Source: UNIV OF MINNESOTA submitted to
DAIRY CATTLE MANAGEMENT, WELFARE AND BEHAVIOR
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
1001363
Grant No.
(N/A)
Project No.
MIN-16-021
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Oct 1, 2013
Project End Date
Sep 30, 2018
Grant Year
(N/A)
Project Director
Endres, MA, I.
Recipient Organization
UNIV OF MINNESOTA
(N/A)
ST PAUL,MN 55108
Performing Department
Animal Science
Non Technical Summary
Animal welfare is an important issue that impacts consumer confidence in animal production. Surveys taked in the last 15 years indicate strong public concern for farm animal welfare, i.e. that animals have a 'good life'. Producers also want to provide the best care possible to their animals, not only because it is the right thing to do, but because animal welfare can affect productivity. Research is needed to learn best management practices and housing that can improve welfare of dairy cattle. That is the goal of our project.
Animal Health Component
0%
Research Effort Categories
Basic
15%
Applied
85%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
30734103100100%
Knowledge Area
307 - Animal Management Systems;

Subject Of Investigation
3410 - Dairy cattle, live animal;

Field Of Science
3100 - Management;
Goals / Objectives
The ultimate goal is to improve welfare and productivity of dairy cows. The project will aim to optimize management and housing in large, organic and robotic milking dairy operations and to use automatic behavior monitoring devices to detect disease and other early lactation disorders in dairy cows.
Project Methods
The project includes collecting on-farm welfare and behavior data from various dairy operations, dairy cow records for 2 years, economic data as appropriate, housing characteristics, and management protocols. Best management practices will be developed using the data collected from these farms (types of farm will vary, so best practices will also vary) and disseminated to the intended audience. Learning and intended behavior change evaluations will be conducted at every extension event, and follow-up surveys of what changes have been made by producers who attended the events will be conducted one year later. Veterinarians and other consultants will be asked to report of any changes they have observed on their client's operations that happened mostly due to implementation of practices originating from the project. In addition, information from this project will be used to develop classroom materials for two undergraduate animal science courses in dairy production management systems and a veterinary lecture on bovine behavior.

Progress 10/01/13 to 09/30/18

Outputs
Target Audience:Dairy veterinarians, consultants, nutriitionists, academics, extension educators, students, producers Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?During the entire project period, four PhD and five MS students completed their degrees, and one MS and one PhD student started their programs. In addition, one post-doctoral researcher, two visiting professors, one visting PhD student and eight undergraduate students were trained. The project director and her team attended numerous scientific and extension conferences. How have the results been disseminated to communities of interest?The project director and her team presented research results at over 35 scientific and extension events in the US and abroad. Besides scientific articles, information was disseminated via industry media with appearances on TV, radio, newspaper and magazines, including Bloomberg News and the Associated Press. An article on cow comfort was published in the Star Tribune in 2018. Feld days on Minnesota dairy farms were attended by more than 3000 people over the project period. Results were also disseminated via social media (Twitter and Facebook) and the extension website. Various events were organized during the project period, including two Precision Dairy Farming conferences chaired by the project director and a symposium on Precision Dairy at the 2017 ADSA annual meetings also chaired by the project director. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Automated technologies to milk, feed, or monitor cattle are becoming more common in the USA. There has been a steady growth in the number of robotic milking dairy operations in the upper Midwest and also in other regions of the country. This trend might help keep more dairy farms in business as the younger generation prefers technology and would come back to the farm, which will help improve US economy and help sustain the dairy industry. It is important to conduct research that focuses on these systems as it is estimated that a larger proportion of farms in the US will be using this technology in the future and we should be proactive when conducting research. Studies performed under this project have helped improve the use of automated milking systems, which can result in higher milk production and improved animal wellbeing. One of our studies found that cow milking speed, milking frequency, use of a robotic feed pusher, cow comfort index (how well cows use the stalls), amount of concentrate feed consumed at the milking station, and number of cows per robot were associated with greater daily milk production per cow and per robot. Producers have increased the use of robotic feed pushers as one of our more recent studies indicates that 66% of robotic milking farms are using them in 2018 compared to 35% of the farms in an earlier study in 2014. In a study with 82 randomly selected conventional milking dairy farms in Minnesota, we compared the top 25th percentile farms for milk production with the other 75th percentile farms. Although there is a trend for an increase in robotic milking farms in the US, conventional farms are still the majority of farms and we still need to learn how to better manage these farms. Better management will result in improved cow performance and farm profitability. We found that factors such as stall comfort, pen design, dry matter intake, forage management, cow time budget, milking frequency, use of bST, footbath management and cow grouping differed between the two categories for milk production. Factors influencing feed cost per cwt and energy-corrected milk production per cow were also evaluated. We consistently find that cow comfort is a key factor for improved performance in dairy cows. Another study showed that the welfare of dairy cows in very large dairy operations (average of approximately 5,000 cows per herd) was adequate (based on low prevalences of lameness and hock lesions, low somatic cell count and mastitis incidence, etc) and these dairy farms can dilute their cost of production per cow due to their economies of scale. They have specialized and efficient labor, averaging over 100 cows per FTE (full time employee equivalent). Another objective of this project was to investigate whether cow behaviors and activity such as feeding and resting time, rumination and social ranking during the prepartum and early postpartum period could be used to help producers identify cows at risk for health disorders. One of our studies confirmed that most cows die or leave the herd during the first 40 days after calving; therefore, identifying animals at risk earlier, before they become severely ill, could reduce on farm cow mortality and improve animal health with tremendous economic and animal welfare benefits to the dairy industry. A reduction in on-farm mortality from the current 6% to 3% would result in an estimated economic benefit of over $500 million to the US dairy industry. Better health is one aspect of good animal welfare and achieving it requires improving many aspects of the cow's environment and management. Improved animal welfare is something that the general public has increasingly greater interest. When animals are housed in groups (the trend in the dairy industry), it is more difficult to monitor individual animals. In one of our studies with cows on pasture, we validated an ear tag accelerometer that is supposed to monitor feeding, resting, rumination and activity behavior of cows. Previous validation studies had been reported only for confinement systems. We found that this ear tag system accurately measured eating and rumination times, moderately measured resting time, and less accurately measured activity. It appeared that the activity behavior could have been affected by fly pressure on pasture. It was encouraging that feeding behavior could be measured by this technology even on pasture systems. In one of our studies (with cows in confinement) we found that monitoring cow feeding behavior during the 3 weeks immediately prior to calving helped identify animals that went on having two or more health disorders soon after calving. These results are very promising, as more technology is being developed and used in the dairy industry, including face recognition. As technology becomes more ubiquitous and affordable, we will be able to more closely monitor cows and identify animals at risk early, reducing on farm mortality and improving animal wellbeing.

Publications

  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Siewert, J. M., Salfer, J. A., & Endres, M. I. (2018). Factors associated with productivity on automatic milking system dairy farms in the Upper Midwest United States. Journal of Dairy Science, 101(9), 8327-8334. doi: 10.3168/jds.2017-14297
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Salfer, J. A., Siewert, J. M., & Endres, M. I. (2018). Housing, management characteristics, and factors associated with lameness, hock lesion, and hygiene of lactating dairy cattle on Upper Midwest United States dairy farms using automatic milking systems. Journal of Dairy Science, 101(9), 8586-8594. doi: 10.3168/jds.2017-13925
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: G.M. Pereira, B.J. Heins, M.Endres, and K. Minegishi. 2018. Estrus detection with an activity and rumination monitoring system in an organic grazing and in a low-input conventional herd. J. Dairy Sci.101 (Suppl.2):153
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Endres, M.I. 2018. Invited talk: What have we learned about automated milk feeders? J. Dairy Sci.101 (Suppl.2):162
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Peiter, M., M.H.O. Pasetti, J.A. Salfer, and M.I. Endres. 2018. Does the training of nulliparous cows to use a robotic milking system influence their milk yield and milking frequency? J. Dairy Sci.101 (Suppl.2):283
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Peiter, M., M.H.O. Pasetti, J.A. Salfer, and M.I. Endres. 2018. A comparison of milk yield and milking frequency of primiparous versus multiparous cows in robotic milking systems. J. Dairy Sci.101 (Suppl.2):284
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Endres, M.I. 2018. Invited talk: Automated milk feeders for preweaned dairy calves in the Upper Midwest United States. Midwest ADSA: Abst.74
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Medrano-Galarza,C.,S.J.LeBlanc,...T.J.DeVries,J.Rushen,M.I.Endres,D.B. Haley. 2018. Effect of age of introduction to an automated milk feeder on calf learning and performance and labor requirements. Journal of Dairy Science, 101(10), 9371- 9384. doi: 10.3168/jds.2018-14390
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Medrano-Galarza,C.,S.J.LeBlanc,...T.J.DeVries,J.Rushen,M.I.Endres,D.B. Haley. 2018. Associations between management practices and within-pen prevalence of calf diarrhea and respiratory disease on dairy farms using automated milk feeders. Journal of Dairy Science, 101(3), 2293-2308. doi: 10.3168/jds.2017-13733
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Pereira,G.M.,B.J.Heins,and M.I.Endres. 2018. Technical note: Validation of an ear-tag accelerometer sensor to determine rumination, eating, and activity behaviors of grazing dairy cattle. Journal of Dairy Science, 101(3), 2492-2495. doi: 10.3168/jds.2016-12534


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

Outputs
Target Audience:Dairy producers, veterinarians, dairy industry advisors, researchers, extension educators, students Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The project director and/or her graduate students attended various events, including national ADSA meetings, Four-State and Tri-State Dairy Nutrition Conferences, US Precision Dairy Farming conference, and dairy field days among others. A visiting PhD student from Brazil was mentored. Visits to dairy farms for whole-system management analysis took place during the year. How have the results been disseminated to communities of interest?Research results were presented at ADSA meetings in Pittsburgh, ISAE International meeting in Denmark, various conferences in the US, and also used for teaching of undergraduate students. University of Kentucky and University of Minnesota co-organized the 3nd US Precision Dairy Farming Conference in Lexington, KY where many precision dairy technologies were discussed and results were presented. The PD authored two book chapters in the Large Dairy Herd Management ADSA publication. Information resulting from the project was also disseminated via dairy industry publications such as Hoard's Dairyman and Dairy Herd, via social media and posted on the Dairy Extension website. What do you plan to do during the next reporting period to accomplish the goals?It is estimated that five journal articles will be submitted for publication in 2018. Presentations will be given at various events thoughout the year. The project will be completed and a new project proposal will be submitted in the area of dairy management and welfare.

Impacts
What was accomplished under these goals? Automated technologies to milk, feed, or monitor cattle behavior are becoming more common in the USA. University of Minnesota research has helped improve the use of automated milking and calf milk feeding systems, which can result in improved cattle productivity and wellbeing. It was found that cow milking speed, milking frequency, use of a robotic feed pusher, cow comfort index, amount of concentrate consumed at the milking station, and cows per robot were associated with greater daily milk production per cow and per robot. Overall median annual mortality rate of preweaned calves fed with automated milking systems was 2.6% and 57% of farms reported mortality rates below 3%/yr. Mortality rate was associated with navel disinfection, farm size, age range in calf groups and serum total protein concentration. Calf health scores were associated with season of measurement, bacterial counts in the milk, peak milk allowance, time to reach peak milk allowance, space per calf, group size, and use of positive pressure ventilation system. Validation of a cow sensor technology helped the industry better understand the need for considering aspects of the environment like fly pressure when developing algorithms for activity behavior. A study with 82 randomly selected dairy farms in Minnesota compared top 25th percentile farms for milk production with other farms and found that factors such as stall comfort, pen design, dry matter intake, forage management, cow time budget, milking frequency, use of bST, footbath management and cow grouping differed between the two categories for milk production. Factors influencing feed cost per cwt and energy-corrected milk production per cow were also evaluated. Improving these factors on dairy farms will result in great profitability and therefore, improved sustainability of the dairy industry.

Publications

  • Type: Book Chapters Status: Published Year Published: 2017 Citation: Endres, M.I. 2017. The relationship of cow comfort and flooring to lameness disorders in dairy cattle. Vet. Clin. North Am. Food Anim. Pract. 33:227233.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Jorgensen, M.W., A. Adams-Progar, A.M.de Passill�, J. Rushen, S.M. Godden, H. Chester-Jones, and M.I. Endres. Factors associated with dairy calf health in automated feeding systems in the Upper Midwest United States. J. Dairy Sci. 100:5675-5686
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Jorgensen, M.W., A. Adams-Progar, A.M.de Passill�, J. Rushen, J.A. Salfer, and M.I. Endres. 2017. Mortality and health treatment rates of dairy calves in automated milk feeding systems in the Upper Midwest of the United States. J. Dairy Sci. 100:9186-9193.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Jorgensen, M.W., K. Janni, A. Adams-Progar, H. Chester-Jones, J.A. Salfer, and M.I. Endres. 2017. Housing and management characteristics of calf automated feeding systems in the Upper Midwest of the United States. J. Dairy Sci. 100:9881-9891.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Salfer, J.A., K. Minegishi, W. Lazarus, E. Berning, and M.I. Endres. 2017. Finances and returns for robotic dairies. J. Dairy Sci. 100:7739-7749.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Evink, T. and M.I. Endres. 2017. Management, operational, animal health and economic characteristics of large dairy herds in 4 states in the Upper Midwest of the United States. J. Dairy Sci. 100:9466-9475.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2018 Citation: Pereira, Glenda; Heins, Bradley; Endres, Marcia. 2018. Technical Note: Validation of an ear-tag, accelerometer sensor to determine rumination, eating and activity behaviors of grazing dairy cattle. JDS: in press.
  • Type: Other Status: Published Year Published: 2017 Citation: Peiter, M, M. Jorgensen, and M. I. Endres. 2017. Daily milk consumption, number of visits, drinking speed and weight gain of preweaned calves in Midwest US farms with automated feeders. J. Dairy Sci.100 (Suppl. 2):137.
  • Type: Book Chapters Status: Published Year Published: 2017 Citation: Endres, M.I. and R.E. James. 2017. Facility systems for the young dairy calf: Implications for animal welfare and labor management. Pg 475-484 In: Large Dairy Herd Management, 3rd Ed, D. Beede, ed, American Dairy Science Association, Champaign, IL.
  • Type: Book Chapters Status: Published Year Published: 2017 Citation: Shearer, J.K., M.F. Hutjens, and M.I. Endres. 2017. Managing the herd to minimize lameness. Pg 1093-1102 In: Large Dairy Herd Management, 3rd Ed, D. Beede, ed, American Dairy Science Association, Champaign, IL.
  • Type: Other Status: Published Year Published: 2017 Citation: Pereira, G., B. Heins, and M. Endres. 2017. Validation of an accelerometer to monitor rumination, eating and activity in an organic grazing dairy herd. J. Dairy Sci.100 (Suppl. 2):355.
  • Type: Other Status: Published Year Published: 2017 Citation: Siewert, J.M., J. A. Salfer, and M.I. Endres. 2017. Daily milk production, number of milkings, feed consumption and rumination time for cows in robotic milking systems in the United States. J. Dairy Sci.100 (Suppl. 2):355
  • Type: Other Status: Published Year Published: 2017 Citation: Endres, M., M. Peiter, and M. Jorgensen. 2017. Feeding behavior of group-housed calves in Midwest US farms with automated feeders. In Proc. 51th Congress ISAE, Aarhus, Denmark, pg 68.
  • Type: Other Status: Published Year Published: 2017 Citation: Medrano-Galarza, C., S. J. LeBlanc, A. Jones-Bitton, T. J. DeVries, A. M. de Passill�, J. Rushen, M.I. Endres, and D.B. Haley. 2017. Associations of management practices and calf health on dairy farms using automated milk feeders in southern Ontario. J. Dairy Sci.100 (Suppl. 2):340
  • Type: Other Status: Published Year Published: 2017 Citation: Medrano-Galarza, C., S. J. LeBlanc, A. Jones-Bitton, T. J. DeVries, A. M. de Passill�, J. Rushen, M.I. Endres, and D.B. Haley. 2017. Which data recorded by automated calf feeders can help to detect sick calves? J. Dairy Sci.100 (Suppl. 2):137.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Endres, M.I. Automated calf feeder systems: What we learned from farms in the Upper Midwest USA. 2017. Pg. 55 in Proc. Conf. Precision Dairy Farming, Lexington, KY, May 30-June 1, 2017.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Endres, M.I. and J.A. Salfer. 2017. Feeding cows in a robotic milking system. Pg 61-67 In: Proc. Tri-State Dairy Nut. Conf., Fort Wayne, IN, April 2017.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Endres, Marcia and Lee Kloeckner. 2017. Feeding and management practices in top producing dairy herds in Minnesota. Pg. 138-142 In: Proc. Four-State Dairy Nutrition and Management Conf., Dubuque, IA, June 2017.
  • Type: Journal Articles Status: Accepted Year Published: 2018 Citation: Medrano-Galarza, C., S. J. LeBlanc, A. Jones-Bitton, T. J. DeVries, A. M. de Passill�, J. Rushen, M.I. Endres, and D.B. Haley. 2018. Associations between management practices and within-pen prevalence of calf diarrhea and respiratory disease on dairy farms using automated milk feeders.J. Dairy Sci: accepted.


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

Outputs
Target Audience:Dairy producers, dairy consultants, nutritionists, veterinarians, extension educators, researchers, students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Five graduate students were trained one-on-one with a mentor about dairy cattle production and welfare. How have the results been disseminated to communities of interest?Results have been disseminated through seminars, webinars, field days, websites, dairy trade publications, social meda. What do you plan to do during the next reporting period to accomplish the goals?Continue to analyse and summarize data collected during the project and not yet published.

Impacts
What was accomplished under these goals? The quick identification of animals at risk of becoming sick before their health disorder becomes more severe or they die could help improve animal welfare in dairy farms. When animals are housed in groups (the trend in the dairy industry), it is more difficult to monitor individual animals. The early identification of transition cows at risk, before they become severely ill, could reduce on-farm cow mortality and improve animal health with significant economic and animal welfare benefits to the dairy industry. A reduction in on-farm mortality from the current 6% to 3% would result in an estimated economic benefit of over $500 million to the US dairy industry. Better health is one aspect of good animal welfare and achieving it requires improving many aspects of the cow's environment and management. Improved animal welfare is something that the general public has increasingly greater interest. We are investigating how certain behaviors such as feeding or rumination time in adult cows, or visits to the feeder and drinking speed for calves, could potentially help identify animals at risk of becoming seriously ill. We found some promising results for transition cows and calves. Monitoring feeding behavior of cows during the 3 weeks immediately prior to calving helped identify animals that went on having two or more health disorders soon after calving. Farms that used drinking speed of preweaned calves as an alarm to identify sick animals, had lower mortality rates. We also validated an ear tag technology that monitors feeding, resting, rumination and activity behavior of cows used in a grazing system. Previous validations had been reported only for confinement systems. This accelerometer ear tag system accurately measured eating and rumination times, moderately measured resting time, and less accurately measured activity. It appeared that the activity behavior could have been affected by fly pressure on pasture. In our work with robotic milking systems, we are learning about the importance of milking speed and milk production per cow to achieve high daily milk production per robot unit, a clear measure of production efficiency in US dairy farms with robotic systems. Aspects of cow welfare, such as lameness prevalence, were evaluated and housing and management factors contributing to lameness were identified. Comfortable stalls with deep bedding, bedded packs and pasture-based systems appeared to be most cow-friendly.

Publications

  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Chebel, R.C., P.R.B. Silva, M.I. Endres, M.A. Ballou, and K.L. Luchterhand. 2016. Social stressors and their effects on immunity and health of periparturient dairy cows. J. Dairy Sci. 99:3217-3228.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Luchterhand, K.M., P.R.B. Silva, R.C. Chebel and M.I. Endres. 2016. Association between prepartum feeding behavior and periparturient health disorders in dairy cows. Front. Vet. Sci. 3:65.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Silva, P.R.B., K.M. Lobeck-Luchterhand, R.L.A Cerri, D.M. Haines, M.A. Ballou, M.I. Endres, and R.C. Chebel. 2016. Effects of prepartum stocking density on innate and adaptive leukocyte responses and serum and hair cortisol concentrations. Vet. Immun. Immunopath. 169:39-46.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Sjostrom, L.S, B.J. Heins, M.I. Endres, R.D. Moon and J.C. Paulson. 2016. Relationship of activity and rumination to abundance of pest flies among organically certified cows fed 3 levels of concentrate. J. Dairy Sci. 99:9942-9948.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Orman, A. and M.I. Endres. 2016. Use of thermal imaging for identification of foot lesions in dairy cattle. Acta Agric. Scandin. DOI:10.1080/09064702.2016.1179785.
  • Type: Journal Articles Status: Accepted Year Published: 2016 Citation: Salfer, J.A, K. Minegishi, W. Lazarus, E. Berning, M.I. Endres. 2017. Finances and returns for robotic dairies. J. Dairy Sci. (accepted)
  • Type: Journal Articles Status: Submitted Year Published: 2016 Citation: Pereira, G.M. B.J. Heins, and M.I. Endres. 2017. TECHNICAL NOTE: Validation of an accelerometer to monitor rumination, eating and activity in a grazing dairy herd. J. Dairy Sci. (submitted)
  • Type: Journal Articles Status: Under Review Year Published: 2016 Citation: Evink, T.L. and M.I. Endres. 2016. Management, economic, operational and animal welfare characteristics of large dairy operations in the Upper Midwest USA. J. Dairy Sci. (under review)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Shearer, J., M.F. Hutjens and M. Endres. 2016. Managing the herd to minimize lameness. Pg 104 in ADSA Large Dairy Herd Manag. Conf. Proc. Oak Brook, IL. Available from www.adsa.org/meetings/largedairyherdmanagement.aspx
  • Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Kloeckner, L. and M. I. Endres. 2016. Feeding management strategies on large and smaller freestall dairy herds in Minnesota. J. Dairy Sci. 99 (E-Suppl. 1):585.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Pereira, G.M., B. J. Heins, and M. I. Endres. 2016. Activity and rumination in an organic vs. a conventional grazing herd. J. Dairy Sci. 99 (E-Suppl. 1):608


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

Outputs
Target Audience:Dairy producers, dairy industry professionals, university researchers, extension educators, students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Two graduate students completed their degrees in 2015, four students are currently working on the project. PD Endres chaired the 2nd US Precision Dairy Conference and Expo in Rochester, MN which was an opportunity for dairy producers, dairy industry professionals, researchers, extension educators and students to learn more about dairy technologies. We worked together with the University of Kentucky where research in this topic is also being conducted. How have the results been disseminated to communities of interest?Project results were presented at JAM meetings in Orlando, International Society for Applied Ethology International meeting in Japan, various producer and industry conferences in the US, and conferences in Canada and Spain. One of the presentations included a new audience of electrical engineers who had not much experience with dairy farms. Presentation and dairy tour for members of Kiwanis Club. An article summarized some of the project results in an international publication entitled "'Innovations in Research' which aims to translate research into more accessible language. A TV program, called The Machinery Show, highlighted the study with robotic milking systems. What do you plan to do during the next reporting period to accomplish the goals?Continue to analyse data collected from 52 robotic dairy operations and prepare manuscripts, publish manuscripts on behavior of prepartum cows and large dairy case study, continue to collect and summarize on farm data from 80 plus randomly selected dairy farms in Minnesotaa and complete analysis for the study, start new study with transition dairy cows and use of sensor technology.

Impacts
What was accomplished under these goals? There has been a steady growth in the number of robotic milking dairy operations in the upper Midwest. This trend might help keep more dairy farms in business as the younger generation prefers technology and would come back to the farm, which will help improve the state's economy. Our project working with 52 robotic dairy operations has helped understand what are some of the important management factors that can influence productivity in these systems; preliminary analyses showed this includes cow milking speed, amount of concentrate fed daily, and exit length from the robot box. However, analysis is ongoing and use of multivariable mixed models will help better understand animal productivity and welfare in these systems. We are also investigating the use of another automated technology - calf feeders - and accomplishments of this work are reported under a NIFA-sponsored project (grant no. 2012-67021-19280). Another area of interest has been to investigate whether cow behaviors and activity such as feeding and resting time, rumination and social ranking during the prepartum and early postpartum period could be used to help producers identify cows at risk for health disorders. Another one of our studies confirmed that most cows die or leave the herd during the first 40 days after calving; therefore, identifying animals at risk earlier, before they become severely ill, could reduce on farm cow mortality and improve animal health with tremendous economic and animal welfare benefits to the dairy industry. We found so far that monitoring these behaviors in cows housed in freestalls has some potential and we plan to further investigate how to optimize this approach. In addition, we are using rumination and behavior sensors at our organic dairy site and correlating those behaviors collected with these precision dairy tools with health and reproduction in our herd. Another study showed that the welfare of dairy cows in very large dairy operations (average of approximately 5,000 cows per herd) is adequate (based on low prevalences of lameness and hock lesions, low somatic cell count and mastitis incidence, etc) and these dairies can dilute their cost of production per cow due to their economies of scale. They have specialized and efficient labor, averaging over 100 cows per FTE (full time employee equivalent). Another study was just initiated in 2015 to collect data from over 80 randomly selected dairy operations in Minnesota to learn more about feeding management and factors that are influencing economic efficiency in dairy farms while maintaining good cow comfort.

Publications

  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Liboreiro, D. N., K. S. Machado, P. Basso Silva, A. E. Barreto, M. I. Endres, and R. C. Chebel. Characterization of peripartum rumination and activity of cows diagnosed with metabolic and uterine diseases. J. Dairy Sci. 98:6812-6827.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Shahid, M.Q., J. K. Reneau, H. Chester-Jones, R. C. Chebel and M. I. Endres. 2015. Cow and herd level risk factors for on-farm mortality in Midwest US dairy herds. J. Dairy Sci. 98:4401-4414.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Lobeck-Luchterhand, K.M., P.R.B. Silva, R.C. Chebel, M.I. Endres. 2015. Effect of stocking density on social, feeding, and lying behavior of prepartum dairy animals. J. Dairy Sci. 98:240-249.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Endres, M.I. and J.A. Salfer. 2015. An evaluation of automated milking systems in the Midwest United States. J. Dairy Sci. 98, Suppl 2:114.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Chebel, R.C., P. R. B. Silva, K. Luchterhand and M. I. Endres. 2015. Social stressors and their effects on immunity and health of periparturient dairy cows. J. Dairy Sci. 98, Suppl 2:277.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Lobeck-Luchterhand, K.M., P.R. B. Silva, R.C. Chebel, and M. I. Endres. 2015. Association between social ranking and health of transition dairy cows. J. Dairy Sci. 98, Suppl 2:565.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Jorgensen, M., A.Adams Progar, K. Janni, H.Chester-Jones, J. Salfer, and M.Endres. 2015. Housing and management practices on farms using automated calf feeders in the Midwestern United States. J. Dairy Sci. 98, Suppl 2:818.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Jorgensen, M., A.Adams Progar, S.Godden, H.Chester-Jones, A. M. de Passill�, J.Rushen, and M.Endres. 2015. Risk factors for abnormal calf health scores on farms using automated feeders in the Midwest USA. J. Dairy Sci. 98, Suppl 2:819.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Endres, M., K. Lobeck-Luchterhand, P.B. Silva and R. Chebel. 2015. Is social rank associated with health of transition dairy cows? Proc. 49th Intern.Soc. Appl. Ethol.:88. Sapporo, Japan, September 2015.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2015 Citation: Endres, M. 2015. Automated calf feeders and robotic milking: What are keys to success? Proc. Precision Dairy Conf.: 126-132. Rochester, MN, June 2015.
  • Type: Journal Articles Status: Under Review Year Published: 2016 Citation: Orman, A. and M. Endres. Use of thermal imaging for identification of foot lesions in dairy cattle. Livest. Sci.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2016 Citation: Silva, P.R.B., K.M. Lobeck-Luchterhand, R.L.A. Cerri, D.M. Haines, M.A. Balloud, M.I. Endres, R.C. Chebel. Effects of prepartum stocking density on innate and adaptive leukocyte responses and serum and hair cortisol concentrations. Vet. Immunol. Immunopathol.
  • Type: Journal Articles Status: Published Year Published: 2015 Citation: Endres, M. 2015. Dairy welfare, management and behaviour. International Innovation 189:69-71.


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

Outputs
Target Audience: Dairy industry professionals, scientist, students, dairy producers Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Two graduate students completed their degrees in 2014. Various undergraduate students helped with data entry. How have the results been disseminated to communities of interest? Various presentations were given by the PI and her graduate students at national and international meetings, dairy industry conferences, workshops. What do you plan to do during the next reporting period to accomplish the goals? Continue to collect and summarize data for the project, write scientific manuscripts, present results at various conferences, train graduate students, teach undergraduate students.

Impacts
What was accomplished under these goals? Various studies are being conducted to achieve the goals of the project. Some completed study results were summarized and submitted to the Journal of Dairy Science and were published or are in review, other manuscripts are in preparation. Preliminary results were presented at various scientific and industry conferences. We have learned of better practices to improve dairy welfare on farms, increased our understanding of how automated systems are working at various sites, investigated the accuracy of using various behaviors and their monitoring devices to predict cows at risk for transition disorders, and continue to collect and analyse data to improve early detection of disease. We investigated factors that optimize productivity at large dairy operations and are developing economic models to aid decision making to improve animal welfare and productivity. Ongoing analysis is being conducted to investigate factors that optimize productivity in robotic milking systems.

Publications

  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Evink, T., and M. I. Endres. 2014. Mortality and herd turnover rates in large dairy herds in the upper Midwest United States. J. Dairy Sci. 97, E-Suppl. 1:735.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Endres, M., K. Lobeck-Luchterhand, P.B. Silva, R. Chebel. 2014. Can we use prepartum feeding behavior to identify dairy cows at risk for transition health disorders? Page 74 in Proc. 48th Congress of the International Society for Applied Ethology, Vitoria-Gasteiz, Spain, July 29 to Aug 2, 2014. Wageningen Academic Publ.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Liboreiro, D. N., K. S. Machado, M. I. Endres, and R. C. Chebel. 2014. Investigating the use of rumination sensors during the peripartum period in dairy cows. Pg 149 in Abst. 65th Annual Meeting of the European Federation of Animal Science, Copenhagen, Denmark, Aug 2014. Wageningen Acad. Publ.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Lobeck-Luchterhand, K.M., P.R.B. Silva, R.C. Chebel, M.I. Endres. 2015. Effect of stocking density on social, feeding, and lying behavior of prepartum dairy animals. J. Dairy Sci. doi:10.3168/jds.2014-8492
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Endres, M.I., K.M. Lobeck-Luchterhand, L.A. Espejo, C.B. Tucker. 2014. Evaluation of the sample needed to accurately estimate outcome-based measurements of dairy welfare on farm. J. Dairy Sci. 97:3523-3530.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Lobeck-Luchterhand, K.M., P.R.B. Silva, R.C. Chebel, M.I. Endres. 2014. Effect of prepartum grouping strategy on displacements from the feed bunk and feeding behavior of dairy cows. J. Dairy Sci. 97:2800-2807.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Silva, P.R.B., A.R. Dresch, K.S. Machado, J.G.N. Moraes, K. Lobeck-Luchterhand, T.K. Nishimura, M.A. Ferreira, M.I. Endres, R.C. Chebel. 2014. Prepartum stocking density: Effects on metabolic, health, reproductive, and productive responses. J. Dairy Sci. 97:5521-5532.
  • Type: Journal Articles Status: Under Review Year Published: 2015 Citation: Shahid, M.Q., J. K. Reneau, H. Chester-Jones, R. C. Chebel and M. I. Endres. Cow and herd level risk factors for on-farm mortality in Midwest US dairy herds. J. Dairy Sci. (in review, resubmitted)
  • Type: Journal Articles Status: Under Review Year Published: 2015 Citation: Liboreiro, D. N., K. S. Machado, P. Basso Silva, A. E. Barreto, M. I. Endres, and R. C. Chebel. Characterization of peripartum rumination and activity of cows diagnosed with metabolic and uterine diseases. J. Dairy Sci. (in review)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Jorgensen, M., A. Adams Progar, S. Godden, H. Chester-Jones, J. Rushen, A. M. de Passille, and M. I. Endres. 2014. Health of dairy calves when using automated feeders in the Midwest United States. J. Dairy Sci. 97, E-Suppl. 1:18.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Lobeck-Luchterhand, K., P. Basso Silva, R. C. Chebel, and M. I. Endres. 2014. Evaluation of prepartum lying behavior as an indicator of health disorders in transition dairy cows. J. Dairy Sci. 97, E-Suppl. 1:28.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Lobeck-Luchterhand, K., P. Basso Silva, R. C. Chebel, and M. I. Endres. 2014. Effect of stocking density on social and feeding behavior of prepartum dairy cows. J. Dairy Sci. 97, E-Suppl. 1:28.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Lobeck-Luchterhand, K., P. Basso Silva, R. C. Chebel, and M. I. Endres. 2014. Using prepartum feeding behavior to identify dairy cows at risk for transition health disorders. J. Dairy Sci. 97, E-Suppl. 1:28-29.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Sjostrom, L. S., B. J. Heins, M. I. Endres, R. D. Moon, and J. Paulson. 2014. Effect of organic grain supplementation on activity and rumination time of organic dairy cows. J. Dairy Sci. 97, E-Suppl. 1:281.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Sjostrom, L. S., B. J. Heins, M. I. Endres, R. D. Moon, and U. S. Sorge. 2014. Effect of two winter housing systems on production, body weight, somatic cell count, BCS, and dry matter intake of organic dairy cows. J. Dairy Sci. 97, E-Suppl. 1:295.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Liboreiro, D. N., K. S. Machado, P. Basso Silva, M. M. Filho, G. Franco, A. E. Barreto, M. I. Endres, and R. C. Chebel. 2014. Use of peripartum period cud chewing and activity data for diagnosis of health disorders. J. Dairy Sci. 97, E-Suppl. 1:400.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2014 Citation: Liboreiro, D. N., K. S. Machado, P. Basso Silva, M. M. Filho, G. Franco, A. E. Barreto,M. I. Endres, and R. C. Chebel. 2014. Association among peripartum health parameters, cud chewing, and activity. J. Dairy Sci. 97, E-Suppl. 1:412.