-
-
-
Feb 04 2019
-
-
Leveraging Big Data in Agriculture
Authors: Sr. Director of Agribusiness Banking, Stacey Cole
It may seem counterintuitive, but agribusinesses are among the most sophisticated users of data and analytics. Agribusinesses spin out a myriad of data but oftentimes, that data lives in silos. However, the next generation of agtech is stitching together data using new technology solutions to create an unprecedented view of ag operations. Data-driven insights are bringing new efficiencies and reducing risk in what has traditionally been a cyclical, unpredictable industry.
Where Is the Data Coming From?
Historically, producers have relied on industry research and information from third parties to inform their decisions. Today, however, information technology is interwoven throughout their daily operations, allowing agribusinesses to generate a vast trove of specific, valuable data.
This agricultural data comes from a wide array of sources. Here are just a few examples:
- Sensors—on fields and crops to provide data on soil conditions, wind, fertilizer requirements, water availability, and pest infestations; on plants to monitor for nutrients and growth rates; and on livestock and machinery
- Connected/"smart" devices
- Drones to patrol fields and send alerts about crop and livestock conditions
- Satellite imagery
- GPS units on machinery to help producers optimize the use of heavy equipment
- RFID-based traceability systems that provide continuous data on products as they move through the supply chain
Big Data is Big Business
Until recently, much of this ag data existed only in silos. Then technology companies took note of the vast potential of big data in agribusiness, and venture capital began to flow. Investment in “ag tech” has grown by 80 percent annually since 2012, Boston Consulting Group reported in 2016.
The ag tech boom has resulted in innovative applications that make sense of the data that agribusinesses gather. These solutions—which can be used by operations of all sizes—feature better, more intuitive user interfaces built onto meaningful data aggregation and insights. Many of these solutions collect and analyze data—such as weather data and aerial imagery—in real time, so agribusinesses can make quick, targeted decisions based on the newest information possible.
How is the Data Used?
All of this data is being combined and crunched to enable “precision agriculture,” a technology-driven approach to farming management based on observing, measuring and responding to the needs of individual fields, crops and livestock. This approach increases production, improves safety and economic efficiency and minimizes waste and environmental impact. Models can be used to predict yield, improve feed efficiency for livestock, mitigate risk, track food from “farm to table,” manage equipment and operations, and ensure food safety and prevent spoilage, among other applications. Instead of watering an entire field, for example, farmers can water only the areas that need it most, thereby preserving resources and reaping better results. Farmers can even customize individual fields to meet the demands of a specific region or consumer group.
Of all these applications, using big data to manage risk in a cyclical industry like ag could be the most significant. In just one example, big data can now be used to measure the effects of weather forecasts and the chances of crop failure. In 2014, advice from data scientists to Colombian rice farmers was said to have saved millions in damages caused by shifting weather patterns. More generally, agribusinesses can use big data to solidify the processes and practices they use every day, improving efficiency, performance and the bottom line.
Agriculture of the Future
Big data will play an ever-growing role in the future of agriculture and could even help alleviate world hunger. By enabling producers to manage water more effectively and apply more customized care, big data may boost production and thus augment the global food supply. Applications that reduce food waste could help cut postharvest losses by as much as 50 percent, which would produce enough food to feed a billion more people, according to a report by McKinsey & Company. Big data can greatly expedite plant breeding programs, too—reducing processes that once took months or even years to mere days.
Big data is shaping today’s farm-to-table movement as well. Consumers are increasingly interested in knowing where their food came from and how it was grown or raised. RFID-based traceability systems and sensors on food, for instance, can literally track it from farm to table. Blockchain technology is particularly useful here; as Forbes.com notes, blockchain applications can document “all of the B2B relationships that lead up to the final B2C transaction. Consumers can see exactly when their food was grown, what sorts of pesticides and antibiotics were used, and how it compares to other products on the shelves.”
Given the vast power of big data and its innumerable applications, today’s producers should seek access to as much data as possible. Agricultural operations of all sizes are generating big data, whether they know it or not. Agribusinesses must thus look for applications that can break down the silos between data sources and generate meaningful insights. Those who manage to transform this data into useable information that enables better decisions will be the winners in a dynamic, vital industry,
First National Bank is proud to have served agribusiness since 1857. Our knowledge and experience allows us to offer innovative agribusiness and finance solutions, whether your business is beef, pork, grain, ag-supply, processing or any other facet of the industry.
About the Author
Stacey Cole has worked at First National Bank of Omaha since 2006. She grew up on a diversified family agricultural operation in northeast Nebraska. After graduating from Creighton University with her MBA, she joined the Executive Development Program at the bank. Stacey then returned to her agricultural roots by joining the First National Bank of Omaha’s Agribusiness Banking team, where she works with ag producers in cattle, swine, grain, feed, food processing and agribusiness sectors.
The articles in this blog are for informational purposes only and not intended to provide specific advice or recommendations. When making decisions about your financial situation, consult a financial professional for advice. Articles are not regularly updated, and information may become outdated.