/AnMtgsAbsts2009.52213 Tillage and Water Deficit Stress Effects On Corn (Zea mays, L.) Root Distribution.

Tuesday, November 3, 2009: 10:50 AM
Convention Center, Room 325, Third Floor

Joseph Benjamin, USDA-ARS, Akron, CO and David Nielsen, USDA-ARS, Central Great Plains Res. Center, Akron, CO
Abstract:
One goal of soil management is to provide optimum conditions for root growth. Corn root distributions were measured in 2004 from a crop rotation – tillage experiment that was started in 2000. Corn was grown either following corn or following sunflower with either no till or deep chisel tillage. Water content measurements were made twice weekly. Root surface area of corn was measured in 0.225-m increments to a depth of 1.8 m in the row and on each side of the row at the V6, V12, and R1 corn growth stages. Bulk density and water content measurements were made at each root sampling location. Measurements of bulk density – water content – cone index were made to characterize strength characteristics of the soil.

Soil water contents following sunflower were drier than following corn at all soil depths. Chisel tillage resulted in lower bulk density and drier soil conditions in the surface 22 cm of soil but had no effect deeper in the soil. More roots were found in the surface 22 cm layer of soil under no till. Total root surface area was greater in the no till treatment at the V6 growth stage, but tillage had no effect on total roots later in the growing season. Corn following sunflower had lower total root surface area than corn following corn at the R1 growth stage, primarily due to drier soil conditions deep in the soil profile which reduced exploration of these soil layers by roots.

Root distributions were dependant on the water content and strength characteristics of the soil. Where low water contents and resultant high soil strength existed, little root growth was found. For models to accurately predict the distribution and concentration of corn roots, the strength characteristic of the individual soil and accurate predictions of the in-season water contents are needed.