Nondestructive detection of radish root phenotype based on electrical resistance tomography and ResNet

【Objective】 In view of the problems that the existing experimental equipment for root phenotype detection is expensive, requires special personnel to operate, and cannot perform rapid in situ non-destructive detection of root phenotypes, this paper proposes a non-destructive detection method for radish root phenotype based on electrical resistance tomography (ERT) and deep residual network (ResNet).【Method】 Firstly, the ERT positive problem of the radish-agar field for different cases was performed by COMSOL, and a large amount of boundary voltage data was obtained. Secondly, the nonlinear mapping relationship between the internal conductivity distribution and the boundary voltage inside the radish-agar field was modeled based on ResNet, and image of radish-agar field were reconstructed. Finally, a set of radish root phenotype detection device was developed based on ERT, and the experimental verification was carried out.【Result】 The radish root phenotype detection method based on ERT and ResNet could achieve sustainable nondestructive detection of radish root phenotype, and the experimental setup was simple to operate and low cost, while the relative error of image reconstruction was less than 5%.【Conclusion】 The method of radish root phenotype detection based on ERT can achieve nondestructive detection of radish root phenotype with high imaging accuracy combining with ResNet algorithm. This method can be effectively used for the detection of radish root phenotypes.