Practiced in Precision
Written By: Steve Richter
One of Gary Wagner’s trusty laptop computers bounces next to him on the pickup seat during a hectic northern Red River Valley harvest. Before finishing soybeans, Wagner stops to download yield-monitor data from the sugar-beet harvester run by brothers Wayne and Daryl, his partners in A.W.G. Farms.
Deep layers of data define the management of the 4,300 acre Crookston, MN, wheat, barley, beet and soybean operation. Yield monitors, GPS systems, soil tests, aerial and satellite photos, digital rain gauges, soil surveys, even lasers, provide grist for enhanced computer field maps, more colorful and detailed than most.
The self-taught computer enthusiast starts to see patterns when he compares these maps. Some answer questions; others highlight problems that need more attention. After collecting five years of field data, he has developed a reliable database for making wise decisions.
“I don’t know what we need to collect, so I’m collecting everything now,” says Wagner, who years ago learned programming to adapt an early personal computer for farm use. “We’re trying to decide what’s important.”
One year’s data can help compare varieties, herbicide rates or plant food performance, explains Wagner, a cooperator in the field and classroom with nearby University of Minnesota-Crookston and a customer of Crookston Valley Co-Op and Farmers Union Oil of Climax, MN. But to improve overall management and maybe even modify soil factors, he notes: “It seems wise to start with three to six years of data before putting too much stock in yield maps or making costly changes.”
In one case, after digesting three years of digitized data, Wagner thought at first that compaction caused wheat/beet field problem. But further mapping and analysis seem to indicate something else. Deep nitrate shortage? Or is it organic? The search goes on.
A.W.G. Farms’ air seeder can variably spread three nutrients in one pass, but Wagner cautions that fertility is only one of several important yield factors. Others with as much impact include water-holding capacity, organic content and pH levels.
Despite the area’s table-top terrain, maps and photos show that poor drainage damages the Wagners’ yields most. In one beet field, for example, per-acre return varied by $340 form the high-producing end to a still poorly drained area.
At age 21, Gary took over the 900-acre family farm with older brother Wayne after their father died. Twenty-two years later, the early adopter is still learning. He’s finding, for example, that soil sampling by fine-tuned topography rather than grids makes agronomic as well as economic sense on their farm. He points to overlapping aerial photos and microtopographic maps that define specific management areas in irregular shapes, not neat squares.
“Maybe our grandfathers knew more about precision ag (than we thought),” he notes. “I don’t want to cut back to farming 20- and 40-acre regions like they did, but we need to manage that way.”
In high demand on the ag winter speaking circuit, Wagner talks about taking the “leap of faith” to precision farming’s promised land. He and his brothers have “leaped,” investing big bucks and long hours with, so far, undetermined return.
“In the long run, farmers will figure out how to make site-specific farming economical so they can meet consumer demand for attribute-specific food products,” Wagner tells groups. “Farmland with data may be worth more, too.”
In the meantime, frustrations are many. “Farmers want black and white answers,” he points out, “but precision farming has 256 shades of gray.
“Precision farming is not so much about yield monitors, variable-rate fertilizer spreaders, grid soil sampling or whatever term you can think of,” adds Wagner. “It’s about tools a farmer can use to help locate, evaluate and execute management decisions.”