Non-destructive high-throughput measurement of elastic-viscous properties of maize using a novel ultra-micro sensor array and numerical validation

Abstract

Abstract Maize is the world's most produced cereal crop, and the selection of maize cultivars with a high stem elastic modulus is an effective method to prevent cereal crop lodging. We developed an ultra-compact sensor array inspired by earthquake engineering and proposed a method for the high-throughput evaluation of the elastic modulus of maize cultivars. A natural vibration analysis based on the obtained Young's modulus using finite element analysis (FEA) was performed and compared with the experimental results, which showed that the estimated Young's modulus is representative of the individual Young's modulus. FEA also showed the hotspot where the stalk was most deformed when the corn was vibrated by wind. The six tested cultivars were divided into two phenotypic groups based on the position and number of hotspots. In this study, we proposed a non-destructive high-throughput phenotyping technique for estimating the modulus of elasticity of maize stalks and successfully visualized which parts of the stalks should be improved for specific cultivars to prevent lodging.

Code and data availability

The paper states that all source code used (the plantFEM finite-element analysis software for the maize elastodynamics simulations) is publicly available on GitHub at the authors' URL. No phenotype dataset or raw sensor waveform deposit is explicitly stated.