Applications: High-Tech Harvest

Small farms have recently found that high-tech tools can improve yields and profits.

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Can computers do for the small farm what they've done for other businesses? More, actually

All last spring cold rain fell on Corn Belt fields, leaving them chilled and sodden. On the few days when no rain fell, thick clouds prevented the ground from drying out. Farmers cannot set seed in water-saturated soils (planting machinery compacts wet ground, making a poor incubator for baby roots), but they also cannot wait forever. Past a certain date, every day of delay costs the fall harvest a few percent of yield. For many farmers, that window was narrowing quickly. They stayed indoors, paced, called each other, told farmer stories, and recalled the glory years in the 1970s, when it seemed as if the price of corn would rise forever.

Some farmers, like Doug Harford of Grundy County in Illinois, were a bit better prepared. Harford, a blond column of a man in his middle forties, had laid drainage pipes under his fields, and those had carried off enough water to allow him to squeeze some seed into the ground. Still, he too had a few hours to sit inside, watch his fields soak, and sum up the roller-coaster ride he's been living since he took over his father's farm two decades back.

Every business has its uncertainties, Harford says, but farming is extreme. People in the cities read about the major droughts and floods, but the unpredictability is ever present. Crops are affected by the combination of biology (soil flora and fauna), geology (soil type), and meteorology, all of which fluctuate drastically over space and time. The same input will not produce the same output from one year to the next, nor do any two acres on one farm grow the same yield in the same year -- let alone two acres from different farms. No two situations are ever equal. "People have a tendency to confuse experiences with experiments," Harford says. "Agriculture is mostly experiences."

That unpredictability defines farming culture, making farmers conservative, skeptical, and careful. It also makes farm management more of an art than a science. Other businesses can calculate the tradeoffs between marginal returns and incremental resource costs quantitatively, objectively. A farmer considering whether an extra hour of field inspection makes sense on a given acre must account for the effect of changes in soil type, seed variety, field and planting geometry, tillage practices, yield histories, drainage, pest populations, density of organic material, and so on, all of which can fluctuate wildly across a single field. Turning those variables into hard numbers requires massive amounts of measurement. In the absence of those data, farmers make do by weighing the questions "intuitively." When they do write down numbers, the numbers are estimates -- what Harford calls WAGs, for "wild-assed guesses."

WAGs are not arbitrary: a skilled farmer can manage a host of complexities through "feel." But every farmer's feel has its limitations. Managing through feel sets a limit on the number of acres that can be managed effectively, which in turn limits the efficiencies of scale farmers can bring to bear. Harford believes that if food prices are going to remain low, sooner or later farm management will have to become more quantitative -- less experience, more experiment.

Harford had been thinking about the problem of limitations for some time. He knew that in theory there was a solution: measuring the flow of harvested material every few seconds as it passes through the combine, addressing each measurement with the location of the field segment that each "unit" of material comes from, and then using those "addresses" to plot the yield measurements on a map. A farmer could then control the variables by overlaying the yield data with maps representing the various factors -- for instance, comparing the difference in yield that comes from laying 10 units of fertilizer Y on soil type Z when Z is planted with seed "alpha" with laying 12 units of fertilizer on exactly the same combination of factors.

The theory behind the process, known as "yield monitoring," has been discussed in the academic literature since at least the 1950s and used as an instrument in agricultural research since the 1960s. Commercial farmers had not touched it because the labor required -- stopping to weigh the units of harvested material every few feet, determining the coordinates of the area that had grown that unit, and handling the tremendous volume of data required to make the overlays -- was prodigious. Agricultural research stations had the staff and students to do such scut work; businesses that had to make a profit did not.

In the late 1980s, as often happens, someone too far outside the industry to have heard what was and was not practical saw what seemed like a huge opportunity. Allen Myers was a power transmission engineer at the time, working for Sundstrand Corp., in Rockford, Ill. Though he was no farmer, he knew computers, and he saw that the digital engines were growing cheap and powerful enough to allow many of the most onerous information-handling yield-monitoring tasks to be automated. He also knew about a new idea in the location business. In 1983 Ronald Reagan (in the wake of the Korean Airlines Flight 007 disaster) had announced that a network of navigation satellites built by the Defense Department would be made available for civilian use. The satellites broadcast their orbital position and a time stamp continuously, allowing receivers moving around on the ground to use simple triangulation to find their location. The whole system was called GPS, for "global positioning system." Myers knew he could use the satellites to find his locations.

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