Next up ROBOTS

Mar 1, 2007 12:00 PM, By Jodie Wehrspann

Ag technology is becoming more seamless. According to Jess Lowenberg-DeBoer, agricultural economist at Purdue, in order for any ag technology to be economically viable, and in turn become widely adopted, it must be easy to use. In technical terms, it must move from being an “information-intensive technology” to an “embodied-knowledge technology.”

“So what do I mean by information-intensive technology?” says Lowenberg-DeBoer, who has studied the economics of precision farming for 22 years. “I mean that using field-level data to make decisions typically requires you to collect data, analyze it, and put it back in a format that is usable.” Examples of this kind of technology include variable-rate technology (VRT) and Integrated Pest Management. He says technologies like these have high associated costs and relatively slow adoption rates.

Embodied-knowledge technology, in contrast, is purchased in the form of an input and can be used with little or no knowledge or effort. In other words, you don't need to know much about the technology in order to benefit from it. Examples of it are widespread.

“Most of the ag technology of the 20th century was embodied technology,” Lowenberg-DeBoer says. “Examples include hybrid seed, chemical weed control and mechanization. All of those are classic embodied technologies, and they have been very productive.”

Lowenberg-DeBoer says embodied-knowledge technology is the most economically efficient solution for using scientific knowledge to solve agricultural problems because it compensates for skilled labor. “People with the skills to interpret precision ag data and implement the spatial management plans are expensive and hard to find,” he says. “And most farmers did not become farmers because they wanted to sit behind a computer and analyze data. Most became farmers at least in part because they valued an outdoor, active lifestyle. If it is profitable enough, they will spend time crunching numbers, but most would prefer not to.”

Three waves

Lowenberg-DeBoer says precision farming is already in the process of becoming embodied-knowledge technology. And it is happening in three waves.

The first precision agricultural technology to be designed and commercialized as embodied-knowledge technology was vehicle-based nitrogen (N) sensing developed in the 1990s. Examples include GreenSeeker, Norsk Hydro (Yara) N sensor, and Crop Circle. These products measure the greenness of leaves, which relates to the amount of nitrogen in a corn plant, and then vary the rate of N on the go when used with variable-rate application equipment.

The second wave was GPS-enabled vehicle guidance technology that assists with steering. He says this technology is well on its way to becoming standard. “The real technology success story of the last decade is guidance,” he says. According to Purdue surveys with custom applicators, use of GPS lightbars grew from 5% in 1999 to 57% in 2006 nationally, and up to 77% in the Midwest. During the same time frame, use of GPS auto-guidance systems, where the equipment takes over steering, grew from 6 to 20%.

“We've also seen great interest among farmers, although we don't have the numbers,” he says. “Low-cost assisted steering systems that sell for around $5,000 are popular even among those you'd never expect to be interested in higher tech. Included in that group are older farmers with back or shoulder problems who say that assisted steering systems are allowing them to stay in farming a few more years.”

Robots are next

Lowenberg-DeBoer believes the third wave of embodied-knowledge technology will be robotics. “Twenty years ago few people would have imagined the current market for GPS guidance,” he says. “If you would have told U.S. farmers that there would be equipment to take over steering of the tractor or combine, most would have said, ‘What do I need that for? I can steer. And I can do a good job at it.’ But the market has seen tremendous growth, and farmers are finding uses for it. I think we may see the same thing with robotics.”

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