An iPad based in the cab of Brian Marshall’s tractor and synced to the planter allows him to perform real-time field mapping and data visualization.
Some farmers are using the technology to evaluate hybrid performance; others are taking a wait-and-see approach
On a balmy May afternoon, Brian Marshall is in the height of corn planting. The smells of freshly turned dirt and diesel fuel hang in the air as the 37-year-old farmer drives his 16-row planter across a 60-acre, river-bottom field. From his tractor seat, Marshall eyes two precision technology monitors and an iPad synced to the planter. The monitors help guide his planting speed, seeding population and seed spacing, while the iPad allows him to perform real-time, in-the-field mapping and data visualization.
In the 12 years since returning to the family farm near Maysville, Mo., harnessing hybrid performance data has improved Marshall’s corn yield average by 8%.
"One year I noticed a 22% difference between two hybrids planted next to each other in the same field," says Marshall, who manages 4,600 acres of crops with the help of his father, Dennis, and two full-time employees. "That’s an extreme example that doesn’t happen very often, but I think it illustrates what our industry can do with technology now."
To understand the phenomenon of big data, it is often described using four Vs. Value is arguably the most important because big data is useless unless there’s a return on investment.
While Marshall gathers and evaluates his operation’s data on his own, he sees the opportunity to benefit from using multi-farm data aggregation, often referred to as big data. Large ag companies such as DuPont, John Deere, Monsanto and Winfield, as well as many small niche companies, are helping farmers glean information from big data to make seed selections, plan fertility programs and, in the process, reduce or refocus their input costs.
The big deal. The use of big data for such purposes poses a tremendous boon for the ag industry as it races to produce more food for a world population projected to reach 9 billion by 2050. At the same time, big data is big business. Some industry consultants project the ag sector will soon see total revenues of $20 billion or more annually from big data services. The huge value proposition is a lure for well-meaning individuals and corporations—as well as those less scrupulous. Concerns about the latter and various other risks are contributing to the decision made by farmers such as Marshall to keep their data to themselves, for now.
"I want to know there’s no opportunity for anyone to take my data and do something else with it," Marshall says. "That’s my sticking point."
Such concerns are sticking points for other U.S. farmers as well. A Farm Journal survey of 628 farmers conducted earlier this summer shows while 91.5% collect data from their operations, only 49.6% share their information with any individual or firm specializing in data aggregation management and analysis. Along with that, citing privacy concerns, 71% of the farmers surveyed do not use the "cloud" to store and access their data.
Chris Fennig, managing director of MyFarms LLC, says the business of big data has been poorly implemented in other industries. He believes agriculture has the opportunity to "do big data right," and make it a win-win proposition for farmers and service providers.
"The last thing I want to do is build so much concern around sharing data that no one is willing to share it," he says. "But it must be mutually beneficial—good for the farmer and good for his trusted advisers who are looking to help the farmer get better."
How did we get here? There has been a logical progression to the development of big data, though it is easy to miss or overlook. People have long-gathered information, analyzed it and made decisions based on it, but the amount of data created has skyrocketed in recent years. IBM estimates that 2.5 quintillion (a one followed by 18 zeroes) bytes of data are created every day, and 90% of the data in the world is less than two years old. Such huge amounts of data being generated require the use of multiple computer processors to help people sort and evaluate the information for decision-making purposes.
|Source: Farm Journal Pulse
A similar scenario is shaping up in agriculture. The majority of producers, some unknowingly, produce a variety of data on their farms via various sensors and modems on their tractors, combines and other equipment. However, few farmers have tapped into the potential that big data offers for decision making, a challenge Monsanto identified early on and developed its new FieldScripts program to address. The program, formally introduced this year in Illinois, Indiana, Iowa and Minnesota, delivers DeKalb-specific hybrid matches and variable-rate planting prescriptions to customers. The prescriptions are based on fertility data and two to three years of yield history in a given field. Company officials say use of the prescriptions can help farmers produce an additional 5 bu. to 10 bu. of corn per acre.
DuPont Pioneer also promises significant production, sustainability and financial rewards with its Encirca program, introduced to farmers this past spring. The brand-neutral suite of whole-farm decision services is designed to help farmers enhance yield results by fine-tuning their seeding rates and fertility programs.
"When all of the components are working together, we believe there’s between $50 and $100 per acre ROI [return on investment] to the farmer," explains Joe Foresman, director of services for DuPont Pioneer.
While companies tout the potential payoffs from their respective programs, farmers don’t always see a consistent ROI from implementing them. Steve Pitstick, a long-time user of precision technology on his 2,600-acre corn and soybean farm near Dekalb, Ill., and a beta tester of FieldScripts, says he believes above-average growing conditions in 2013 cancelled out potential yield gains the prescribed recommendation might have contributed. Yet, he believes prescriptive technology has merit. He anticipates as the various programs are refined to evaluate more agronomic factors that impact yield, such as weather conditions, crop residue and tillage, farmers will benefit financially more often.
Glossary of Terms
If the language surrounding the topic of big data is foreign to you, take heart. You can master the basic lingo in no time, which will come in handy as you talk with technology advisers and read their terms-of-service contracts. Here are definitions of 10 key terms, some of which Farm Journal has modified to better fit the agricultural industry and its usage of big data, specifically.
Algorithm: Step-by-step instructions that allow computers to perform various tasks, such as sorting data or identifying records.
- Seed Guide 2014
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