[AISWorld] AMCIS-2018 Call for Papers

[Michael Chilton]

CALL FOR PAPERS

AMCIS 2018

New Orleans, Louisiana, USA

August 16-18, 2018

Mini-track: Computers in the Business & Production of Agriculture

Track: Advances in Information Systems Research (General Track)
Introducing a new mini-track to the America's Conference of Information Systems (AMCIS).  For the first time, we solicit papers dealing with computers in agriculture.  Our discipline is largely ignoring innovation, development and use of agricultural data, but the opportunities are there and the need to explore them exists.  Farmers are now using technology to collect and analyze huge amounts of data to help make decisions and manage their production.  This has been labeled "smart farming" and "precision agriculture."
MINITRACK BACKGROUND & DESCRIPTION
The world's food supply needs to keep up with population growth.  It needs to become more efficient to account for such inhibitors as climate changes, land degradation, water contamination and even dietary preferences.  Improving agricultural productivity is therefore a global challenge.  To meet this challenge, technology is being utilized in much the same way as in other disciplines, such as finance and economics, health care, construction and manufacturing.  Farmers are collecting huge amounts of data for analysis, are employing networks of sensors and utilizing data storage solutions in the "cloud."  This mini-track seeks papers from researchers engaged in cross disciplinary work that is investigating, employing and/or developing technological solutions to the agricultural problems of the day.
Research of this type falls into the two broad categories that make up our food supply-animals and plants.  We list below some examples of how and where technology is being used in agriculture.

  1.  Animals

a.       Animal health.  By digitizing animal movement, activity and behavior, it is now possible to accurately assess the health of animals.  Animals can't tell us how they feel, but a trained Veterinarian can determine an animal's health by observing its behavior.  Systems used on feed stock are now able to predict health outcomes up to 3 days before a trained observer will notice symptoms (cf. e.g., White, et al., 2016).  These systems also reduce the amount of vaccine use, an important achievement as consumers are becoming more demanding of meat produced without drug interventions.  With 95 million cattle on feed in the United States alone, and with disease prevalence as high as 17%, health monitoring systems could provide transformative benefits to the cattle industry.

b.       Animal feed efficiency.  Technology makes it possible to calculate an animal's efficiency by measuring its daily consumption and its growth rate.  Two animals may experience similar growth rates, but if one requires less feed to maturity, it is more efficient and less costly than the other.  In a commodities market, the rancher has no control over demand and prices, but given more efficient animals, he can better control his costs.  Research is needed that can provide precise pecuniary benefits of feed efficiency.

  1.  Plants

a.       Use of drones (precision agriculture).  Drones are now used to survey fields and determine such things as soil moisture content, fertility, weed infestation and plant/tree health.  Depending upon the payload, a farmer can view and analyze spectral graphs of his fields and use the data to cover the field more efficiently with water and/or fertilizer.

b.       Geographic Positioning Systems (GPS).  It is now no longer necessary for a farmer to manually drive a tractor through a field.  The tractor and its functions can be programmed and allowed to follow a pre-determined path based on its GPS position, while its payload (fertilizer) is applied in precise amounts based on soil analysis.
These areas raise lots of exciting research possibilities and are some that MIS researchers need to explore.  It represents the human food supply, which is a necessary component for health and population growth, especially as the population of the Earth grows and may exceed our ability to feed everyone.  If you are working with other researchers in animal science, veterinary medicine, agronomy, grain science or any related field in agriculture, you might like to submit your work to this mini-track.  We are especially interested in topics that explore business models relying on the analysis of agricultural data.  Some potential research topics might include:

  1.  Design science: identification of applications in agriculture to help improve efficiency. This could produce theories that guide the design of these applications.
  2.  Analyzing animal health using automated techniques that record animal behavior and movement.
  3.  Measurement of residual feed intake (RFI) and other indexes of animal feed efficiency.
  4.  The business of precision agriculture-monitoring crop producing fields for insects, disease, fertility, moisture and their effects on production.
  5.  How efficiency in food production (animal or plant) is affected by precision agriculture.
These topics are timely and important.  The business of agriculture is huge, and it affects everyone.  We need to find new techniques and applications to assist farmers and ranchers as they supply food to the world.  We need to develop theories that guide the design, implementation and deployment of automated techniques in the production of agriculture.
Please visit the AMCIS-2018 web site for more information: https://amcis2018.aisnet.org/submissions/track-descriptions/#toggle-id-3
References
White, B. J., Amrine, D. E. & Goehl, D. R. (2015).  Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations.  Journal of Animal Science, 93(8), pp. 4115-4122.

White, B. J., Goehl, D. R. & Amrine, D. E. (2015). Comparison of Remote Early Disease Identification (REDI) system to visual observations to identify cattle with bovine respiratory disease.  International Journal of Applied Research in Veterinary Medicine, 13(1), pp. 23-30.

Zhang, C. & Kovacs, J. M. (2012).  The application of small unmanned aerial systems for precision agriculture: a review.  Precision Agriculture, 13(6), pp. 693-712.

Zhang, C., Walters, D. & Kovacs, J. M. (2014).  Applications of low altitude remote sensing in agriculture upon farmers' requests-A case study in northeastern Ontario, Canada.  PLOS ONE, https://doi.org/10.1371/journal.pone.0112894