Maize Stalk Lodging: A Structural Engineering Approach.

Introduction

Stalk lodging has proven to be a persistent agricultural problem, due to complex interactions between environmental, biological, and abiotic factors.  Genetic relationships that influence lodging are similarly complex, with low levels of heritability. This study describes the application of engineering failure analysis techniques to stalk lodging.  An failure analysis of late season corn stalk lodging revealed that lodging consistently occurs within a few centimeters of stalk nodes, regardless of environment, hybrid type, weather, and planting density.  The purpose of this study was to determine candidate physiological features near the node that may significantly affect stalk strength.

Methods

A sample of 1000 stalks were used in this study (5 hybrids, 5 planting densities, 2 locations, 2 replicates, 10 stalks per replicate).  All stalks were collected immediately before harvest.  Geometric and tissue data was collected via high-resolution x-ray computed tomography (µCT scanning).  Mechanical testing involved a 3-point bending test of each stalk. Customized software was used to analyze the CT scan of each stalk, providing values for numerous geometric features of each stalk.  Statistical analysis of these features were then performed to identify candidate features which may affect stalk strength.

Results

This study represents the first application of engineering principles to study the specific region of stalk failure. Patterns of failure location of laboratory bending tests compared favorably with field observations. Failure strength and stalk stiffness were highly correlated. Geometric factors associated with stalk strength included the following: diameters (major and minor), rind thickness, and cross-sectional moment of inertia.  The above represents preliminary data of a partial data set.  Testing is currently underway, and will be completed by June 30^th, 2014, allowing adequate time for data analysis including significance tests, statistical prediction of strength based on geometric features, etc.