Integrated research within Big Data, Bioinformatics & Omics strengthens dairy sciences and advances animal systems management.
Faculty and Staff
Victor E. Cabrera
Professor – Management
Professor – Genetics
Professor – Genetics
Assistant Professor – Precision Agriculture and Data Analysis
Professor – Genetics and Beef Cattle Production
Professor – Breeding and Genetics
Sebastian Arriola Apelo
Assistant Professor – Metabolism
Jennifer Van Os
Assistant Professor and Extension Specialist – Animal Welfare
Associate Professor – Meat Science
Selected Peer-Reviewed Articles
Ricci, A., M. Li, P. M. Fricke, and V. E. Cabrera. 2020. Short Communication: Economic impact among 7 reproductive programs for lactating dairy cows including a sensitivity analysis of the cost of hormonal treatments. Journal of Dairy Science 103:5654–5661. (Paper)
Njuki, E., B. E. Bravo-Ureta, and V. E. Cabrera. 2020. Climatic effects and total factor productivity: econometric evidence for Wisconsin dairy farms. European Review of Agricultural Economics (2020) pp. 1–26 doi:10.1093/erae/jbz046 (Paper)
Barrientos, J. A., H. White, R. D. Shaver, and V. E. Cabrera. 2020. Improving nutritional accuracy and economics through multiple ration-grouping strategy. Journal of Dairy Science 103:3774-3785. (Paper)
Cabrera, V. E., J. A. Barrientos, H. Delgado, and L. Fadul-Pacheco. 2020. Real-time continuous decision making using big data on dairy farms. Journal of Dairy Science 103:3856–3866. (Paper)
Chung, H., J. Li, Y. Kim, J.M.C. Van Os, S.H. Brounts, C.Y. Choi. 2020. Using implantable biosensor and wearable scanners to monitor dairy cattle heat stress in real-time. Computers in Agriculture 174:105453.
Aiken, V. C. F., Fernandes, A. F. A., Passafaro, T. L., Acedo, J. S., Dias, F. G., Dórea, J. R. R. and Rosa, G. J. M. Forecasting beef production and quality using large-scale integrated data from Brazil. Journal of Animal Science 98(4), 2020 (in press; doi:10.1093/jas/skaa089).
Fernandes, A. F. A., Turra, E. M., Alvarenga, E. R., Passafaro, T. L., Lopes, F. B., Alves, G. F. O., Singh, V. and Rosa, G. J. M. Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia. Computers and Electronics in Agriculture 170: 105274, 2020
Passafaro, T.L., Fernandes, A. F. A., Valente, B. D., Williams, N. H. and Rosa, G. J. M. Network analysis of swine movements in a multi-site pig production system in Iowa, USA. Preventive Veterinary Medicine 174: 104856, 2020.
Cominotte, A., Fernandes, A. F. A., Dorea, J. R. R., Rosa, G. J. M., Ladeira, M. M., van Cleeff, E. H. C. B., Pereira, G. L., Baldassinic, W. A. and Machado Neto, O. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livestock Science 232: 103904, 2020.
Chitakasempornkul, K., Rosa, G. J. M., Jager, A. and Bello, N. M. Investigating causal biological relationships between reproductive performance traits in high-performing gilts and sows. Journal of Agricultural, Biological, and Environmental Statistics, 2020 (in press; https://doi.org/10.1007/s13253-020-00389-0).
Pralle, R.S. and H.M. White. 2020. Symposium review: big data, big predictions: utilizing milk Fourier-transform infrared and genomics to improve hyperketonemia management. J. Dairy Sci. 103(4):3867-3873. https://doi.org/10.3168/jds.2019-17379.
Bresolin, T. and J. R. R. Dorea. 2020. Infrared Spectroscopy as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems. Frontiers in Genetics (Accepted).
Zhi Li, Xiao-Lin Wu, Wei Guo, Jun He, Hao Li, Guilherme J. M. Rosa, Daniel Gianola, Richard G. Tait Jr., Jamie Parham, John Genho, Tom Schultz, Stewart Bauck. Estimation of genomic breed composition of individual animals in composite beef cattle. Animal Genetics. 2020. 51(3): 457-460.
N Gross, F Peñagaricano, and H Khatib (2020) Integration of whole-genome DNA methylation data with RNA sequencing data to identify markers for bull fertility. Animal Genetics (in press)
H Louvandini, PS Corrêa, R Amorín, L Liu, EH Ieda, CR Jimenez, SM Tsai, CM McManus, and F Peñagaricano (2020) Gestational and lactational exposure to gossypol alters the testis transcriptome. BMC Genomics 21: 59.
Ouellet, V., V. E. Cabrera, L. Fadul-Pacheco, and Ã‰. Charbonneau. 2019. The relationship between the number of consecutive days with heat stress and production performance of Holstein dairy cows raised in a continental climate. Journal of Dairy Science 102:8537-8545. (Paper)
Kebreab, E., K. F. Reed, V. E. Cabrera, P. E. Vadas, G. Thoma, and J. M. Tricarico. 2019. A new modeling environment for integrated dairy system management. Animal Frontiers 9:25-32. (Paper)
Wu, Y., D. Liang, R. D. Shaver, and V. E. Cabrera. 2019. An income over feed cost nutritional grouping strategy. Journal of Dairy Science 102:4682-4693. (Paper)
Bellingeri, A., V. E. Cabrera, A. Gallo, D. Liang, and F. Masoero. 2019. A survey of dairy cattle management, crop planning, and forages cost of production in Northern Italy. Italian Journal of Animal Science 18-786-798. (Online) (Paper)
KrpÃ¡lkovÃ¡, L., V. E. Cabrera, L. ZavaldilovÃ¡, and M. Å tÃpkovÃ¡. 2019. Importance of hoof health in dairy production. Effect of claw disorders on milk production, fertility, and longevity, and their economic impact in Holstein cows. Czech Journal of Animal Science 64:107-117. (Paper)
Fernandes, A. F. A., Dorea, J. R. R., Fitzgerald, R., Herring, W. and Rosa, G. J. M. A novel automated system to acquire biometric and morphological measurements, and predict body weight of pigs via 3D computer vision. Journal of Animal Science 97: 496-508, 2019.
Passafaro, T.L., Van de Stroet, D., Bello, N. M., Williams, N. H. and Rosa, G. J. M. Generalized additive mixed model on the analysis of total transport losses of market-weight pigs. Journal of Animal Science 97: 2025-2034, 2019.
Aiken, V. C. F., Dórea, J. R. R., Acedo, J. S., Sousa, F. G., Dias, F. G. and Rosa, G. J. M. Record linkage for farm-level data analytics: Comparison of deterministic, stochastic and machine learning methods. Computers and Electronics in Agriculture 163: 104857, 2019.
Koltes, J. E., Cole, J. B., Clemmens, R., Dilger, R. N., Kramer, L. M., Lunney, J. K., McCue, M. E., McKay, S. D., Mateescu, R. G., Murdoch, B. M., Reuter, R., Rexroad, C.E., Rosa, G. J. M., Serão, N. V. L., White, S. N., Woodward-Greene, M. J., Worku, M., Zhang, H. and Reecy, J. M. A Vision for development and utilization of high-throughput phenotyping and big data analytics in livestock. Frontiers in Genetics 10: 1197, 2019.
Chitakasempornkul, K., Meneget, M. B., Rosa, G. J. M., Lopes, F. B., Jager, A., Gonçalves, M. A. D., Dritz, S. S., Tokach, M. D., Goodband, R. D. and Bello, N. M. Investigating causal biological relationships between reproductive performance traits in high-performing gilts and sows. Journal of Animal Science 97: 2385-2401, 2019.
N Gross, MG Strillacci, F Peñagaricano, and H Khatib (2019) Characterization and functional roles of paternal RNAs in 2–4 cell bovine embryos. Scientific Reports 9: 20347.
Jabarzareh, A., A. Sadeghi-Sefidmazgi, G. Ghorbani, and V. E. Cabrera. 2018. Economic evaluation of sexed semen use in Iranian dairy farms according to field data. Reprod Dom Anim. 2018:1â€“8. DOI: 10.1111/rda.13247. (Paper)
Mur-Novales, R., F. Lopez-Gatius, P. Fricke, V. E. Cabrera . 2018. An economic evaluation of management strategies to mitigate the negative impact of twinning in dairy herds. Journal of Dairy Science 101:8335â€“8349. (Paper)
Cabrera, V. E. 2018. Helping dairy farmers to improve economic performance utilizing data-driving decision support tools. Animal 12(1):134-144. (Paper)
Wang, X., H. Gao, K.G. Gebremedhin, B. Schmidt Bjerg, J. Van Os, C.B. Tucker, G. Zhang. 2018. A predictive model of Equivalent Temperature Index for dairy cattle (ETIC). Journal of Thermal Biology 76:165-170.
Bello, N. M., Ferreira, V. C., Gianola, D. and Rosa, G. J. M. Conceptual framework for investigating causal effects from observational data in livestock. Journal of Animal Science 96(10): 4045-4062, 2018.
Huang, X., Elston, R. C., Rosa, G. J. M., Mayer, J., Ye, Z., Kitchner, T., Brilliant, M. H., Page, D. and Hebbring, S. J. Applying family analyses to electronic health records to facilitate genetic research. Bioinformatics 34(4): 635-642, 2018.
Wang, Y., Mi, X., Rosa, G. J. M., Chen, Z., Lin, P., Wang, S. and Bao, Z. Technical note: an R package for fitting sparse neural networks with application in animal breeding. Journal of Animal Science 96: 2016-2026, 2018.
Pralle, R. S., K. W. Weigel, and M. White. 2018. Predicting blood β-hydroxybutyrate using milk Fourier transform infrared spectrum, milk composition, and producer-reported variables with multiple linear regression, partial least squares regression, and artificial neural network. J. Dairy Sci. 101:4378-4387. https://doi.org/10.3168/jds.2017-13209.
Chandler, T. L., R. S. Pralle, J. R. R. Dorea, S. E. Poock, G. R. Oetzel, R. H. Fourdraine, H. M. White. 2018. Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early lactation Holstein and Jersey cows. J. Dairy Sci. 101:2476-2491. https://doi.org/10.3168/jds.2017-14076.
Dorea, J. R. R., G. M. J. Rosa, and L. E. Armentano. 2018. Mining data from milk infrared spectroscopy to improve feed intake predictions in lactating dairy cows. Journal of Dairy Science 101:5878-5889.
Lin Z., Wei LM., Cai W., Zhu YL., Tucholski T., Mitchell SD., Guo W., Ford PF., Diffee GM and Ying G. Simultaneous Quantification of Protein Expression and Modifications by Top-down Targeted Proteomics: A Case of Sarcomeric Subproteome. Molecular and Cellular Proteomics. 2018.18(3): 594-605. PMID: 30591534.
AL Skibiel, F Peñagaricano, R Amorín, BM Ahmed, GE Dahl, and J Laporta (2018) In utero heat stress alters the offspring epigenome. Scientific Reports 8: 14609.
Bach, A., and V. E. Cabrera. 2017. Robotic milking: feeding strategies and economic returns. Journal of Dairy Science 100:7720-7728. (Paper)
Liang, D. F. Sun, M. A. Wattiaux, V. E. Cabrera, J. L. Hedtcke, and E. M. Silva. 2017. Effect of feeding strategies and cropping systems on greenhouse gas emission from Wisconsin certified organic dairy farms. Journal of Dairy Science 100:5957-5973. (Paper)
López-Gatius, F., C. Andreu-VÃ¡zquez, R. Mur-Novalesd, V. E. Cabrera, R. H. F. Hunter. 2017. The problem of twin pregnancies in dairy cattle. A review on practical prospects. Livestock Science 197:12-16. (Paper)
Selected Book Chapters
Cabrera, V. E. 2020. Data-driven decision support tools in dairy herd health. In: Improving dairy herd health. Prof. Emile Bouchard (Ed). Burleigh Dodds Science Publishing, ISBN-00: 000-000000000.
Fraisse, C. W., N. E. Breuer, and V. E. Cabrera. 2019. Developing climate-based decision support systems (DSS) from agricultural systems models. In: Advances in crop modelling for a sustainable agriculture. Boote, K. (Ed), Burleigh Dodds Series in Agricultural Science, ISBN-13: 978-1786762405. (Book)
Liang, D., and V. E. Cabrera. 2017. Dairy Farm Management Strategies to Reduce Greenhouse Gas Emissions: Mitigation Strategies and Economic Considerations in the US. in: Agricultural Research Updates. Volume 20. Nova Science Publishers. (Chapter)
Overton, M. W., and V. E. Cabrera. Accepted July 2016. Monitoring and quantifying value of change in reproductive performance. In: Large Dairy Herd Management Book. American Dairy Science Association. (Chapter)
GJM Rosa, VPS Felipe, and F Peñagaricano (2016) Applications of Graphical Models in Quantitative Genetics and Genomics. In: Systems Biology in Animal Production and Health, Vol. 1. pp 95-116. Springer International Publishing.
KrpÃ¡lkovÃ¡, L., V. E. Cabrera, J. Kvapilik, J. Burdych, M. Å tipkovÃ¡, P. Crump, L. StÃ¡dnik, and M. Vacek. 2014. Optimal growth of heifers and effect of milk yield level on dairy herd production, reproduction, and profitability. LAP LAMBERT Academic Publishing, SaarbrÃ¼cken, Deutschland, Germany. (Chapter)
Greaser, M.L. and Guo Wei. 2014. “Proteins” In “Handbook of Muscle Foods Analysis, Second Edition”, ed, Leo M.L.Nollet, Fidel Toldra, CRC Press, Boca Raton, FL, PP357-368.
Cabrera, V. E. 2012. DairyMGT: A suite of decision support systems in dairy farm management. IN Decision Support Systems. Jao C. (Ed), INTECH, Rijeka, Croatia. (Chapter)
Cabrera, V. E., P. E. Hildebrand. 2012. Chapter 7th: Linear programming for dairy herd simulation and optimization: An integrated approach for decision-making. IN Linear programming – New frontiers in theory and applications. Zoltan, A. M. (Ed.), Nova Science Publishers, Inc., Hauppauge, NY. (Chapter)
Cabrera, V. E., D. SolÃs, G. A. Baigorria, and D. Letson. 2009. 7th: Managing climate variability in agricultural analysis. IN: Long, J.A., and D. S. Wells (Eds.), Ocean circulation and El NiÃ±o: New research, p. 163-179, Nova Science Publishers, Inc., Hauppauge, NY. (Chapter)
Hoogenboom, G., C. W. Fraisse, J. W. Jones, K. T. Ingram, J. J. O’Brien, J. G. Bellow, D. Zierden, D. E. Stooksbury, J. O. Paz, A. Garcia y Garcia, L. C. Guerra, D. Letson, N. E. Breuer, V. E. Cabrera, L. U. Hatch, and C. Roncoli. 2007. Climate-based agricultural risk management tools for Florida, Georgia and Alabama, USA. In: Sivakumar, M. V. K. and J. Hansen (Eds.), Climate Prediction and Agriculture: Advances and Challenges, p. 273-278, Springer, Berlin.
Langeveld, J.W.A., Crawford, A., Paine, M., Pinheiro, S., de Boef, W., Kristensen, I.S., Hermansen, J., Dedieu, B., Hildebrand, P., Cabrera, V.E., Jansen, D., and Dixon, J. 2006. Project setup and learning processes in participative systems oriented research initiatives. In: H. Langeveld, N. Roling (Eds.), Changing European farming systems for a better future. New visions for rural areas. p. 89-91, Wageningen Academic Publishers, Wageningen.
Selected Conference Proceedings
Li, M, V. E. Cabrera, and K. Reed. 2019. Updating Holstein and Jersey lactation curve parameters for the Rumination Farm System Model (RuFaS). Journal of Dairy Science 102: (Suppl. 1): M128.
Li, W., and V. E. Cabrera. 2019. Interactions among pregnancy rate, turnover ratio, and herd structure. Journal of Dairy Science 102: (Suppl. 1): M131.
Delgado, H., L. Fadul-Pacheco, and V. E. Cabrera. 2019. The use of integrated data to identify first-lactation cows at high risk of clinical mastitis. Journal of Dairy Science 102: (Suppl. 1): M134.
Fadul-Pacheco, L., H. Delgado, and V. E. Cabrera. 2019. Machine learning algorithms for early prediction of clinical mastitis. Journal of Dairy Science 102: (Suppl. 1): 94.
Li, M., V. E. Cabrera, and K. Reed. 2019. A stochastic animal life-cycle simulation model and its herd structure. Journal of Dairy Science 102: (Suppl. 1): 96.
Barrientos-Blanco, J., V. E. Cabrera, and R. D. Shaver. 2019. Executing a better nutritional grouping strategy in commercial dairy farms. Journal of Dairy Science 102: (Suppl. 1): 98.
Bellingeri, A., A. Gallo, D. Liang, F. Masoero, and V. E. Cabrera. 2019. Development of a decision support tool for optimal allocation of nutritional resources in a dairy herd. Journal of Dairy Science 102: (Suppl. 1): 100.
Li, W., and V. E. Cabrera. 2019. Economics of using beef semen. Journal of Dairy Science 102: (Suppl. 1): 102.
Mur-Novales, R., P. M. Fricke, V. E. Cabrera, J. O. Giordano, M. C. Wiltbank, and J. P. N. Martins. 2019. Effects of parity, season and region on fertility of lactating dairy cows submitted to a Double-Ovsynch protocol for first timed-AI. Journal of Dairy Science 102: (Suppl. 1): W110.
Ricci, A., M. Li, P. M. Fricke, and V. E. Cabrera. 2019. The reproductive and economic impact among 6 reproductive programs for lactating dairy cows including a sensitivity analysis of the cost of hormonal treatments. Journal of Dairy Science 102: (Suppl. 1): W115.
Skevas, T., and V. E. Cabrera. 2019. Spatial dependence and dynamic productivity growth in Wisconsin dairy farming. doi =10.22004/ag.econ.291178. Research in Agricultural Economics. (Paper)
Njuki, E., B. Bravo-Ureta, and V. E. Cabrera. 2019. Productivity, weather and climate: Evidence for a sample of Wisconsin dairy farms from a GTRE model. AsociaciÃ³n Española de Economía Agraria, XII Congreso de Economía Agraria, Lugo, Galicia, September 5, 2019.
Heather White. Use of Big Data to Monitor Herd Health. Invited talk. Production, Management, and the Environment: Advancing Artificial Intelligence on Dairy Farms Symposium. American Dairy Science Association Meetings, Cincinnati, OH. June 2019
Heather White. Big data, big decisions: Utilizing multiple data sources to improve sub-clinical ketosis management. Invited Keynote Speaker. Australian Association of Ruminant Nutritionist Annual Meeting. Attwood, Victoria, Australia. October 2019
Mingming Sun, Yutong Jin, Chaoqun Zhu, Maimaiti Rexiati, Hanfang Cai, Martin Liss, Michael Gotthardt, Ying Ge and Wei Guo. Phosphorylation of RNA binding motif 20 is a novel target to reduce myocardial stiffness in diastolic dysfunction. 2019 Basic Cardiovascular Sciences (BCVS) meeting, Boston, MA, July 29th –August 1nd 2019.
Liang, D., H. Delgado, and V. E. Cabrera. 2018. A virtual dairy farm brain. 13th European International Farming System Association Symposium of the Farming and Rural Systems: Farming systems: facing uncertainties and enhancing opportunities. Chania, Crete, Greece, 01-05 July 2018. (Paper)
Ouellet, V., V. E. Cabrera, L. Fadul-Pacheco, P. Greiner, and E. Charbonneau. 2018. Relationship between the accumulative effects of heat stress and Holstein dairy cowsâ€™ milk performances in eastern Canada. Journal of Dairy Science 101: (Suppl. 2): 94. (Abstract)
Barrientos, J. A., V. E. Cabrera, and R. D. Shaver. 2018. Improving nutritional accuracy through multiple ration-grouping strategy. Journal of Dairy Science 101: (Suppl. 2): 100. (Abstract)
Wei Guo, Chaoqun Zhu, Vikram Chhatre and Qiurong Wang. Diverse splicing mode of a giant gene TTN and its splicing regulation. The 2nd –international Caparica Conference in Splicing, Caparica, Portugal, July 16th-19th 2018.
Selected Popular Press Articles
Help us help you make better use of dairy data. Hoard’s Dairyman. February 10 2020 (Article)
Farming out data-driven decisions. Hoard’s Dairyman. March 25 2020 (Article)
Data: Think big, but start small. Hoard’s Dairyman. April 10 2020 (Article)
Big Data, Big Opportunities. Progressive Dairy. July 29 2019 (Article)
Cabrera, V. E. Information overload calls for a Virtual Dairy Brain. PDPW Dairy’s Bottom Line. June 2018 (Article)
Cabrera, V. E. Pick a straw: Conventional, sexed, or beef semen? Progressive Dairyman 19 April 2018. (Article)
Akins, M. S. Strategically manage heifer inventory. Professional Dairy Producers of Wisconsin – Dairy’s Bottom Line. November 2018
Akins, M.S. and M. A. Hagedorn. Putting a price tag on raising replacements. Hoard’s Dairyman. April 2016
Contreras-Govea, F. E.V. E. Cabrera, R. D. Shaver, D. K. Beede, L. E. Armentano and M. J. VandeHaar. Pp. 92. Hoard’s Dairyman. 10 February 2015. (Article)
Contreras-Govea, F. E.V. E. Cabrera and R. D. Shaver. Pp. 787. Hoard’s Dairyman. December 2015. (Article)
Contreras-Govea, F. E.V. E. Cabrera and R. D. Shaver. Pp. 607. Hoards™ Dairyman. 25 September 2015. (Article)
Contreras-Govea, F. E., A. S. Kalantari, V. E. Cabrera, R. D. Shaver and L. E. Armentano. Pp. 390. Feeding. 25 May 2015. (Article)
Hardie, C. A., V. E. Cabrera, M. Dutreuil, and R. Gildersleeve. 2012. Pp. 20. Midwest Forage Association Forage Focus. December 2012. (Article)
Cabrera, V. E. 2012. Pp. 646. Hoards Dairyman. 10 October 2012. (Article)
Gould, B. W., and V. E. Cabrera. 2011. Cheese Reporter. 16 December 2011.
Gould, B. W., and V. E. Cabrera. 2011. New York State Department of Agriculture and Markets.
Selected Research Posters
Waldon, N. L., C. Seely, S. Erb, R. Pralle, M. Martin, and H. M. White. Use of blood metabolites peripartum to predict postpartum liver triglyceride content in dairy cattle. Professional Agricultural Workers Conference. Tuskegee University. p. 24. 2019
Pralle, R.S., C. S. Seely, H. T. Holdorf, J. Woolf, and H. M. White. Clustering based on liver and blood metabolite concentrations suggests cows are susceptible or resistant to early postpartum metabolic disorders. Advances in Animal Biosciences. 10(3):493.
Pralle, R.S., K. W. Weigel, N. E. Schultz, H. M. White. Hyperketonemia genome-wide association study in Holstein cows. Annual Meeting of the European Federation of Animal Science. 70(25):538. 2019
Pralle, R.S., K. W. Weigel, N. E. Schultz, and H. M. White. Hyperketonemia SNP by parity group genome-wide interaction study in Holstein cows. Annual Meeting of the European Federation of Animal Science. 70(25):541. 2019
Selected Other Publications
Cabrera, V. E., J. Barrientos, L. Fadul, and H. Delgado. 2019. Real-time continuous decision-making using big data. Journal of Dairy Science 102: (Suppl. 1): 322.
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. (Paper)
Mur-Novales, R. M., and V. E. Cabrera. 2017. What type of semen should I use? Proceedings Dairy Cattle Reproduction Council Annual Convention. Reno, NV 7-9 November 2017. (Paper)
Bach, A. V. E. Cabrera 2016. Robotic milking: feeding strategies and economic returns. Journal of Dairy Science 99 (Suppl. 1): 35
Cabrera, V. E. 2014. Economics of fertility in high-yielding dairy cows on confined TMR systems. In Proceedings. International Cow Fertility Conference, New Science New Practices. Westport, Mayo, Ireland. 18-21 May 2014. (Paper) (Presentation)
Cabrera, V. E. 2013. Grouping strategies to improve feed efficiency. 26th American Dairy Science Association Discover Conference: Dairy Feed Efficiency. Naperville, IL. 23-26 September 2013. (Abstract) (Presentation)
Cabrera, V. E. 2011. The need for applied research and decision support tools in dairy farm management and decision-making. 2011 American Dairy Science Association Foundation Lecture. New Orleans, LO. 12 July 2011. (Paper) (Presentation)
Cabrera, V. E. 2011. Economic comparison of reproductive management programs. 21st American Dairy Science Association Discover Conference: Improving Reproductive Efficiency of Lactating Dairy Cows. Itasca, IL. 11 May 2011. (Abstract) (Presentation)
Cabrera, V. E. 2011. The economic value of changes in 21-day pregnancy rate and what controls this value. 21st American Dairy Science Association Discover Conference: Improving Reproductive Efficiency of Lactating Dairy Cows. Itasca, IL. 10 May 2011. (Abstract) (Presentation)
Cabrera, V. E. 2011. Exploring methods to assess the economic value of dairy cattle reproductive programs. Midwest American Dairy Science Association Meeting. Des Moines, IA. 15 March 2011. (Abstract) (Presentation)
Cabrera, V. E. 2009. A large Markovian linear program model for dairy herd decision-making. American Dairy Science Association Annual Meeting. Montreal, Canada. 15 July 2009. (Abstract) (Presentation)