Integrated research within Big Data, Bioinformatics & Omics strengthens dairy sciences and advances animal systems management.
Faculty and Staff
Victor E. Cabrera
Professor – Management
Guilherme Rosa
Professor – Genetics
Hasan Khatib
Professor – Genetics
Joao Dorea
Assistant Professor – Precision Agriculture and Data Analysis
Brian Kirkpatrick
Professor – Genetics and Beef Cattle Production
Kent Weigel
Professor – Breeding and Genetics
Sebastian Arriola Apelo
Assistant Professor – Metabolism
Jennifer Van Os
Assistant Professor and Extension Specialist – Animal Welfare
Jeff Sindelar
Associate Professor – Meat Science
Steven Ricke
Professor and Director- Meat Science & Animal Biologics Discovery Program
Selected Peer-Reviewed Articles
2021
Cabrera, V. E., L. Fadul-Pacheco. (Accepted 27 March 2021). Future of dairy farming from the Dairy Brain perspective: Data integration, analytics, and applications. International Dairy Journal 00:00-00. https://doi.org/10.1016/j.idairyj.2021.105069.
Cabrera, V. E., and P. M. Fricke. 2021. Economics of twin pregnancies in dairy cattle. Animals 11(2):552. https://doi.org/10.3390/ani11020552.
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.
Fadul-Pacheco, H. Delgado, and V. E. Cabrera. 2021. Exploring machine learning algorithms for early prediction of clinical mastitis. International Dairy Journal 119: 105051. https://doi.org/10.1016/j.idairyj.2021.105051.
Fadul-Pacheco, L., M. Liou, D. J. Reinemann, and V. E. Cabrera. 2021. A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments. Animals 11(5): 1229. https://doi.org/10.3390/ani11051229.
Hansen, T. L., M. Li, J. Li, C. J. Vankerhove, M. A. Sotirova, J. M. Tricarico, V. E. Cabrera, E. Kebreab, K. F. Reed. 2021. The Ruminant Farm Systems Animal Module: A Biophysical Description of Animal Management and Industry Applications. Animals 11(5): 1373. https://doi.org/10.3390/ani11051373.
Li, W., and V. E. Cabrera. 2021. Revealing the Effects of Reproduction and Turnover Rate on Farm Profitability through Herd Structure Dynamics. Appro. Poult. Dairy & Vet Sci 8(1). https://doi.org/10.31031/APDV2020.08.000678.
Martin, M. J., J. R. R. Dórea, M. R. Borchers, R. L. Wallace, S. J. Bertics, S. K. DeNise, K. A. Weigel, and H. M. White. 2021. Comparison of methods to predict feed intake and residual feed intake using behavioral and metabolite data in addition to classical performance variables. Journal of Dairy Science. Accepted. https://doi.org/10.3168/jds.2020-20051
Oliveira, D.A.B., L. G. R. Pereira, T. Bresolin, R. E. P. Ferreira. J.R.R. Dorea. 2021. A Review of Deep Learning Algorithms for Computer1Vision Systems in Livestock. Livestock Science (accepted).
Schachtschneider KM, Schook LB, Meudt JJ, Shanmuganayagam D, Zoller JA, Haghani A, Li CZ, Zhang J, Yang A, Raj K, Horvath S. Epigenetic clock and DNA methylation analysis of porcine models of aging and obesity. GeroScience 2021. doi.org/10.1007/s11357-021-00439-6 (In Press).
Skevas, T., I. Skevas, and V. E. Cabrera. (Accepted 22 March 2021). Examining the Relationship Between Social Inefficiency and Financial Performance. Evidence from Wisconsin Dairy Farm. Sustainability 13(7): 3635. https://doi.org/10.3390/su13073635.
Skevas, T., I. Skevas, and V. E. Cabrera. 2021. Farm profitability as a driver of spatial spillovers: The case of somatic cell counts on Wisconsin dairies. Agricultural and Resource Economics Review 00:00-00. https://doi.org/10.1017/age.2020.22.
Uddin, M. E., H. A. Aguirre-Villegas, R. A. Larson, and M. A. Wattiaux. Carbonprint of milk from Holstein and Jersey cows fed low or high forage diet with alfalfa silage or corn silage as the main forage source. J. Cleaner Production 298:126720 (https://doi.org/10.1016/j.jclepro.2021.126720)
2020
Feye, K.M., D.R.Thompson, M.J. Rothrock, M.H. Kogut, and S.C. Ricke. 2020. Poultry processing and the application of microbiome mapping. Poultry Sci. 99: 678-688.
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.
2019
Ouellet, V., V. E. Cabrera, L. Fadul-Pacheco, and É. 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)
Krpálková, L., V. E. Cabrera, L. Zavaldilová, and M. Å tÃpková. 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.
2018
Ricke, S.C., S.A. Kim, and S. H. Park. 2018. Molecular-based identification and detection of Salmonella in food production systems: Current perspectives. J. Appl. Microbiol. 125: 313-327.
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. 2018:1–8. 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 101:8335–8349. (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.
2017
Kim, S.A., S.H. Park, S.I. Lee, C.M. Owens, and S.C. Ricke. 2017. Assessment of chicken carcass microbiome responses during processing in the presence of commercial antimicrobials using a next generation sequencing approach. Scientific Repts. 7:43354. doi: 10.1038/srep43354.
Park, S.H., S.I. Lee, S.A. Kim, K. Christensen, and S.C. Ricke. 2017. Comparison of antibiotic supplementation versus a yeast-based prebiotic on the cecal microbiome of commercial broilers. PLoS ONE 12(8): e0182805. https://doi.org/10.1371/ journal.pone.0182805
Park, S.H., S.A. Kim, P.M. Rubinelli, S.M. Roto,and S.C. Ricke. 2017. Microbial compositional changes in broiler chicken cecal contents from birds challenged with different Salmonella vaccine candidate strains. Vaccine 35: 3204-3208.
Rubinelli, P.M., S.A. Kim, S.H. Park, S.M. Roto*, N.J. Nealon, E.P. Ryan, and S.C. Ricke. 2017. Differential effects of rice bran cultivars to limit Salmonella Typhimurium in chicken cecal in vitro incubations and impact on the cecal microbiome and metabolome. PLoS ONE 12(9): e0185002. doi.org/10.137/journal.pone0185002.
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-Vázquez, 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
2020
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.
2019
Rackerby, B., S.I. Lee, I. Moppert, S.C. Ricke, K.C. Jeong, and S.H. Park. 2019. Chapter 2. Application of whole genome sequencing to transposon mutants of Salmonella Heidelberg. pp. 17- 27. In: S.C. Ricke, S.H. Park, M.L. Davis. (Eds.) Microbial Transposon Mutagenesis: Methods and Applications. Springer Science, New York, NY.
Yang, Y., R. Chandrashekar, S.C. Ricke, and Y.M. Kwon. 2019. Chapter 13. Construction of DNA- barcode-tagged Salmonella strains. pp. 141 – 150. In: S.C. Ricke, S.H. Park, M.L. Davis. (Eds.) Microbial Transposon Mutagenesis: Methods and Applications. Springer Science, New York, NY.
Lee, S.I., S.A. Kim, S.H. Park, and S.C. Ricke. 2019. Molecular and new generation techniques for rapid detection of foodborne pathogens and characterization of microbial communities in poultry meat. pp. 235-260, In: Venkitanarayanan, K., S. Thakur, and S.C. Ricke (Eds.) Food Safety in Poultry Meat Production Springer Science, New York, NY.
Feye, K.M. and S.C. Ricke. 2019. Chapter 18. Establishment of a standardized 16S rDNA library preparation to enable analysis of microbiome in poultry processing using Illumina MiSeq platform. pp. 213-227. In: Arnaud Bridier (Ed.) Foodborne Bacterial Pathogens: Methods and Protocols. Methods in Molecular Biology. Springer Science, New York, NY.
Ricke, S.C., T.M. Dawoud, S. A. Kim, S.H. Park, and Y.M. Kwon 2018 Chapter 1. Salmonella cold stress response: Mechanisms and occurrence in foods. In: G.M. Gadd and S. Sariaslani (Eds.) Advances in Applied Microbiology 104: 1-38.
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)
2017
Ricke, S.C., J. Hacker, K. Yearkey, Z. Shi, S.H. Park, and C. Rainwater. 2017. Chap. 19. Unravelling food production microbiomes: Concepts and future directions. In: S.C. Ricke, G.G. Atungulu, S.H. Park, and C.E. Rainwater (Eds.) Food and Feed Safety Systems and Analysis. Elsevier Inc., San Diego, CA pp. 347-374.
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)
2016
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.
2015
Ricke, S.C., T.M. Dawoud, and Y.M. Kwon. 2015. Chapter 4. Application of molecular methods for traceability of foodborne pathogens in food safety systems. In: S.C. Ricke, J.R. Donaldson, and C.A. Phillips (Eds.) Food Safety: Emerging Issues, Technologies and Systems. Elsevier, Oxford, UK, pp. 37-63.
2014
Ricke, S.C. and R.K. Gast. 2014. Salmonella/Salmonella Enteritidis. In Encyclopedia of Food Microbiology- 2nd Edition, Vol. 3, pp. 343-348. Carl Batt and Mary Lou Tortello (Eds.), Elsevier, Ltd. Oxford, UK.
Krpálková, L., V. E. Cabrera, J. Kvapilik, J. Burdych, M. Štipková, P. Crump, L. Stádnik, 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, Saarbrücken, 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.
2013
Ricke, S.C., O.-K. Koo, S. Foley, and R. Nayak. 2013. Chapter 7. Salmonella. In Guide to Foodborne Pathogens- 2nd Edition, R. Labbé and S. García (Eds.), Wiley-Blackwell, Oxford, UK, pp. 112-137.
2012
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)
2009
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 Niño: New research, p. 163-179, Nova Science Publishers, Inc., Hauppauge, NY. (Chapter)
2007
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.
2006
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
2020
Steve Ricke: “Metabolism of the Microbiome” Symposium – The Future of the Poultry Gut-Health Nexus: Improving Food Safety. International Association for Food Protection Annual Virtual Meeting, Online, Oct. 26-28, 2020.
Steve Ricke: “Delivery of Bioinformatics in Poultry Processing” Poultry Science Annual Virtual Meeting, Online, July 20, 2020.
2019
Steve Ricke: “Optimizing Feed Additives in Poultry Using Microbiome Analyses”, Symposium on Gut Health in Production of Food Animals, Hilton St. Louis at the Ballpark, St. Louis, MO, Nov. 5, 2019.
Steve Ricke: “Campylobacter Interventions and the Gastrointestinal Tract Microbiome”, Campylobacter, Helicobacter, and Related Organisms Conference- 2019, ICC Belfast, 2 Lanyon Place, Belfast, UK. Sept. 11, 2019.
Steve Ricke: “What is an Ideal Feed Additive for Broilers and How Can We Assess This? Keynote Presentation, 6th International Conference on Poultry Intestinal Health, Auditorium Del Massino Via Massimiliano Massino, 1 00144, Rome, Italy, Apr. 5, 2019.
Steve Ricke: “Application of Microbiome Sequencing in Food Processing Environments”, 16th Annual Conference of the Midsouth Computational Biology & Bioinformatics Society, McBios Informatics for Precision Medicine, UAB Informatics Institute. Hilton Birmingham at University of Alabama, Birmingham, AL, Mar. 29, 2019.
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. Asociación 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.
2018
Steve Ricke: “Review of Existing In – Feed Solutions to Reduce Antibiotic Dependence on Farm”, Symposium on Interventions to Reduce Antibiotic Resistance and Antibiotic Use in Animal Production, International Association or Food Protection – European Symposium on Food Safety, Stockholm, Sweden, Apr. 26, 2018.
Steve Ricke: “Prebiotics and the Avian Microbiome – Research Strategies and Applications”, Dept. of Pathology, Bacteriology, and Avian Diseases, Faculty of Veterinary Medicine – Merelbeke, Ghent University, Ghent, Belgium, Mar. 7, 2018.
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 cows’ 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.
2017
Steve Ricke: “Salmonella Vaccines and the Microbiome in Poultry – A New Food Safety Paradigm”, The Korean Society of Food Hygiene and Safety, The K Hotel, Seoul, South Korea, Nov. 10, 2017.
Steve Ricke: “Foodborne Salmonella in Poultry and Food Production: Research Strategies”, William C. Frazier Lecture, Food Research Institute – Spring Meeting, Pyle Center – University of Wisconsin, Madison, WI, May 17, 2017.
2016
Steve Ricke: “Stacking the Deck in the Gut – Current Status and Future Prospects of Prebiotics”, 59th Annual Meeting Puerto Rico Society of Microbiologists – American Society for Microbiology – Local Branch, Industrial Microbiology – From the Lab Bench to the Production Line and Beyond, Verdanza Hotel, 8020 Tartak Street, Isla Verde Carolina, Puerto Rico, May 27, 2016.
2013
Steve Ricke: “Application of Genomics and Metabolite Analysis to Assess Poultry Gastrointestinal Ecology Response to Prebiotics”, College of Food Science & Nutritional Engineering, East Campus, China Agricultural University, No. 17 Quinghua Donglu, Hai Dian District, Beijing, P.R. China, Nov. 14, 2013.
Selected Popular Press Articles
2020
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)
Making data work on the farm. Hoard’s Dairyman. April 25 2020 (Article)
Creating value from data. Hoard’s Dairyman. May 10 2020 (Article)
2019
Big Data, Big Opportunities. Progressive Dairy. July 29 2019 (Article)
2018
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
2016
Akins, M.S. and M. A. Hagedorn. Putting a price tag on raising replacements. Hoard’s Dairyman. April 2016
2015
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)
2012
Alali, W., P. Crandall, K. Gibson, D. Jaroni, G. Kostandini, S. Ricke, L. Trimble, S. Angioloni, and M. L. Davis. 2012. From food safety to economics: Processing your chickens for market. APPPA Grit Nov/DecIssue 72: 6-8, 10.
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)
2011
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
2020
Dittoe, D.K., K. M. Feye, and S. Ricke. 2020. Salmonella and Campylobacter influence the microbiota response of skin-on, bone-in chicken thighs treated with different antimicrobials. Poultry Science Association Annual Virtual Meeting, Online, July 20th – 22nd.
Clark, K.M., J.P. Holt, L.E. Anderson, D.K. Dittoe, and S.C. Ricke. 2020. Characterizing sow microbiome and drinking water quality at different production locations. Animal Science Association Annual Virtual Meeting, Online, July 19th – 23rd.
2019
Wages, J.A., K.M. Feye, B.J. Bench, and S.C. Ricke. 2019. Next generation sequencing of subsamples used for traditional microbiological analysis of Campylobacter in broiler carcass rinsates collected with neutralizing buffered peptone water or buffered peptone water. Poultry Science Association Annual Meeting, Montreal, Québec, Canada, July 15th – 18th.
Feye, K.M., P.M. Rubinelli, H.O. Pavlidis, J.A. Byrd, W.E. Chaney, D.R. McIntyre, and S.C. Ricke. 2019. Changes to the microbiome may mediate the anti-Salmonella effects demonstrated by XPCTM, International Poultry Scientific Forum, Atlanta, GA, Feb. 11-12th.
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
2018
Feye, K.M., L. R. Meyer, H. Lekkala, D.R. Thompson and S.C. Ricke. 2018. Assessment of computer science and cybersecurity skills of undergraduate students interested in food safety. Poultry Science Association Annual Meeting, San Antonio, TX, July 22nd – 26th.
Micciche, A.C., L.M., Meyer, and S. C. Ricke. 2018. 16S rDNA-based sequencing as a rapid method to identify bacteria cultivated from nonselective aerobic plate bacterial colonies isolated from commercial poultry feed. Poultry Science Association Annual Meeting, San Antonio, TX, July 22nd – 26th.
2017
Park, S.H., S.A. Kim, P. Rubinelli, C.A. Baker, and S.C. Ricke. 2017. Effect of Salmonella vaccine strains on broiler chicken cecal microbiota. International Assoc. Food Prot. Annual Meeting, Tampa, FL July, 9-12.
Kim,S.A. S.H. Park, A.D. Wolfenden, B.M. Hargis, H.O. Pavlidis, D.R. McIntrye, and S.C. Ricke. 2017. Characterization of mixed bacterial populations in chicken ceca recovered from colonies on Campylobacter selective commercial media using 16S rRNA next generation sequencing. Poultry Science Association Annual Meeting, Orlando, FL, July 16th -20th.
2016
Kim, S.A., S.H. Park, and S.C. Ricke. 2016. Development of a rapid method to quantify Salmonella Typhimurium using a combination of MPN and qPCR with a shortened enrichment time. International Assoc. Food Prot. Annual Meeting, St. Louis, MO, July 31st– Aug. 3rd.
Kim, S.A., S.H. Park, S.I. Lee, and S.C. Ricke. 2016. Assessment of different microbial populations on chicken carcasses at various first processing steps using a next generation sequencing approach. Poultry Science Association Annual Meeting, New Orleans, LA, July 11th -14th.
Park, S.H., S.I. Lee, and S.C. Ricke. 2016. In-depth analysis of broiler chicken gut microbiome responses over time fed a commercial yeast-based prebiotic. Amer. Soc. Microbiol. General Annual Meeting, Boston, MA, June 16-20.
Wages, J., J. Handley, S. H. Park, and S.C. Ricke. 2016. Comparison of indicator microbial populations occurring during multiple stages of commercial poultry carcass processing by conventional plating method and next generation sequencing. International Poultry Scientific Forum, Atlanta, GA, Jan. 26-27th.
Selected Other Publications
2020
Ricke, S.C. (Ed.) 2020. Improving Gut Health in Poultry. Burleigh Dodd Publishing, Cambridge, UK. 522 pp.
2019
Ricke, S.C., S.H. Park, and M.L. Davis. (Eds.) 2019. Microbial Transposon Mutagenesis: Protocols and Applications. Methods and Applications. Humana Press. Springer Science, New York, NY 183 pp.
Venkitanarayanan, K., S. Thakur, and S.C. Ricke (Eds.) 2019. Food Safety in Poultry Meat Production, Springer Science, New York, NY. 301 pp.
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.
2018
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)
2017
Ricke, S.C. (Ed.) 2017. Achieving Sustainable Production of Poultry Meat- Volume 1 Safety, Quality and Sustainability. Burleigh Dodd Publishing, Cambridge, UK. 480 pp.
Ricke, S.C., G.G. Atungulu, S.H. Park, and C.E. Rainwater (Eds.) 2017. Food and Feed Safety Systems and Analysis. Elsevier Inc., San Diego, CA 406 pp.
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)
2016
Ricke, S.C. and R.K. Gast (Eds.). 2016. Producing Safe Eggs-The Microbial Ecology of Salmonella. Elsevier, Inc., San Diego, CA. 436 pp.
Bach, A. V. E. Cabrera 2016. Robotic milking: feeding strategies and economic returns. Journal of Dairy Science 99 (Suppl. 1): 35
2015
Ricke, S.C., J.R. Donaldson, and C.A. Phillips (Eds.) 2015. Food Safety: Emerging Issues, Technologies and Systems. Academic Press, Elsevier, Inc., Oxford, UK, 449 pp.
Cabrera, V. E. 2015. Economics of production efficiency: Nutritional grouping. Journal of Dairy Science 98 (Suppl. 2): 350. (Abstract) (Presentation)
2014
Cabrera, V. E. 2014. Impact of decision support tools available for dairy farm management. Animal Science 92 (E-Suppl. 2):293. (Abstract) (Presentation)
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)
2013
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)
2012
Ricke, S.C., E.J. Van Loo, M.G. Johnson and C.A. O’Bryan (Eds.), 2012. Organic Meat Production and Processing. Wiley Scientific/IFT, New York, NY 444 pp.
Callaway, T.R. and S.C. Ricke (Eds.), 2012. Direct Fed Microbials/Prebiotics for Animals: Science and Mechanisms of Action, Springer Science, New York, NY, 206 pp.
2011
Kwon, Y.M. and S.C. Ricke (Eds), 2011. High-Throughput Next Generation Sequencing: Methods and Applications. Methods in Molecular Microbiology 733 – Springer Protocols, Humana Press, New York, NY 308 pp.
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)
2010
Ricke, S.C. and F.T. Jones (Eds), 2010. Perspectives on Food Safety Issues of Food Animal Derived Foods, University of Arkansas Press, Fayetteville, AR, 362 pp.
2009
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)