1The Pennsylvania State University, Department of Plant Science, Tyson Building, University Park, PA 16802, USA
2Department of Biology, Greenville University, 315 E. College Ave, Greenville, IL 62246, USA
3Forschungszentrum Jülich GmbH, Institute of Bio-and Geosciences-Plant Sciences (IBG-2), 52425 Jülich, Germany
4Noble Research Institute, LLC, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA
| Received 23 Apr 2020 |
Accepted 05 Sep 2020 |
Published 08 Nov 2020 |
A soil coring protocol was developed to cooptimize the estimation of root length distribution (RLD) by depth and detection of functionally important variation in root system architecture (RSA) of maize and bean. The functional-structural model OpenSimRoot was used to perform in silico soil coring at six locations on three different maize and bean RSA phenotypes. Results were compared to two seasons of field soil coring and one trench. Two one-sided -test (TOST) analysis of in silico data suggests a between-row location 5 cm from plant base (location 3), best estimates whole-plot RLD/D of deep, intermediate, and shallow RSA phenotypes, for both maize and bean. Quadratic discriminant analysis indicates location 3 has ~70% categorization accuracy for bean, while an in-row location next to the plant base (location 6) has ~85% categorization accuracy in maize. Analysis of field data suggests the more representative sampling locations vary by year and species. In silico and field studies suggest location 3 is most robust, although variation is significant among seasons, among replications within a field season, and among field soil coring, trench, and simulations. We propose that the characterization of the RLD profile as a dynamic rhizo canopy effectively describes how the RLD profile arises from interactions among an individual plant, its neighbors, and the pedosphere.
