DuPont Pioneer researchers use sophisticated, state-of-the-art equipment to plant, manage, harvest and collect data from test plots. Doing so leads to improved hybrids and varieties for growers.

“We’re using specialized equipment for precommercial testing and product development,” says Jan Jackson, DuPont Pioneer IMPACT field-testing lead. “We can more effectively identify the best products for grower environments and support the Pioneer sales team in providing growers with the right product for the right acre.”

The IMPACT™ (Intensively Managed Product Advancement Characterization and Training) trial program provides local data to help Pioneer with decisions on crop genetics. Plots allow researchers to test dozens of Pioneer® brand corn hybrids and soybean varieties that are candidates for commercialization. The large number of local plots means Pioneer researchers can learn how products perform in a wide variety of growing environments. Data from these plots show which products offer the best performance in a given environment, allowing Pioneer to bring only the best products to market for growers.

“We need to extract high-quality data on each hybrid or variety we’re testing,” Jackson says. “It’s not just planters and combines: we’re using specialized equipment for preparing and managing seed before planting, and for collecting and analyzing complex data at harvest.”

Pioneer uses the data to make precommercial decisions about which products to keep or cull. Information pulled from test plots also helps researchers develop agronomic trait scores for each.

Researchers use four- and eight-row planters. The planters are the perfect size to establish thousands of test fields across North America. Row width may vary between 30-, 36-, 38- or 40-inch row spacing or require planting on soil ridges depending on geography, grower preference and field management. For these areas, research must use special planters with telescoping row units to be able to adjust to the different row width of each grower cooperator.

“We test in thousands of North American fields to understand local environments and how each product performs in those environments,” Jackson says. “We need high uniformity within the field to accurately separate genetic differences. At the same time, we need diverse field environments on a field-to-field basis.”

“We start collecting information on growth and plant development as soon as the plant emerges,” Jackson says. “When we decide to advance a product, we must know how it performs in a wide array of conditions.”