Basak Rinku, Wahid Khan A
Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
Plants (Basel). 2022 Jun 28;11(13):1713. doi: 10.3390/plants11131713.
Root biomass is one of the most relevant root parameters for studies of plant response to environmental change. In this work, a dynamic and adjustable electrode array sensor system is designed for developing a cost-effective, high-speed data acquisition system based on electrical impedance tomography (EIT). The developed EIT system is found to be suitable for in situ measurements and capable of monitoring the changes in root growth and development with three-dimensional imaging by measuring impedances in multiple frequencies with the help of an EIT sensor. The designed EIT sensor system is assessed and calibrated by the inhomogeneities in both water and soil media. The impedances are measured for multiple tap roots using an electrical impedance spectroscopy (EIS) tool connected to the sensor at frequencies ranging from 1 kHz to 100 kHz. The changes in conductivity are calculated by obtaining the boundary voltages from the measured impedances for a given stimulation current. A non-invasive imaging method is utilized, and the spectral changes are observed accordingly to evaluate the growth of the roots. A further root analysis helps us estimate the root biomass non-destructively in real-time. The root size (such as, weight, length) is correlated with the measured impedances. A regression analysis is performed using the least square method, and more than 97% correlation is found for the biomass estimation of carrot roots with an RMSE of 4.516. The obtained models are later validated using a new and separate set of carrot root samples and the accuracy of the predicted models is found to be 93% or above. A complete electrode model is utilized, and the reconstruction analysis is performed and optimized by utilizing the impedance imaging technique in difference method. The tomography of the root is reconstructed with finite element method (FEM) modeling considering one-step Gauss-Newton (GN) algorithm which is carried out using an open source software known as electrical impedance and diffuse optical tomography reconstruction software (EIDORS).
根生物量是研究植物对环境变化响应时最相关的根系参数之一。在这项工作中，设计了一种动态可调电极阵列传感器系统，用于开发基于电阻抗断层成像（EIT）的经济高效、高速数据采集系统。所开发的EIT系统被发现适用于原位测量，并且能够借助EIT传感器通过测量多个频率的阻抗来以三维成像方式监测根系生长和发育的变化。所设计的EIT传感器系统通过水和土壤介质中的不均匀性进行评估和校准。使用连接到传感器的电阻抗谱（EIS）工具在1 kHz至100 kHz的频率范围内测量多个主根的阻抗。通过针对给定激励电流从测量的阻抗中获取边界电压来计算电导率的变化。利用一种非侵入性成像方法，并相应地观察光谱变化以评估根系生长。进一步的根系分析有助于我们实时无损估计根生物量。根大小（如重量、长度）与测量的阻抗相关。使用最小二乘法进行回归分析，发现胡萝卜根生物量估计的相关性超过97%，均方根误差为4.516。随后使用一组新的、单独的胡萝卜根样本对获得的模型进行验证，发现预测模型的准确率在93%或以上。利用完整电极模型，并采用差分法中的阻抗成像技术进行重建分析和优化。考虑一步高斯 - 牛顿（GN）算法，使用称为电阻抗和扩散光学断层成像重建软件（EIDORS）的开源软件通过有限元方法（FEM）对根系断层成像进行重建。
