Progress 09/01/15 to 09/30/18
Outputs
Target Audience:Project reachedscientists and students at the University of Wisconsin, other universities in the US and colleagues abroad.Information from project reacheddairy farmers inWisconsin and other States, some in other countriesand a broad spectrum ofdairy farm nutritionists and consultants. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project has trained to MS students: Yaqi Wu and Jorge Barrientos. Both in the Dairy Science Department. Student Yaqi Wu presented her work at the Dairy Science Seminar (DySci 900) in Spring 2017 andat the American Dairy Science Association annual meeting in Pittsburg, June 2017. Student Jorge Barrientos presented his work at the Dairy Science Seminar (DySci 900) in Spring 2018 andat the American Dairy Science Association annual meeting in Knoxville, June 2018. How have the results been disseminated to communities of interest?Scientific results have been presented at the American Dairy Science Association annual meeting in June 2017 (Pittsburg) and in June 2018 (Knoxville).Results have also been discussed in several seminars and lab meetings at the UW-Dairy Science department. Practical outcomes and applications have been shared with the UW-Extension system in coordinated programming with County Extension and also industry professionals. Jorge's application has been highlighted on several presentations related to a leveraging UW-2020 "Dairy Brain" project. Some of those included UW-2020 Advisory Committee in Madison, WI (January 2018); International Congress of Bovine Medicine (ANEMBE) in Vigo, Spain (June, 2018); International Farming System Association meeting in Chania, Greece (June 2018); USDA-NC2042 meeting in Roanoke, VA (October, 2018); USDA-SCC084 meeting in Madison, WI (November, 2018). What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
This project trained two MS students: Yaqi Wu and Jorge Barrientos. Yaqi addressedmostlygoal (1) to improve grouping nutritional managementwhereasJorge tackled mostly goal (2) implementing a system to integrate information and develop a farm decision system. Yaqi developed a "mixed integer programming" optimization model to maximize the milk income minus the feed costs by allocating cows to nutritional groups according to farm constraints. She found that this methodology performs better than the scientific state-of-the-art for grouping cows, clustering cows according to their nutrient requirements. She presented her work at the 2017 ADSA (Annual Dairy Science Meeting) in Pittsburg, which was then upgraded to a scientific paper that is currently under review at theJDS (Journal of Dairy Science). We expect this paper to be accepted any time soon and we expect these findings torevolutionize the thinking about nutritional grouping and economicfeed efficiency at the herd level.Jorge implemented these concepts on his research, but in addition, he was very interested in a practical application that farmers can use in a permanent basis. As such, he worked intensively in (a) real-time integration of disparate data streams required for the analysis (e.g., herd management data + feed management data + dairy herd improvement (DHI) data + diet formulation data). These data are normally disconnected on farms and therefore unavailable for continuous analyses. And (b) implement a practical nutritional grouping strategy in a farm without disrupting actual management and flow of animals to pens. He was successful developing code to extract and connect live data streams, propose allocation of cows to farm pens, and formulate diets according to farm constraints resulting in a SOP (standard operation protocol) for the farm to follow. His analyses showed that a particular farm could improve profitability by about $50/cow per year when following the proposed SOP. His work has been presented at the 2018 ADSA meeting in Knoxville and a paper is being finalized for submission. Based on these, a decision support system is available to be implemented in a practical way in commercial dairy farms. We expect that our 3,000-cow collaborating farm will be the first one on taking advantage of these discoveries. Since this is a prominent farm, we expect many other farms will follow.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Cabrera, V. E. 2018. Helping dairy farmers to improve economic performance utilizing data-driving decision support tools. Animal 12(1):134-144.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
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.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
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.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Barrientos, J. A., R. D. Shaver, and V. E. Cabrera. 2018. Improving nutritional accuracy and economics through multiple ration-grouping strategy. In Proceedings XXIII International Congress ANEMBE of Bovine Medicine, Vigo, Spain, 06-09 June 2018.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Barrientos, J., R. Shaver, V. E. Cabrera, and D. Liang. 2018. Improving nutritional accuracy and economics in commercial dairy farms. 2018 Professional Dairy Producers of Wisconsin Business Conference. Alliant Energy Center, Madison, 14-15 March 2018.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Liang, D., H. Delgado, H. White, and V. E. Cabrera. 2018. Data up to your eyeballs. Proceedings 2018 Professional Dairy Producers of Wisconsin Business Conference. Alliant Energy Center, Madison, 14-15 March 2018.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Barrientos, J., E. Charbonneau, S. Binggeli, and V. E. Cabrera. 2018. Improving nutritional accuracy and economics through multiple ration-grouping strategy. Symposium sur les bovins laitiers. 30 October 2018. Drummondville, Quebec, Canada.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Cabrera, V. E. 2018. What are the economic advantages of grouping and feeding dairy cows by nutritional need? Proceedings of 29th Annual Florida Ruminant Nutrition Symposium. Gainesville, FL 5-7 February 2018.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2019
Citation:
Wu, Y., D. Liang, R. D. Shaver, and V. E. Cabrera. 2019 under review. An income over feed cost nutritional grouping strategy. Journal of Dairy Science 00:00-00.
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Progress 10/01/16 to 09/30/17
Outputs
Target Audience:Our project reached colleagues at the University of Wisconsin, researchers from the USDA Forage Center, dairy farmers in Wisconsin and other States, and dairy farm nutritionists and consultants. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Student Yaqi Wu attended to the American Dairy Science Association annual meeting in Pittsburg, June 2017. How have the results been disseminated to communities of interest?Results had been presented at the American Dairy Science Association annual meeting in Pittsburg, June 2017 in addition to several seminars at the UW-Dairy Science department. Additionally, outcomes of the project were partially shared through the UW-Extension system. What do you plan to do during the next reporting period to accomplish the goals?We will finalize the paper that describes the optimization of nutritional grouping, which should be submitted in the first quarter of 2018. Student Jorge Barrientos will continue collecting and analyzing data of a large local farm to assess the best protocols to improve the efficiency of feeding cows within the already established grouping strategies of the farm.
Impacts
What was accomplished under these goals?
A model has been created. The model, created by student Yaqi Wu, absorbs the actual farm data and bases it on optimizing the allocation of cows to be grouped under the same diet to maximize milk income minus the feed cost, the major component of dairy farms' profitability. The data for Yaqi's analyses came from 7 Wisconsin farms provided by BoviSynch (a dairy farm software company based on Green Bay). These data are what is called "test control Dairy Herd Improvement (DHI) data" that most of dairy farms go through every month. The data contains cow-level information on milk yield, fat, protein, conductivity, somatic cell counts, etc. The data for Jorge's project is "live" and it is permanently coming from a large (~3,000 cow) dairy farm close by campus These data sets all come from different data collection software/systems- dairy records software, feed software, milking parlor data, even genetics data. Jorge is aggregating all these data to understand and follow up the grouping strategies of cows and propose more efficient ways to group the cows for more precise feeding. The model has been presented at the annual American Dairy Science Association meeting. A paper is under finalization for submission to the Journal of Dairy Science. In parallel, another student, Jorge Barrientos, is working with farm data to understand the grouping strategies applied to dairy cows on a permanent basis to propose a more efficient way to group the cows thereby improving feed efficiency and consequently profitability.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Wu, Y., V. E. Cabrera, R. D. Shaver. 2017. Maximizing income over feed cost by grouping cows with mixed-integer programing. Journal of Dairy Science 100 (Suppl. 2): 327.
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2018
Citation:
Cabrera, V. E. 2017. Helping dairy farmers to improve economic performance utilizing data-driving decision support tools. Animal 1-11.
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2017
Citation:
Cabrera, V. E. 2017. Economics of nutritional grouping. Lely North America FMS Conference. Fair Oaks Farms, IN.
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Progress 10/01/15 to 09/30/16
Outputs
Target Audience:We reached dairy farmers in Wisconsin, dairy farm nutritionists and dairy farm consultants. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One graduate student is being trained on this project. How have the results been disseminated to communities of interest?Through presentations at scientific meetings, scientific abstracts, and paper proceedings. What do you plan to do during the next reporting period to accomplish the goals?We anticipate to present results of current research analyses at the annual Dairy Science Meeting and produce a paper. The paper will describe new methods to group cows for improved milk income minus feed costs. Methodology and results will become an important baseline for the project for continued research and extension endeavors.
Impacts
What was accomplished under these goals?
The project student, Yaqi Wu, is working in the research objective of project -developing a sophisticated simulation model to quantify the economic value of nutritional grouping strategies. The optimization model based on "mixed integer programming" that maximizes the milk income minus feed costs (IOFC) when grouping the cows nutritionally. In the past, other criteria had been used to nutritionally group cows like days in milk or productivity. The best known way to group cows had been the "cluster" which groups cows according to their nutritional requirements. Preliminary results of Yaqi shown that the mixed integer programming could be even better than the cluster improving the farm IOFC when grouped based on maximum IOFC; so it is promising. Yaqi is planning to submit an abstract the the annual dairy science meeting and present this work in June this year in Pittsburg. Lastly, the first set of results are anticipated to be presented at the annual Dairy Science Meeting in Pittsburg in June 2017.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Cabrera, V. E. 2016. Impact of nutritional grouping on the economics of dairy production efficiency. 67th European Federation of Animal Science (EAAP). 29 August September 2. Belfast, U.K.
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Cabrera, V. E. 2016. Dietary grouping strategies to improve profitability on dairy farms. Engormix: 7 August 2016.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Cabrera, V. E. 2016. Impact of nutritional grouping on the economics of dairy production efficiency. Tri-State Dairy Nutrition Conference. April 18-20, 2016. Grand Wayne Center, Fort Wayne, Indiana.
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