Plant impedance spectroscopy: a review of modeling approaches and applications

Electrochemical impedance spectroscopy has emerged over the past decade as an efficient, non-destructive method to investigate various (eco-)physiological and morphological properties of plants. This work reviews the state-of-the-art of impedance spectra modeling for plant applications. In addition to covering the traditional, widely-used representations of electrochemical impedance spectra, we also consider the more recent machine-learning-based approaches

Evaluating the potential of Distribution of Relaxation Times analysis for plant agriculture

The analysis of a Distribution of Relaxation Times (DRT) has proven to be extremely effective for the study of electrochemical power sources. Biological systems are non-inductive, making them very suitable candidates for DRT analysis, as demonstrated by recent research. In this work, we conduct the first evaluation of DRT analysis in agricultural applications. We revisit published equivalent electrical circuit parameter data to evaluate the potential of DRT analysis for various plant electrochemical impedance spectroscopy applications. We investigate the advantages and limitations of adopting this emerging analysis method as an impedance modelling strategy for the electrochemical characterisation of plants. We illustrate its promise by comparing it with the standard methods using simulations and measurements published in the literature on fruit ripening, plant stress, and post-harvest processing of agricultural products. This study highlights the potential of DRT analysis as an effective modelling strategy for impedimetric system characterisation in agriculture, with promising advantages over standard techniques

Equivalent electrical circuits and their use across electrochemical impedance spectroscopy application domains

When studying electrochemical systems, EIS practitioners face the challenge of choosing a relevant equivalent electrical circuit to analyze their measurement data and interpreting the role of its components. In this review, we take a closer look at the use of equivalent electrical circuits (EEC) across various application domains. We aim to aid EIS practitioners in determining and evaluating their EEC-based data analysis methodology in light of recent progress from all EIS application domains. We review EEC usage and its interpretation while additionally providing software to automatically search for equivalent electrical circuits from the relevant application domain literature that fit EIS measurements supplied by users. Finally, we make a comparison of the impedimetric behaviour and circuit modelling approaches of a range of different electrochemical systems and discuss some complementary EIS data analysis strategies

Practical equivalent electrical circuit identification for electrochemical impedance spectroscopy analysis with gene expression programming

Researchers relying on electrochemical impedance spectroscopy need to decide which equivalent electrical circuit to use to analyze their measurements. Here, we present an identification algorithm based on gene expression programming to support this decision. It is accompanied by some measures to enhance the interpretability of the resulting circuits, such as the removal of redundant components to avoid overly complex circuits. We also provide the option to depart from an initial population of widely applied circuits, allowing for quick identification of known circuits that are capable of modeling the measurement data. As the number of measurements per experiment is typically rather limited in real-life experiments, we examine the number needed to find an adequate circuit topology for two example circuits. Next, the algorithm is tested on impedance simulations for a variety of circuits. Noise robustness is evaluated by subjecting the impedance measurements to increasing amounts of Gaussian noise, demonstrating that the algorithm still works well even for noise levels that are significantly higher than what is typically encountered in practice. Finally, we validate the algorithm by identifying the appropriate circuit for impedance measurements from a biological application

Altered intravenous drug disposition in people living with cystic fibrosis : a meta‐analysis integrating top‐down and bottom‐up data

Cystic fibrosis (CF) has been linked to altered drug disposition in various studies. However, the magnitude of these changes, influencing factors, and underlying mechanisms remain a matter of debate. The primary aim of this work was therefore to quantify changes in drug disposition (top-down) and the pathophysiological parameters known to affect pharmacokinetics (PKs; bottom-up). This was done through meta-analyses and meta-regressions in addition to theoretical PK simulations. Volumes of distribution and clearances were found to be elevated in people living with CF. These increases were larger in studies which included patients with pulmonary exacerbations. Differences in clearance were smaller in more recent studies and when results were normalized to body surface area or lean body mass instead of body weight. For the physiological parameters investigated, measured glomerular filtration rate and serum cytokine concentrations were found to be elevated in people living with CF, whereas serum albumin and creatinine levels were decreased. Possible pathophysiological mechanisms for these alterations relate to renal hyperfiltration, increases in free fraction, and inflammation. No differences were detected for cardiac output, body fat, fat free mass, hematocrit, creatinine clearance, and the activity of drug metabolizing enzymes. These findings imply that, in general, lower total plasma concentrations of drugs can be expected in people living with CF, especially when pulmonary exacerbations are present. Given the potential effect of CF on plasma protein binding and the variability in outcome observed between studies, the clinical relevance of adapting existing dosage regimens should be evaluated on a case-by-case basis

On the pivotal role of water potential to model plant physiological processes

Water potential explains water transport in the Soil-Plant-Atmosphere Continuum (SPAC), and is gaining interest as connecting variable between ‘pedo-, bio- and atmosphere’. It is primarily used to simulate hydraulics in the SPAC, and is thus essential for studying drought effects. Recent implementations of hydraulics in large-scale Terrestrial Biosphere Models (TBMs) improved their performance under water-limited conditions, while hydraulic features of recent detailed FunctionalStructural Plant Models (FSPMs) open new possibilities for dissecting complex traits for drought tolerance. These developments in models across scales deserve a critical appraisal to evaluate its potential for wider use in FSPMs, but also in crop systems models (CSMs), where hydraulics are currently still absent. After refreshing the physical basis, we first address models where water potential is primarily used for describing water transport along the transpiration pathway from the soil to the leaves, through the roots, the xylem and the leaf mesophyll. Then, we highlight models for three ecophysiological processes, which have well-recognised links to water potential: phloem transport, stomatal conductance and organ growth. We identify water potential as the bridge between soil, root and shoot models, as the physiological variable integrating below- and aboveground abiotic drivers, but also as the link between water status and growth. Models making these connections enable identifying crucial traits for ecosystem resilience to drought and for breeding towards improved drought tolerance in crops. Including hydraulics often increases model complexity, and thus requires experimental data on soil and plant hydraulics. Nevertheless, modelling hydraulics is insightful at different scales (FSPMs, CSMs and TBMs)