**6. Future Developments: Keep Up with Technology and Needs**

A number of emerging and evolving technologies are today available to dairy farmers more than ever. These include the use of smart phones, tablets and similar hardware devices; more efficient software resources; and improved data networks. There is no doubt the trend of fast technological improvement in the area of computer, software, and gadget develop‐ ment will continue even at a faster pace. Progressive farmers and an increasing proportion of Extension agents and dairy farm consultants are already using these technologies. New technologies bring challenges to keep information systems up-to-date, but at the same time bring great opportunities for improved DSS development.

One important advantage of smart phones and tablets is their portability along with connec‐ tivity. Nowadays farmers enjoy voice and, importantly, data network and therefore the ca‐ pability to save and retrieve data eventually from anywhere at anytime. For example, a farmer can have complete information of a cow (e.g., age, lactation, pregnancy status, pro‐ duction history, today's production, genetic background, health incidence, etc.) at the time the cow is being registered through a smart phone system whether the cow is in a corral, in the milking parlor, or out in the field grazing. This gives the farmer the opportunity to make critic a land time-sensitive decisions right away. This could be one of the major benefits of smart phones and tablets applications. Decision support systems have to be integrated with these new technologies and need to take advantage of these important advantages.

C, CSS, MySQL, Spreadsheet applications, and executable programs. The DSS have pro‐ ven to be effective decision-making tools for improved dairy farming operation. Large dissemination and impact of these DSS tools can be verified by having 9,336 downloads of these DSS tools during the one-year period between May 2011 and April 2012 and the request of 168 talks with 6,500 people in attendance across the world during the 4-year

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The development and maintenance of the DairyMGT.info tools has been possible by the partial support of several extra-mural grants: Agriculture and Food Research Initiative from the US‐ DA National Institute of Food and Agriculture Competitive Grants No.: 2010-51300-20534, 2010-85122-20612, 2011-68004-30340 and several Hatch grants to V.E.C from the College of Ag‐ riculture and Life Sciences at the University of Wisconsin-Madison. Acknowledgement is ex‐ tended to a number of people involved at different levels in the development of these tools; Collaborators: B.W. Gould, R.D. Shaver, M.A. Wattiaux, L. Armentano, J. Vanderlin, K. Bolton; Students: J.O. Giordano, J. Janowski, M. Valvekar, E. Demarchi, A. Kalantari; Programmers: A.

[1] Rotz, Corson., Chianese, Montes. F., Hafner, S. D., & Coiner, C. U. (2011). The Inte‐ grated Farm System Model: Reference Manual Version 3.5. USDA Agricultural Re‐ search Service. http://www.ars.usda.gov/SP2UserFiles/Place/19020000/

[2] Cabrera, V. E., Hildebrand, P. E., Jones, J. W., Letson, D., & de Vries, A. (2006). An Integrated North Florida Dairy Farm Model to Reduce Environmental Impacts under Seasonal Climate Variability. *Agriculture Ecosystems & Environment*, 113, 82-97.

[3] Groenendaal, H., Galligan, D. T., & Mulder, H. A. (2004). An Economic Spreadsheet Model to Determine Optimal Breeding and Replacement Decisions for Dairy Cattle.

period between May 2008 and April 2012.

Kalantari, N. Suryanarayana, K. Nathella, V. Vats, A. Gola.

Address all correspondence to: vcabrera@wisc.edu

ifsmreference.pdf (accessed 5 May 2012).

*Journal of Dairy Science*, 87, 2146-2157.

Department of Dairy Science, University of Wisconsin-Madison, U.S.A.

**Acknowledgements**

**Author details**

Victor E. Cabrera\*

**References**

One drawback, however, of smart phones and tablet applications is their restricted screen size and some hardware and software limitations. Applications need to be especially designed for smart phones and tablets. Normally, the information entered and retrieved would need to be summarized or would require additional layers of navigation. Extra design details could, though, lead to more compact, more intuitive, and overall more efficient DSS.

There is a trade-off of functionality and payback. The industry seems to favor both types: application for conventional computers and laptops in addition to those applications for smart phones and tablets. The decision-maker selects what type of tool to use for a particu‐ lar situation. From the developmental standpoint, this is an additional challenge that re‐ quires additional work and expertise.

Important considerations regarding upcoming and developmental technologies are the in‐ creasing need for integration of DSS with information systems currently used in a farm. Most of the farmers are already using some type of software or information systems for op‐ erational management such as feeding, general record keeping, reproductive synchroniza‐ tion programs, identification, heat devices, or others. The DSS portrayed in this chapter and similar have the opportunity of becoming a bridge among these information systems. Deci‐ sion support systems can use live information from farm records and provide predictions that go beyond the simple record keeping summaries. Farmer expertise combined with realtime DSS projections using farm record keeping systems is a powerful combination for effi‐ cient and effective decision-making in dairy farm management.
