emissions with 17 to 27% from feedlot sources. Holstein steers that entered the beef production system as a by-product of dairy production had the lowest carbon footprint because the emissions associated with their mothers were primarily attributed to milk rather than meat production. For the Holstein system, the feedlot phase was responsible for 91% of the total GHG emission, while the calf-ranch phase was responsible for 7% with the remaining 2% from transportation. This simulation study provides baseline emissions data for California beef production systems and indicates where mitigation strategies can be most effective in reducing emissions. During the feedlot phase, use of BAA decreased NH3 emission by 4 to 9 g/kg HCW, resulting in a 7% decrease in NH3 loss from the full production system. Combined use of ionophore, growth implant, and BAA treatments decreased NH3 emission from the full production system by 14 g/ kg HCW, or 13%. The C footprint of beef was decreased by 2.2 kg carbon dioxide equivalent (CO2e)/kg HCW using all the growth-promoting technologies, and the Holstein beef footprint was decreased by 0.5 kg CO2e/ kg HCW using BAA. Over the full production systems, these decreases were relatively small at 9% and 5% for Angus and Holstein beef, respectively. The growth-promoting technologies we evaluated are a cost-effective way to mitigate GHG and NH3 emissions, but naturally managed cattle can bring a similar net return to Angus cattle treated with growth-promoting technologies when sold at an 8% greater premium price.

Publications

• Stackhouse-Lawson, K.R., C.A. Rotz, J.W. Oltjen and F.M. Mitloehner. 2012. Carbon footprint and ammonia emissions of California beef production systems. J. Anim. Sci. 90:4641-4655.
• Stackhouse, K.R., C.A. Rotz, J.W. Oltjen and F.M. Mitloehner. 2012. Growth-promoting technologies decrease the carbon footprint, ammonia emissions, and costs of California beef production systems. J. Anim. Sci. 90:4656-4665.

Progress 01/01/11 to 12/31/11

Outputs
OUTPUTS: Results from our study of producers' costs and benefits associated with participating in animal identification programs showed that benefits of ID for management are ill defined. We developed a model of the cow-calf production system to address this deficiency, and have results showing the interaction of management decisions and use of individual records associated with animal identification. We have also initiated work that will show the impact of beef production systems on beef quality. In particular, we have linked a ruminant digestion system with a sheep composition model to serve as a model for future beef work. Also, economic models of proper length of feedlot feeding have been reported. PARTICIPANTS: L.J. Butler, Extension Specialist, Agricultural and Resource Economics, University of California, Davis is a co-PI on the project to determine costs and benefits associated with animal identification. R.D. Sainz, Professor, Animal Science, University of California, Davis is a collaborator on beef growth and composition work. TARGET AUDIENCES: Beef producers, their support organizations, and state and federal government. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Based on publications and extension work using the outputs above, beef producers should improve their understanding of how animal identification may improve herd management and be encouraged to implement appropriate participation in animal identification programs. Results of our work to model the cow-calf production system show some management strategy by animal efficiency interactions. For example, selecting replacements on phenotypic weaning weight improves subsequent system efficiency over selection on genetic breeding value for weaning weight alone. Also, producers will gain greater control over beef quality and improve profitability once our advances with the sheep model is extended to beef, showing the effects of level of production on digestibility of diets and subsequent effects on carcass characteristics and profitability.

Publications

• Oltjen, J., F. Bradley, R. Ingram, H. George, B. Reed, C. Collar, D. Giraud, J. Harper, E. Mussen, J. Davy and D. Meyer. 2011. Raising animals. In: Small Farm Handbook, 2nd Ed. (L. Tourte and B. Faber, Eds.) pp. 145-161. University of California, Agriculture and Natural Resources, Oakland, CA. Publication 3526.
• Oltjen, J.W. 2011. Beef cattle models for optimum feedlot harvest endpoint. First Joint Meeting AAPA-ASAS. Mar del Plata, Argentina, October 4-7, Revista Argentina de Produccion Animal 31(Suppl. 1):268.

Progress 01/01/10 to 12/31/10

Outputs
OUTPUTS: Results from our study of producers' costs and benefits associated with participating in animal identification programs showed that benefits of ID for management are ill defined. We developed a model of the cow-calf production system to address this deficiency, and have results showing the interaction of management decisions and use of individual records associated with animal identification. We have also initiated work that will show the impact of beef production systems on beef quality. In particular, we have linked a ruminant digestion system with a sheep composition model to serve as a model for future beef work. PARTICIPANTS: L.J. Butler, Extension Specialist, Agricultural and Resource Economics, University of California, Davis is a co-PI on the project to determine costs and benefits associated with animal identification. R.D. Sainz, Professor, Animal Science, University of California, Davis is a collaborator on beef growth and composition work. TARGET AUDIENCES: Beef producers, their support organizations, and state and federal government. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Based on publications and extension work using the outputs above, beef producers should improve their understanding of how animal identification may improve herd management and be encouraged to implement appropriate participation in animal identification programs. Results of our work to model the cow-calf production system show some management strategy by animal efficiency interactions. For example, selecting replacements on phenotypic weaning weight improves subsequent system efficiency over selection on genetic breeding value for weaning weight alone. Also, producers will gain greater control over beef quality and improve profitability once our advances with the sheep model is extended to beef, showing the effects of level of production on digestibility of diets and subsequent effects on carcass characteristics and profitability.

Publications

• Cannas, A., A.S. Atzori, I.A.M.A. Teixeira, R.D. Sainz and J.W. Oltjen. 2010. The energetic cost of maintenance in ruminants: from classical to new concepts and prediction systems. In: Energy and Protein Metabolism and Nutrition (G.M. Crovetto, Ed.) pp. 531-542. European Assoc. for Anim. Prod. Publ. No. 127.
• Oltjen, J.W., A. Cannas, A., A.S. Atzori, L.O. Tedeschi, R.D. Sainz and D.G. Fox. 2010. Integration of the Small Ruminant Nutrition System and of the UC Davis sheep growth model for improved predictions. In: Energy and Protein Metabolism and Nutrition (G.M. Crovetto, Ed.) pp. 553-554. European Assoc. for Anim. Prod. Publ. No. 127.

Progress 01/01/09 to 12/31/09

Outputs
OUTPUTS: Results from our study of producers costs and benefits associated with participating in animal identification programs showed that benefits of ID for management are ill defined. We developed a model of the cow-calf production system to address this deficiency, and have preliminary results showing the interaction of management decisions and use of individual records associated with animal identification. We have also initiated work that will show the impact of beef production systems on beef quality. In particular, we are linking a ruminant digestion system with our beef and sheep composition models. PARTICIPANTS: L.J. Butler, Extension Specialist, Agricultural and Resource Economics, University of California, Davis is a co-PI on the project to determine costs and benefits associated with animal identification. R.D. Sainz, Professor, Animal Science, University of California, Davis is a collaborator on beef growth and composition work. TARGET AUDIENCES: Beef producers, their support organizations, and state and federal government. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Based on publications and extension work using the outputs above, beef producers should improve their understanding of how animal identification may improve herd management. and be encouraged to implement appropriate participation in animal identification programs. Also, producers will gain greater control over beef quality and improve profitability due to our academic papers on the affect of cattle health, management practices, and carcass characteristics on producer profitability.

Publications

• Butler, L.J., Oltjen, J.W., Velez, V.J., Evans, J.L., Haque, F., Bennett, L.H., Caja, G. 2009. Cost-benefit analysis of the U.S. National Animal Identification System in California. Book of Abstracts No. 15, 60th Annual Meeting of the European Association for Animal Production, p.488.
• Gaspar, P., Oltjen, J.W., Drake, D.J., Ahmadi, A.B., Romera, A.J., Woodward, S.J.R., Bennett, L.N, Haque, F. and Butler, L. 2009. Management simulation tool for evaluating individual identification of beef cattle Book of Abstracts No. 15, 60th Annual Meeting of the European Association for Animal Production, p. 326.
• Oltjen, J. W., Ahmadi, A., Romera, A.J. and Drake, D.J. 2009. Interfacing CCFARM Simulation Engine with Microsoft Excel's VBA Engine to Generate On-Demand Outputs. Proceedings of the 7th World Congress of Computers in Agriculture and Natural Resources (WCCA2009), June 22-24, 2009, Reno, Nevada, USA.
• Oltjen, J.W., A. Ahmadi, A.J. Romera, D.J. Drake, P. Gaspar and S.J.R. Woodward. 2009. PCRANCH: Cow-Calf Herd Simulation System. 7th International Workship Modelling Nutrient Digestion and Utilization in Farm Animals, Paris, September 10-12. p. 64.

Progress 01/01/08 to 12/31/08

Outputs
OUTPUTS: We have compared producers' costs and benefits associated with participating in animal identification programs such as the voluntary NAIS or market-driven programs. The analysis used conventional or electronic ID technologies for livestock operations of different sizes (scale), types, and types of certifications. For example, this information could be used to improve genetics or to determine the appropriate certification programs in which to market or the foreign markets to target. This has resulted in a regional analysis of costs and benefits associated with animal ID programs We have also conducted animal performance research on the impact of beef genetics and production systems on beef quality. In particular, we have published analytical results of production and economic relationships between genetics, management, and beef quality and recommendations to producers and packers. PARTICIPANTS: L.J. Butler, Extension Specialist, Agricultural and Resource Economics, University of California, Davis is a co-PI on the project to determine costs and benefits associated with animal identification. R.D. Sainz, Professor, Animal Science, University of California, Davis is a collaborator on beef growth and composition work. TARGET AUDIENCES: Beef producers, their support organizations, and state and federal government. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Based on publications and extension work using the outputs above, beef producers should improve their understanding of animal ID issues and be encouraged to implement appropriate participation in animal identification programs. Also, producers will gain greater control over beef quality and improve profitability due to our academic papers on the affect of cattle health, management practices, and carcass characteristics on producer profitability.

Publications

• McPhee, M. J., J. W. Oltjen, J. G. Fadel, D. Perry, and R. D. Sainz. 2008. Development and evaluation of empirical equations to interconvert between twelfth-rib fat and kidney, pelvic, and heart fat respective fat weights and to predict initial conditions of fat deposition models for beef cattle. J. Anim Sci. 86: 1984-1995.
• Oltjen, J.W., D.J. Drake, A.B. Ahmadi, A.J. Romera, S.J.R. Woodward, L.N. Bennett, F. Haque and L.J. Butler. 2008. Management simulation tool for estimating value of individual identification of beef cattle. In: Proceedings of Western Sec. American Society of Animal Science 59:140-141.
• Garcia, F., R.D. Sainz, J. Agabriel, L.G. Barioni and J.W. Oltjen. 2008. Comparative analysis of two dynamic mechanistic models of beef cattle growth. Animal Feed Science and Technology 143:220-241.
• Oltjen, J.W., A. Ahmadi, A.J. Romera, D.J. Drake and S.J.R.Woodward. 2008. PRANCH: Cow-calf herd simulation system. In: Agricultural Information and Information Technology Proceedings of IAALD AFITA WCCA (T. Nagatsuka and S. Ninomiya, Eds.) pp. 123-126.
• McPhee, M.J., Oltjen, J.W., Fadel, J.G., Mayer, D.G., Sainz, R.D. (2008). Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme. Mathematics and Computers in Simulation. doi: 10.1016/j.matcom.2008.08.011 Oltjen, J.W., D.J. Drake, A.B. Ahmadi, A.J. Romera, S.J.R. Woodward, L.N. Bennett, F. Haque and L.J. Butler. 2008. Management simulation tool for estimating value of individual identification of beef cattle. J. Anim. Sci. 86(E-Suppl. 3):139.
• Oddy, V. H., R.C. Dobos, M. J. McPhee, W. McKiernan, J. W. Oltjen and R. D. Sainz (2008). A new tool to predict beef cattle fatness in the field. Canadian Journal of Animal Science, 88[4], 735.