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Soil health is a complex phenomenon that reflects the ability of soil to support both plant growth and other ecosystem functions. To our knowledge, research on extracellular electron transfer processes in soil environments is limited and could provide novel knowledge and new ways of monitoring soil health. Electrochemical activities in the soil can be studied by inserting inert electrodes. Once the electrode is polarized to a favorable potential, nearby microorganisms attach to the electrodes and grow as biofilms. Biofilms are a major part of the soil and play critical roles in microbial activity and community dynamics. Our work aims to investigate the electrochemical behavior of healthy and unhealthy soils using chronoamperometry and cyclic voltammetry. We developed a bioelectrochemical soil reactor for electrochemical measurements using healthy and unhealthy soils taken from the Cook Agronomy Farm Long-Term Agroecological Research site; the soils showed similar physical and chemical characteristics, but there was higher plant growth where the healthy soil was taken. Using carbon cloth electrodes installed in these soil reactors, we explored the electrochemical signals in these two soils. First, we measured redox variations by depth and found that reducing conditions were prevalent in healthy soils. Current measurements showed distinct differences between healthy and unhealthy soils. Scanning electron microscopy images showed the presence of microbes attached to the electrode for healthy soil but not for unhealthy soil. Glucose addition stimulated current in both soil types and caused differences in cyclic voltammograms between the two soil types to converge. Our work demonstrates that we can use current as a proxy for microbial metabolic activity to distinguish healthy and unhealthy soil. 

Abstract Parameters representing three‐dimensional (3D) biofilm structure are quantified from confocal laser‐scanning microscope (CLSM) images. These 3D parameters describe the distribution of biomass pixels within the space occupied by a biofilm; however, they lack a direct connection to biofilm activity. As a result, researchers choose a handful of parameters without there being a consensus on a standard set of parameters. We hypothesized that a select 3D parameter set could be used to reconstruct a biofilm image and that the reconstructed and original biofilm images would have similar activities. To test this hypothesis, an algorithm was developed to reconstruct a biofilm image with parameters identical to those of the original CLSM image. We introduced an objective method to assess the reconstruction algorithm by comparing the activities of the original and reconstructed biofilm images. We found that biofilm images with identical structural parameters showed nearly identical activities and substrate concentration profiles. This implies that the set containing all common structural parameters can successfully describe biofilm structure. This finding is significant, as it opens the door to the next step, of finding a smaller standard set of biofilm structural parameters that can be used to compare biofilm structure.