Plant-on-a-chip: continuous, soilless electrochemical monitoring of salt uptake and tolerance among different genotypes of tomato.

Tomatoes (Solanum lycopersicum), a high-value crop, exhibit a unique relationship with salt, where increased levels of NaCl can enhance flavor, aroma and nutritional quality but can cause oxidative damage and reduce yields. A drive for larger, better-looking tomatoes has reduced the importance of salt sensitivity, a concern considering that the sodium content of agricultural land is increasing over time. Currently, there are no simple ways of comparing salt tolerance between plants, where a holistic approach looking at [Na+] throughout the plant typically involves destructive, single time point measurements or expensive imaging techniques. Finding methods that collect rapid information in real time could improve the understanding of salt resistance in the field. Here we investigate the uptake of NaCl by tomatoes using TETRIS (Time-resolved Electrochemical Technology for plant Root environment In situ chemical Sensing), a platform used to measure chemical signals in the root area of living plants. Low-cost, screen-printed electrochemical sensors were used to measure changes in salt concentration via electrical impedance measurements, facilitating the monitoring of the uptake of ions by roots. We not only demonstrated differences in the rate of uptake of NaCl between tomato seedlings under different growth conditions, but also showed differences in uptake between varieties of tomato with different NaCl sensitivities and the relatively salt-resistant "wild tomato" (Solanum pimpinellifolium) sister species. Our results suggest that TETRIS could be used to ascertain physiological traits of salt resistance found in adult plants but at the seedling stage of growth. This extrapolation, and the possibility to multiplex and change sensor configuration, could enable high-throughput screening of many hundreds or thousands of mutants or varieties.

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue.

Accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. Here, a phenotyping platform for rapid, continuous-time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating detection of microscopic levels of cell death. Validation is performed by transiently expressing the effector protein AVRblb2 in transgenic Nicotiana benthamiana (expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. Detection of cell death is achieved at microscopic intensities, where leaf tissue appears healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously. This data is used to develop supervised machine-learning (ML) models for classification of HR. Input data (inclusive of the entire tested concentration range) is classified as HR-positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 h and with 87.8% mean accuracy (F1 score = 0.81) at 22 h. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

NFC-enabled potentiostat and nitrocellulose-based metal electrodes for electrochemical lateral flow assay.

Rapid detection of pathogens at the point-of-need is crucial for preventing the spread of human, animal and plant diseases which can have devastating consequences both on the lives and livelihood of billions of people. Colorimetric, lateral flow assays consisting of a nitrocellulose membrane, are the preferred format today for low-cost on-site detection of pathogens. This assay format has, however, historically suffered from poor analytical performance and is not compatible with digital technologies. In this work, we report the development of a new class of digital diagnostics platform for precision point-of-need testing. This new versatile platform consists of two important innovations: i) A wireless and batteryless, microcontroller-based, low-cost Near Field Communication (NFC)-enabled potentiostat that brings high performance electroanalytical techniques (cyclic voltammetry, chronoamperometry, square wave voltammetry) to the field. The NFC-potentiostat can be operated with a mobile app by minimally trained users; ii) A new approach for producing nitrocellulose membranes with integrated electrodes that facilitate high performance electrochemical detection at the point-of-need. We produced an integrated system housed in a 3D-printed phone case and demonstrated its use for the detection of Maize Mosaic Virus (MMV), a plant pathogen, as a proof-of-concept application.

Time-resolved chemical monitoring of whole plant roots with printed electrochemical sensors and machine learning.

Traditional single-point measurements fail to capture dynamic chemical responses of plants, which are complex, nonequilibrium biological systems. We report TETRIS (time-resolved electrochemical technology for plant root environment in situ chemical sensing), a real-time chemical phenotyping system for continuously monitoring chemical signals in the often-neglected plant root environment. TETRIS consisted of low-cost, highly scalable screen-printed electrochemical sensors for monitoring concentrations of salt, pH, and H2O2 in the root environment of whole plants, where multiplexing allowed for parallel sensing operation. TETRIS was used to measure ion uptake in tomato, kale, and rice and detected differences between nutrient and heavy metal ion uptake. Modulation of ion uptake with ion channel blocker LaCl3 was monitored by TETRIS and machine learning used to predict ion uptake. TETRIS has the potential to overcome the urgent "bottleneck" in high-throughput screening in producing high-yielding plant varieties with improved resistance against stress.

Continuous monitoring of chemical signals in plants under stress.

Time is an often-neglected variable in biological research. Plants respond to biotic and abiotic stressors with a range of chemical signals, but as plants are non-equilibrium systems, single-point measurements often cannot provide sufficient temporal resolution to capture these time-dependent signals. In this article, we critically review the advances in continuous monitoring of chemical signals in living plants under stress. We discuss methods for sustained measurement of the most important chemical species, including ions, organic molecules, inorganic molecules and radicals. We examine analytical and modelling approaches currently used to identify and predict stress in plants. We also explore how the methods discussed can be used for applications beyond a research laboratory, in agricultural settings. Finally, we present the current challenges and future perspectives for the continuous monitoring of chemical signals in plants.