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A Comparison of Two Models to Evaluate Soil Physical Property Effects on Corn Root Growth
Two models for evaluating soil physical condition effects on root growth were compared. The first model, called the Jones model, is a submodel for root growth limitations used by several complex soil–plant–atmosphere models. The second model uses soil physical limitations as identified by the least...
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Published in: | Agronomy journal 2013-05, Vol.105 (3), p.713-720 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Two models for evaluating soil physical condition effects on root growth were compared. The first model, called the Jones model, is a submodel for root growth limitations used by several complex soil–plant–atmosphere models. The second model uses soil physical limitations as identified by the least limiting water range (LLWR). Root surface area density (Rsa) and bulk density (ρb) were determined at the V6, V12, and R1 growth stages of corn in 2004. Water contents (θ) throughout the growing season were determined twice per week with a neutron probe. The cumulative predicted relative root growth suitability (PRGS) was determined using soil physical limitations to root growth defined by each model. Significant plot‐to‐plot variability was observed in ρb and θ. The LLWR resulted in a wider range of PRGS for all sampling times and soil depths. Regressions using the LLWR criteria for soil physical limitations resulted in significant correlations between Rsa with PRGS 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 nonsignificant correlation between Rsa with PRGS or a linear, negative correlation, indicating less root surface area with better soil conditions. Using limitations of soil physical properties as identified by the LLWR in larger, more comprehensive plant and root growth models may provide a better response of these models to variable soil conditions. |
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ISSN: | 0002-1962 1435-0645 |
DOI: | 10.2134/agronj2012.0104 |