The evolution of digital agriculture and considerations today

A farmer commented to me the other day when talking about data that the industry “really needs to be able to exchange data across platforms.” This comment was associated with other comments about how farmers are looking for help in understanding the benefits data can bring to their business but also how data services and portability of data need to be simplified. We also discussed how data are being generated on a variety of machinery but likely not all with the same brand. Our discussion ended with his belief that data could bring additional information back to his farm and in particular to be able to benchmark facets of his operation with others. However, proof and clarity to what data services actually deliver were needed.

Big data?

Big data continues to be a hot discussion topic within the agricultural community. New technology and services are continuing to come online to help farmers. In the past two years, the advancement of wireless technology and telematics solutions have simplified the transmission of data between agricultural machinery, but more importantly allowing data to be stored online and in a location making them more accessible so farmers can take advantage of service offerings. With companies rolling out a variety of data-based services, it can be hard to understand and realize where the benefit exists. Opportunities around “big data” do exist for farmers as proven in other industries like the medical field and retail sector. One thing to understand is that actual big data capabilities are very limited today in agriculture but elements of big data continue to be developed. The term gets misused frequently and really represents a buzz word in the agricultural sector.

Wikipedia defines “big data” as “an all-encompassing term for any collection of data sets so large or complex that it becomes difficult to process them using traditional data processing applications.” I would add that the term data aggregation applies as well, falling under the term complex in this definition since the data and their format comes from as assortment of technologies. Aggregation refers to the compiling of data layers not only from an individual farm but farms across a regional or nationally that in return can be analyzed to generate a whole new of level of information and insights to help advance production agriculture.

When we consider the need to accelerate understanding of how corn hybrids perform under a range of varying growing conditions and management practices, big data could provide much deeper information from adding farm based data to a seed company’s trials. Think about capturing rainfall data and other growing condition factors that we have access to today. The analysis and ability to understand hybrid responses requires large amounts of data about growing conditions and practices used to grow the crop. It is the existence of big data that can accelerate our learning over time and bring benefits to the entire agricultural sector; especially individual farmers. Big data can help ensure individual farmers are practicing sound agronomy but also be able to verify sustainability and environmental stewardship.

Digital agriculture

A recent report published by the Iowa AgState group about the ag data space highlighted aspects of where we are today related to data and their integration into agriculture. The term “digital agriculture” was an encompassing term presented describing the ability to fully utilize technology and data thereby enhancing farm profitability, yields, and sustainability.

The report listed that several key areas fall under digital agriculture, and includes precision agriculture, prescriptive agriculture, enterprise agriculture, and big data. This framework suggests that agriculture has moved beyond just technology and basic prescription map generation and has matured to a point where we are starting to be able to take advantage of all those years of data collection while having the capabilities to bring multiple data layers together for a much deeper analyses.

As an industry, precision agriculture is well developed, providing technology that has outpaced our agronomic and economic complete understanding of its value within farming systems. Technology that provides savings but yield gains and input efficiencies are at times not well documented. Prescriptive agriculture reflects new growth across the industry with several companies providing multi-layered analysis capabilities to generate prescription maps for various inputs. Growth in prescriptive agriculture has been exponential recently. There are a few examples of enterprise agriculture offerings — mostly focused on large farms. Big data has not been realized in agriculture today while several companies developed pieces for those capabilities. So enterprise agriculture and big data are at very early stages. You can use digital agriculture as the blanket direction agriculture is heading with placing company offerings for data under one of the four terms.

While data are a central component to digital agriculture, today privacy and security around data are at the forefront of farmers’ concerns. Data can be used to better understand agronomic and economic decisions at the farm and will continue to help as the various facets of digital agriculture grow — the more information available, the less risk and improved decision making. This benefit has been proven in published research over the years along with case studies reported in popular press.

Quality data

However, information derived from data is only as good as the data itself. An important aspect generally overlooked and not discussed enough is data quality. Quality data must be a focus as digital agriculture grows. Assuming that yield data downloaded from a yield monitor is correct or without error can be misleading at times. Errors can be present within different data layers so proper setup, calibration and operation of machinery and technology is ever important to ensure that the best quality data are generated.

Work at Ohio State is helping to develop new procedures and advance technologies to generate more consistent and accurate data generated on agricultural machinery. This type of research in conjunction with industry efforts will help ensure checks and balances exists for technologies generating data. There is also a need to improve the resolution of yield maps to truly reflect the variability across fields that has been lost with the increased size of today’s combines and headers. In the meantime, take the time to follow manufacturer guidelines for setup, calibration and maintenance of the technology.

Considerations around data

As you visit with your trusted data consultant or consider many of the services being offered that require precision ag data layers from your farm, here are a few things to think about:

  • Take time to establish naming conventions for grower, farms, and fields, ensuring they are consistent across technology platforms,
  • Discuss what the data service being offered provides and how it aligns with your needs,
  • Understand terms and conditions of a company’s data policy,
  • Ask about security measures around storing data,
  • Ask about the portability of your data if you choose to work with a different company’s data service (can you easily transfer all your data?),
  • Understand how data are transferred between online platforms and who has access to data,
  • Focus on data quality by following calibration and setup procedures while taking good notes about field conditions when collecting data, and
  • Maintain a backup of your raw data and keep them in a secure location. I recommended having an annual backup file for all raw data.

Upcoming events

There are two upcoming opportunities for farmers, consultants and others working with data services in agriculture to learn about current trends within the industry and the value data could bring to the farm. I would encourage those wanting to be engaged and understanding the current state of the data space to attend one of these day-long sessions. These are good opportunities to hear from experts but also to network with others.

1)    PrecisionAg Data Workshops: Leverage big data to its fullest potential, February 16, 2015 at the Crowne Plaza Columbus North-Worthington, Columbus, Ohio. More information is at www.precisionag.com.

2)    Conservation Tillage and Technology Conference, Ada, Ohio. On March 4th there will be “Big Data” session. More information is available at ctc.osu.edu .

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One comment

  1. I didn’t know that precision agriculture is included in digital agriculture. I think a lot of farmers don’t know this. They may know about precision agriculture but not know a lot about digital agriculture.

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