Agronomy Journal • Volume 105, Issue 3 • 2013 713 Soil Tillage, Conservation & Management A Comparison of Two Models to Evaluate Soil Physical Property Effects on Corn Root Growth Joseph G. Benjamin,* David C. Nielsen, Merle F. Vigil, Maysoon M. Mikha, and Francisco J. Calderon Published in Agron. J. 105:713–720 (2013) doi:10.2134/agronj2012.0104 Copyright © 2013 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. T he goal of many soil and crop management practices is to provide a more favorable environment for crop produc- tion for the soil at a particular location. One key to the proper use of available soil management techniques is the understand- ing of the complex interactions among soil physical properties, root growth and development, and plant response to changing physical conditions. Soil physical and chemical conditions, as well as the genetic predisposition of the crop species, determine the root distri- bution for a particular crop. Skinner et al. (1998) studied the efects of banded NO 3 fertilizer and furrow irrigation on corn root distribution and showed that there is a complex interac- tion between the stimulation of corn roots due to high NO 3 concentration and the restrictive efect of dry soil on corn roots. Root response to soil conditions was even more complex due to the apparent increase in corn root density in somewhat dry soil compared with consistently moist soil. Benjamin and Nielsen (2004) showed that plant response to dry soil conditions can vary with plant species and the growth stage of a plant within a species. hey found that the root system of soybean [ Glycine max (L.) Merr.] was relatively unafected by water deicit conditions, whereas ield pea [Pisum sativum L. ssp. sativum var. arvense (L.) Poir.] and chickpea ( Cicer arietinum L.) responded to water dei- cit by growing more roots deeper in the soil proile. It is obvious that an active root system with the uptake of water for transpiration greatly afects chemical leaching from the root zone compared with bare soil scenarios. Benjamin et al. (1996) predicted less NO 3 leaching from under a corn crop than under bare soil due to less downward water movement in the soil proile. Jackson and Estes (2007), using three independent models, pre- dicted a hypothetical chemical concentration at the bottom of a 1.1-m proile under corn or turfgrass to be one-half to one-tenth the concentration of the same chemical under bare soil. Models are oten used to integrate these complex interactions into a form that a manager can use to make better management decisions. Complex models have been developed to investigate the efects of management practices on crop yield (Jones et al., 2003), soil erosion (Jones et al., 1991b), and water quality (Ahuja et al., 2000). hese models attempt to distribute roots into the soil based on the crop and its growth stage, the amount of C available for root growth, and the soil conditions in which the crop grows. In general, these models allocate a certain amount of C for root growth and then distribute the roots in the underlying soil based on the relative suitability for root growth in the soil layers. he accuracy and usefulness of these models rely on the ability of the root growth submodel to respond to varying soil conditions. Models for simulating multidimensional root growth into variable soil have been developed (Grant, 1993a, 1993b; Ben- jamin et al., 1996), but the limiting criteria for altering root growth due to changes in soil physical conditions have not been well studied. he nature of root-limiting soil physical conditions is complicated by the fact that diferent mechanisms control root growth at diferent q (m 3 m –3 ) as r b changes. In very wet soil, O 2 and CO 2 difusion into and out of the soil may be limited and ABSTRACT Two models for evaluating soil physical condition efects on root growth were compared. he irst model, called the Jones model, is a submodel for root growth limitations used by several complex soil–plant–atmosphere models. he second model uses soil physical limitations as identiied by the least limiting water range (LLWR). Root surface area density (R sa ) and bulk density (r b ) were determined at the V6, V12, and R1 growth stages of corn in 2004. Water contents (q) throughout the growing season were determined twice per week with a neutron probe. he cumulative predicted relative root growth suitability (P RGS ) was deter- mined using soil physical limitations to root growth deined by each model. Signiicant plot-to-plot variability was observed in r b and q. he LLWR resulted in a wider range of P RGS for all sampling times and soil depths. Regressions using the LLWR criteria for soil physical limitations resulted in signiicant correlations between R sa with P RGS at the expanding zone of root exploration, indicating more root surface area with better soil conditions. Regressions using the Jones criteria for soil physical limitations resulted in either a nonsigniicant correlation between R sa with P RGS or a linear, negative correlation, indicating less root surface area with better soil conditions. Using limitations of soil physical properties as identiied by the LLWR in larger, more comprehensive plant and root growth models may provide a better response of these models to variable soil conditions. USDA-ARS, Central Great Plains Research Station, Akron, CO 80720. Re- ceived 21 Mar. 2012. *Corresponding author (Joseph.Benjamin@ars.usda.gov). Abbreviations: CC, continuous corn; CI, cone index; LLWR, least limiting water range; Rot, crop rotation. Published March 15, 2013