Tuesday Talks with Dr. Patterson
April 21, 2015
Big Data and Agriculture
Some market observers have described the potential presented by big data in agriculture as transformative as the green revolution or modern plant breeding. However, the concept of big data, as it is applied to agriculture, is not broadly understood. Furthermore, as promising as it is to agriculture, it faces numerous challenges.
Precision agriculture allowed producers to move from managing their crop operations at the field level to much smaller areas defined by the square meter or even smaller areas. Using field mapping technologies and sensors and data collection devices integrated into tractors, implements, and other equipment, farmers can tailor the use of inputs (seeds, fertilizers, pesticides, and water) according to plant and soil conditions measured at this much smaller scale. Farm-level, computer-based decision tools were developed to enhance these operations. Precision agriculture has resulted in improved utilization of resources, increased profitability, and improved environmental conditions. As precision agriculture operations progressed, the data collected through these operations were stored and accumulated at the farm-level. Big data refers to opportunities to take these farm level data, combine them with other data sources, notably geospatially referenced data, such as weather data, to develop new management recommendations using advanced analytical software and decision tools. Notably, big data will exploit the opportunities that arise from collecting and aggregating data across multiple farm operations in a region. This data collection process is facilitated by wireless and broadband internet services. (Whitacre, Mark, and Griffen)
The aggregation of data from farmers and other data sources, along with the development of new analytical tools, has created an entire new industry or product market sector in agriculture being served by so-called agricultural technology providers (ATPs). John Deere is a leader in this product category as might be expected given that its equipment products contain the sensors and data collection devices. Monsanto entered this product category with the purchase of the San Francisco-based technology firm Climate Corp. DuPont Pioneer and regional farm supply retailers have also entered this product market category. While data collection and aggregation, combined with analytical tools, creates opportunities for better management decisions and increased profits, it also raises concerns among producers.
Farmers are worried about maintaining control over the data collected from their farms, which they consider as private information, by ATPs and with whom these data are shared. For example, some farmers have expressed concern that data on their farm operations, if viewed by government agencies, could result in increased regulatory oversight. This has led a group of ATPs and farm organizations to develop an agreement in November 2014 on data privacy principles for the use of farm data. The central tenant of this agreement is that farmers maintain control over the use of their data (Gonzalez).
Data privacy is just one of the challenges facing this new product sector. Other challenges include the growth and development of high speed internet services in rural areas to facilitate the movement of data and deployment of new decision tools and products. Currently, the USDA is making loans and grants available to telecommunications firms in rural areas to expand broadband internet access. Since 2009, $5.88 billion in loans and grants have been made available in this effort (Forman-Cook). Other challenges include making data collected by various devices from different equipment dealers compatible and developing user friendly decision tools that fully exploit the available information. Producer adoption of these new technologies will also be a challenge, particularly since the average age of farmers exceeds 65 in many areas.
While concerns over data privacy are valid, it is the aggregation of data from many farm operations that creates some of the greatest opportunity to enhance profits and provide valuable information. Indeed, this is a good example of the economic concept of a network externality. As ATPs are able to aggregate data from multiple farm operations in a region, along with other environmental data, the value of the information increases. ATPs will be able to develop a more complete picture of growing conditions, input usage, and production levels the more participants it has in its network of cooperating growers. This improved information should benefit producers, leading to increased productivity and better resource allocation. Which ATP has the most comprehensive network will affect the quality of the information. Indeed, developing this network is the space in which ATPs and perhaps much of agriculture will compete in the future. Achieving the goal of developing a comprehensive network with enhanced information services for producers, while protecting the privacy of producers is considerable challenge involving technology and social concerns.
Forman-Cook, W. “Administration Takes Steps to Advance Rural Broadband Service.” Agri-Pulse, March 23, 2015. (Accessed April 20, 2015): http://www.agri-pulse.com/Administration-takes-steps-to-advance-rural-broadband-service-03232015.asp
Gonzalez, S. “Ag Companies, USDA, Discuss Big Data Challeges.” Agri-Pulse, February 19, 2015. (Accessed April 20, 2015): http://agri-pulse.com/Ag-companies-USDA-discuss-big-data-challenges-02192015.asp
Whitacre, B.E., T.B. Mark, and T.W. Griffen. “How Connected are Our Farms?” Choices, 3rd Quarter 2014. (Accessed April 20, 2014): http://www.choicesmagazine.org/choices-magazine/submitted-articles/how-connected-are-our-farms
Dr. Paul Patterson is Associate Dean for Instruction for the College of Agriculture and Professor of Agricultural Economics.