Hokkaido University, Sapporo, Japan.
Tokyo Institute of Technology, Tokyo, Japan.
Sci Rep. 2023 Mar 25;13(1):4914. doi: 10.1038/s41598-023-32130-5.
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.
玉米是世界上产量最高的谷类作物，选择茎弹性模量高的玉米品种是防止谷类作物倒伏的有效方法。我们受地震工程启发开发了一种超紧凑型传感器阵列，并提出了一种高通量评估玉米品种弹性模量的方法。基于有限元分析（FEA）得到的杨氏模量进行了自然振动分析，并将结果与实验结果进行了比较，结果表明，估算的杨氏模量能够代表个体杨氏模量。FEA 还显示了玉米在风吹振动时茎部变形最大的热点位置。根据热点的位置和数量，将六种测试品种分为两个表型组。在这项研究中，我们提出了一种非破坏性的高通量表型技术，用于估计玉米茎的弹性模量，并成功地可视化了哪些部位需要改进，以防止特定品种的倒伏。
