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Continuous monitoring of chemical signals in plants under stress

Nature Reviews Chemistry volume 7, pages 7–25 (2023)Cite this article

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Abstract

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.

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Fig. 1: Duration, magnitude and complexity of chemical signals in plants are often highly dependent on the stressor and can be captured through continuous, time-resolved measurements.
Fig. 2: Overview of chemical signals in response to stress in plants.
Fig. 3: Methods for continuous monitoring of chemical signals in plants.
Fig. 4: Sensors for monitoring ions as stress signals in plants.
Fig. 5: Sensors for monitoring radicals and inorganic molecules in plants.
Fig. 6: Sensors for monitoring organic molecules in plants.
Fig. 7: Modelling and analysis of plant stress.

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References

  1. Geilfus, C. M. The pH of the apoplast: dynamic factor with functional impact under stress. Mol. Plant 10, 1371–1386 (2017).

    Article  CAS  Google Scholar 

  2. Zhang, J. & Zhou, J.-M. Plant immunity triggered by microbial molecular signatures. Mol. Plant 3, 783–793 (2010).

    Article  CAS  Google Scholar 

  3. Chisholm, S. T., Coaker, G., Day, B. & Staskawicz, B. J. Host-microbe interactions: shaping the evolution of the plant immune response. Cell 124, 803–814 (2006).

    Article  CAS  Google Scholar 

  4. Lam, E., Kato, N. & Lawton, M. Programmed cell death, mitochondria and the plant hypersensitive response. Nature 411, 848–853 (2001).

    Article  CAS  Google Scholar 

  5. Felle, H. H., Waller, F., Molitor, A. & Kogel, K. H. The mycorrhiza fungus Piriformospora indica induces fast root-surface pH signaling and primes systemic alkalinization of the leaf apoplast upon powdery mildew infection. Mol. Plant Microbe Interact. 22, 1179–1185 (2009).

    Article  CAS  Google Scholar 

  6. Hussain, M., Malik, M. A., Farooq, M., Ashraf, M. Y. & Cheema, M. A. Improving drought tolerance by exogenous application of glycinebetaine and salicylic acid in sunflower. J. Agron. Crop Sci. 194, 193–199 (2008).

    Article  CAS  Google Scholar 

  7. Munné-Bosch, S. & Peñuelas, J. Photo- and antioxidative protection, and a role for salicylic acid during drought and recovery in field-grown Phillyrea angustifolia plants. Planta 217, 758–766 (2003).

    Article  Google Scholar 

  8. Fichman, Y., Miller, G. & Mittler, R. Whole-plant live imaging of reactive oxygen species. Mol. Plant 12, 1203–1210 (2019).

    Article  CAS  Google Scholar 

  9. Albert, M. & Fürst, U. in Plant Receptor Kinases. Methods in Molecular Biology Vol. 1621 (ed. Aalen, R.) 69–76 (Humana, 2017).

  10. Giraldo, J. P., Wu, H., Newkirk, G. M. & Kruss, S. Nanobiotechnology approaches for engineering smart plant sensors. Nat. Nanotechnol. 14, 541–553 (2019).

    Article  CAS  Google Scholar 

  11. Hill, O. The ultimate guide to crop disease and pest forecasting tools. Farmers Weekly https://www.fwi.co.uk/arable/find-latest-crop-disease-pest-forecasts-season (2016).

  12. Liu, J. & Wang, X. Plant diseases and pests detection based on deep learning: a review. Plant Methods 17, 22 (2021).

    Article  Google Scholar 

  13. Harakannanavar, S. S., Rudagi, J. M., Puranikmath, V. I., Siddiqua, A. & Pramodhini, R. Plant leaf disease detection using computer vision and machine learning algorithms. Glob. Transit. Proc. 3, 305–310 (2022).

    Article  Google Scholar 

  14. Mohanty, S. P., Hughes, D. P. & Salathé, M. Using deep learning for image-based plant disease detection. Front. Plant Sci. 7, 1419 (2016).

    Article  Google Scholar 

  15. Flynn, P. Biotic vs. abiotic - distinguishing disease problems. Iowa State University https://hortnews.extension.iastate.edu/biotic-vs-abiotic-distinguishing-disease-problems (2003).

  16. Basu, S., Varsani, S. & Louis, J. Altering plant defenses: herbivore-associated molecular patterns and effector arsenal of chewing herbivores. Mol. Plant Microbe Interact. 31, 13–21 (2018).

    Article  CAS  Google Scholar 

  17. Bi, G. et al. The ZAR1 resistosome is a calcium-permeable channel triggering plant immune signaling. Cell 184, 3528–3541.e12 (2021).

    Article  CAS  Google Scholar 

  18. Ngou, B. P. M., Ahn, H. K., Ding, P. & Jones, J. D. G. Mutual potentiation of plant immunity by cell-surface and intracellular receptors. Nature 592, 110–115 (2021).

    Article  CAS  Google Scholar 

  19. Barker, A. V & Pilbeam, D. J. Handbook of Plant Nutrition (CRC, 2015).

  20. John Cram, B. W. et al. Handbook of reference methods for plant analysis. Crop Sci. 38, 1710–1711 (1998).

    Article  Google Scholar 

  21. Crawford, N. M. Nitrate: nutrient and signal for plant growth. Plant Cell 7, 859–868 (1995).

    CAS  Google Scholar 

  22. Naveed, Z. A., Wei, X., Chen, J., Mubeen, H. & Ali, G. S. The PTI to ETI continuum in Phytophthora-plant interactions. Front. Plant Sci. 11, 593905 (2020).

    Article  Google Scholar 

  23. Flowers, T. J. & Colmer, T. D. Salinity tolerance in halophytes. New Phytol. 179, 945–963 (2008).

    Article  CAS  Google Scholar 

  24. He, M., He, C.-Q. & Ding, N.-Z. Abiotic stresses: general defenses of land plants and chances for engineering multistress tolerance. Front. Plant Sci. 9, 1771 (2018).

    Article  Google Scholar 

  25. Colmenero-Flores, J. M., Franco-Navarro, J. D., Cubero-Font, P., Peinado-Torrubia, P. & Rosales, M. A. Chloride as a beneficial macronutrient in higher plants: new roles and regulation. Int. J. Mol. Sci. 20, 4686 (2019).

    Article  CAS  Google Scholar 

  26. Broyer, T. C., Carlton, A. B., Johnson, C. M. & Stout, P. R. Chlorine — a micronutrient element for higher plants. Plant Physiol. 29, 526–532 (1954).

    Article  CAS  Google Scholar 

  27. Yuan, P., Yang, T. & Poovaiah, B. W. Calcium signaling-mediated plant response to cold stress. Int. J. Mol. Sci. 19, 3896 (2018).

    Article  Google Scholar 

  28. Tuteja, N. & Mahajan, S. Calcium signaling network in plants: an overview. Plant Signal. Behav. 2, 79–85 (2007).

    Article  Google Scholar 

  29. Muday, G. K. & Brown-Harding, H. Nervous system-like signaling in plant defense. Science 361, 1068–1069 (2018).

    Article  CAS  Google Scholar 

  30. Toyota, M. et al. Glutamate triggers long-distance, calcium-based plant defense signaling. Science 361, 1112–1115 (2018). Revelation of a hormone-like role for glutamate in long-distance, time-dependent calcium signalling resulting from herbivore feeding and mechanical wounding.

    Article  CAS  Google Scholar 

  31. Hanstein, S., de Beer, D. & Felle, H. H. Miniaturised carbon dioxide sensor designed for measurements within plant leaves. Sens. Actuators B Chem. 81, 107–114 (2001). Measurement of CO2 inside the stomatal pore enabled using a miniaturized glass-capillary electrochemical sensor.

    Article  CAS  Google Scholar 

  32. Hu, S., Ding, Y. & Zhu, C. Sensitivity and responses of chloroplasts to heat stress in plants. Front. Plant Sci. 11, 375 (2020).

    Article  Google Scholar 

  33. Im, H., Lee, S., Naqi, M., Lee, C. & Kim, S. Flexible PI-based plant drought stress sensor for real-time monitoring system in smart farm. Electronics 7, 114 (2018).

    Article  CAS  Google Scholar 

  34. Ali, M., Cheng, Z., Ahmad, H. & Hayat, S. Reactive oxygen species (ROS) as defenses against a broad range of plant fungal infections and case study on ROS employed by crops against Verticillium dahliae wilts. J. Plant Interact. 13, 353–363 (2018).

    Article  CAS  Google Scholar 

  35. Torres, M. A., Jones, J. D. G. & Dangl, J. L. Reactive oxygen species signaling in response to pathogens. Plant Physiol. 141, 373–378 (2006).

    Article  CAS  Google Scholar 

  36. Lamb, C. & Dixon, R. A. The oxidative burst in plant disease resistance. Annu. Rev. Plant Physiol. Plant Mol. Biol. 48, 251–275 (1997).

    Article  CAS  Google Scholar 

  37. Xu, Q. et al. In vivo monitoring of oxidative burst induced by ultraviolet A and C stress for oilseed rape by microbiosensor. Sens. Actuators B Chem. 141, 599–603 (2009).

    Article  CAS  Google Scholar 

  38. Ding, Y., Shi, Y. & Yang, S. Advances and challenges in uncovering cold tolerance regulatory mechanisms in plants. New Phytol. 222, 1690–1704 (2019).

    Article  Google Scholar 

  39. Iovine, N. M. et al. Reactive nitrogen species contribute to innate host defense against Campylobacter jejuni. Infect. Immun. 76, 986–993 (2008).

    Article  CAS  Google Scholar 

  40. Pauly, N. et al. Reactive oxygen and nitrogen species and glutathione: key players in the legume–Rhizobium symbiosis. J. Exp. Bot. 57, 1769–1776 (2006).

    Article  CAS  Google Scholar 

  41. Parankusam, S., Adimulam, S. S., Bhatnagar-Mathur, P. & Sharma, K. K. Nitric oxide (NO) in plant heat stress tolerance: current knowledge and perspectives. Front. Plant Sci. 8, 1582 (2017).

    Article  Google Scholar 

  42. Šimura, J. et al. Plant hormonomics: multiple phytohormone profiling by targeted metabolomics. Plant Physiol. 177, 476–489 (2018).

    Article  Google Scholar 

  43. Park, J., Lee, Y., Martinoia, E. & Geisler, M. Plant hormone transporters: what we know and what we would like to know. BMC Biol. 15, 93 (2017).

    Article  Google Scholar 

  44. Shah, J. & Zeier, J. Long-distance communication and signal amplification in systemic acquired resistance. Front. Plant Sci. 4, 30 (2013).

    Article  Google Scholar 

  45. McConn, M., Creelman, R. A., Bell, E., Mullet, J. E. & Browse, J. Jasmonate is essential for insect defense in Arabidopsis. Proc. Natl Acad. Sci. USA 94, 5473–5477 (1997).

    Article  CAS  Google Scholar 

  46. Snoeren, T. A. L. et al. The herbivore-induced plant volatile methyl salicylate negatively affects attraction of the parasitoid Diadegma semiclausum. J. Chem. Ecol. 36, 479–489 (2010).

    Article  CAS  Google Scholar 

  47. Fong, D., Luo, S.-X., Andre, R. S. & Swager, T. M. Trace ethylene sensing via Wacker oxidation. ACS Cent. Sci. 6, 507–512 (2020).

    Article  CAS  Google Scholar 

  48. Dudareva, N., Negre, F., Nagegowda, D. A. & Orlova, I. Plant volatiles: recent advances and future perspectives. Crit. Rev. Plant Sci. 25, 417–440 (2006).

    Article  CAS  Google Scholar 

  49. Raghava, T., Ravikumar, P., Hegde, R. & Kush, A. Spatial and temporal volatile organic compound response of select tomato cultivars to herbivory and mechanical injury. Plant Sci. 179, 520–526 (2010).

    Article  CAS  Google Scholar 

  50. Taiz, L., Zeiger, E., Moller, I. M. & Mirphy, A. Plant Physiology and Development (Sinauer Associates, 2015).

  51. Farmer, E. E. & Ryan, C. A. Interplant communication: airborne methyl jasmonate induces synthesis of proteinase inhibitors in plant leaves. Proc. Natl Acad. Sci. USA 87, 7713–7716 (1990).

    Article  CAS  Google Scholar 

  52. Altangerel, N. et al. In vivo diagnostics of early abiotic plant stress response via Raman spectroscopy. Proc. Natl Acad. Sci. USA 114, 3393–3396 (2017).

    Article  CAS  Google Scholar 

  53. Chalker-Scott, L. Environmental significance of anthocyanins in plant stress responses. Photochem. Photobiol. 70, 1–9 (1999).

    Article  CAS  Google Scholar 

  54. Kovinich, N. et al. Not all anthocyanins are born equal: distinct patterns induced by stress in Arabidopsis. Planta 240, 931–940 (2014).

    Article  CAS  Google Scholar 

  55. Wang, M. et al. Bidirectional cross-kingdom RNAi and fungal uptake of external RNAs confer plant protection. Nat. Plants 2, 16151 (2016).

    Article  CAS  Google Scholar 

  56. Kim, G., LeBlanc, M. L., Wafula, E. K., DePamphilis, C. W. & Westwood, J. H. Genomic-scale exchange of mRNA between a parasitic plant and its hosts. Science 345, 808–811 (2014).

    Article  CAS  Google Scholar 

  57. Chen, Y. et al. An aphid RNA transcript migrates systemically within plants and is a virulence factor. Proc. Natl Acad. Sci. USA 117, 12763–12771 (2020).

    Article  CAS  Google Scholar 

  58. Qiao, Y. et al. Oomycete pathogens encode RNA silencing suppressors. Nat. Genet. 45, 330–333 (2013).

    Article  CAS  Google Scholar 

  59. Hou, Y. et al. A Phytophthora effector suppresses trans-kingdom RNAi to promote disease susceptibility. Cell Host Microbe 25, 153–165.e5 (2019).

    Article  CAS  Google Scholar 

  60. Yin, C. et al. A novel fungal effector from Puccinia graminis suppressing RNA silencing and plant defense responses. New Phytol. 222, 1561–1572 (2019).

    Article  CAS  Google Scholar 

  61. Moroz, N. et al. Extracellular alkalinization as a defense response in potato cells. Front. Plant Sci. 8, 32 (2017).

    Article  Google Scholar 

  62. González-Sánchez, M. I. et al. Electrochemical detection of extracellular hydrogen peroxide in Arabidopsis thaliana: a real-time marker of oxidative stress. Plant Cell Environ. 36, 869–878 (2013).

    Article  Google Scholar 

  63. Roper, J. M., Garcia, J. F. & Tsutsui, H. Emerging technologies for monitoring plant health in vivo. ACS Omega 6, 5101–5107 (2021).

    Article  CAS  Google Scholar 

  64. Schornack, S. et al. Ancient class of translocated oomycete effectors targets the host nucleus. Proc. Natl Acad. Sci. USA 107, 17421–17426 (2010).

    Article  CAS  Google Scholar 

  65. Kikkert, J. R., Vidal, J. R. & Reisch, B. I. in Transgenic Plants: Methods and Protocols (ed. Peña, L.) 61–78 (Humana, 2004).

  66. Wong, M. H. et al. Lipid exchange envelope penetration (LEEP) of nanoparticles for plant engineering: a universal localization mechanism. Nano Lett. 16, 1161–1172 (2016).

    Article  CAS  Google Scholar 

  67. Gupta, S. et al. Portable Raman leaf-clip sensor for rapid detection of plant stress. Sci. Rep. 10, 20206 (2020). A portable, handheld Raman sensor designed to clip onto leaves was used for rapid detection of nutrient deficiency in a range of crops.

    Article  CAS  Google Scholar 

  68. Montanha, G. S. et al. X-ray fluorescence spectroscopy (XRF) applied to plant science: challenges towards in vivo analysis of plants. Metallomics 12, 183–192 (2020).

    Article  CAS  Google Scholar 

  69. Sadoine, M. et al. Designs, applications, and limitations of genetically encoded fluorescent sensors to explore plant biology. Plant Physiol. 187, 485–503 (2021).

    Article  CAS  Google Scholar 

  70. Dakir, A., Zahra, B. F. & Omar, A. B. Optical satellite images services for precision agricultural use: a review. Adv. Sci. Technol. Eng. Syst. J. 6, 326–331 (2021).

    Article  Google Scholar 

  71. Ruwanpathirana, G. P. et al. Continuous monitoring of plant sodium transport dynamics using clinical PET. Plant Methods 17, 8 (2021). PET enables continuous, whole-plant, 3D visualization of long-distance Na+ transport dynamics.

    Article  CAS  Google Scholar 

  72. Sophocleous, M. & Atkinson, J. K. A review of screen-printed silver/silver chloride (Ag/AgCl) reference electrodes potentially suitable for environmental potentiometric sensors. Sens. Actuators A Phys. 267, 106–120 (2017).

    Article  CAS  Google Scholar 

  73. Inzelt, G. in Handbook of Reference Electrodes (eds Inzelt, G., Lewenstam, A. & Scholz, F.) 331–332 (Springer, 2013).

  74. Waleed Shinwari, M. et al. Microfabricated reference electrodes and their biosensing applications. Sensors 10, 1679–1715 (2010).

    Article  Google Scholar 

  75. Morales, M. A. & Halpern, J. M. Guide to selecting a biorecognition element for biosensors. Bioconjug. Chem. 29, 3231–3239 (2018).

    Article  CAS  Google Scholar 

  76. Westbroek, P. in Analytical Electrochemistry in Textiles (eds Westbroek, P., Priniotakis, G. & Kiekens, P.) 3–36 (2005).

  77. Søpstad, S., Johannessen, E. A. & Imenes, K. Analytical errors in biosensors employing combined counter/pseudo-reference electrodes. Results Chem. 2, 100028 (2020).

    Article  Google Scholar 

  78. Cao, S. et al. ISFET-based sensors for (bio)chemical applications: a review. Electrochem. Sci. Adv. https://doi.org/10.1002/ELSA.202100207 (2022).

    Article  Google Scholar 

  79. Srinivasan, P., Ezhilan, M., Kulandaisamy, A. J., Babu, K. J. & Rayappan, J. B. B. Room temperature chemiresistive gas sensors: challenges and strategies — a mini review. J. Mater. Sci. Mater. Electron. 30, 15825–15847 (2019).

    Article  CAS  Google Scholar 

  80. Esser, B., Schnorr, J. M. & Swager, T. M. Selective detection of ethylene gas using carbon nanotube-based devices: utility in determination of fruit ripeness. Angew. Chem. Int. Ed. 51, 5752–5756 (2012).

    Article  CAS  Google Scholar 

  81. Li, Z. et al. Real-time monitoring of plant stresses via chemiresistive profiling of leaf volatiles by a wearable sensor. Matter 4, 2553–2570 (2021). Kirigami-inspired, lightweight, wearable, e-nose-style sensor for the detection and prediction of pathogenic infection by VOC release.

    Article  CAS  Google Scholar 

  82. Cui, S., Ling, P., Zhu, H. & Keener, H. M. Plant pest detection using an artificial nose system: a review. Sensors 18, 378 (2018).

    Article  Google Scholar 

  83. Yin, H. et al. Soil sensors and plant wearables for smart and precision agriculture. Adv. Mater. 33, 2007764 (2021).

    Article  CAS  Google Scholar 

  84. Calisgan, S. D. et al. Micromechanical switch-based zero-power chemical detectors for plant health monitoring. J. Microelectromech. Syst. 29, 755–761 (2020).

    Article  CAS  Google Scholar 

  85. Felle, H. Proton transport and pH control in Sinapis alba root hairs: a study carried out with double-barrelled pH micro-electrodes. J. Exp. Bot. 38, 340–354 (1987).

    Article  CAS  Google Scholar 

  86. Felle, H. H. The apoplastic pH of the Zea mays root cortex as measured with pH-sensitive microelectrodes: aspects of regulation. J. Exp. Bot. 49, 987–995 (1998).

    Article  CAS  Google Scholar 

  87. Izumi, R. et al. in Proc. 2017 IEEE Sensors (IEEE, 2017).

  88. Martinière, A., Desbrosses, G., Sentenac, H. & Paris, N. Development and properties of genetically encoded pH sensors in plants. Front. Plant Sci. 4, 523 (2013).

    Article  Google Scholar 

  89. Gjetting, S. K., Ytting, C. K., Schulz, A. & Fuglsang, A. T. Live imaging of intra- and extracellular pH in plants using pHusion, a novel genetically encoded biosensor. J. Exp. Bot. 63, 3207–3218 (2012).

    Article  CAS  Google Scholar 

  90. Tantama, M., Hung, Y. P. & Yellen, G. Imaging intracellular pH in live cells with a genetically encoded red fluorescent protein sensor. J. Am. Chem. Soc. 133, 10034–10037 (2011).

    Article  CAS  Google Scholar 

  91. Fujimaki, S. et al. Base to tip and long-distance transport of sodium in the root of common reed [Phragmites australis (Cav.) Trin. ex Steud.] at steady state under constant high-salt conditions. Plant Cell Physiol. 56, 943–950 (2015).

    Article  CAS  Google Scholar 

  92. Nyein, H. Y. Y. et al. A wearable electrochemical platform for noninvasive simultaneous monitoring of Ca2+ and pH. ACS Nano 10, 7216–7224 (2016).

    Article  CAS  Google Scholar 

  93. Keene, S. T. et al. Wearable organic electrochemical transistor patch for multiplexed sensing of calcium and ammonium ions from human perspiration. Adv. Healthc. Mater. 8, 1901321 (2019).

    Article  CAS  Google Scholar 

  94. Pirovano, P. et al. A wearable sensor for the detection of sodium and potassium in human sweat during exercise. Talanta 219, 121145 (2020).

    Article  CAS  Google Scholar 

  95. Gao, W. et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016).

    Article  CAS  Google Scholar 

  96. Bandodkar, A. J. et al. Epidermal tattoo potentiometric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring. Biosens. Bioelectron. 54, 603–609 (2014).

    Article  CAS  Google Scholar 

  97. Schazmann, B. et al. A wearable electrochemical sensor for the real-time measurement of sweat sodium concentration. Anal. Methods 2, 342–348 (2010).

    Article  CAS  Google Scholar 

  98. Garcia-Cordero, E. et al. Three-dimensional integrated ultra-low-volume passive microfluidics with ion-sensitive field-effect transistors for multiparameter wearable sweat analyzers. ACS Nano 12, 12646–12656 (2018).

    Article  CAS  Google Scholar 

  99. Parrilla, M. et al. Wearable potentiometric ion patch for on-body electrolyte monitoring in sweat: toward a validation strategy to ensure physiological relevance. Anal. Chem. 91, 8644–8651 (2019).

    Article  CAS  Google Scholar 

  100. Demuru, S., Kunnel, B. P. & Briand, D. Real-time multi-ion detection in the sweat concentration range enabled by flexible, printed, and microfluidics-integrated organic transistor arrays. Adv. Mater. Technol. 5, 2000328 (2020).

    Article  CAS  Google Scholar 

  101. Zhai, Q. et al. Vertically aligned gold nanowires as stretchable and wearable epidermal ion-selective electrode for noninvasive multiplexed sweat analysis. Anal. Chem. 92, 4647–4655 (2020).

    Article  CAS  Google Scholar 

  102. Parrilla, M. et al. A textile-based stretchable multi-ion potentiometric sensor. Adv. Healthc. Mater. 5, 996–1001 (2016).

    Article  CAS  Google Scholar 

  103. Kim, M.-Y. et al. Highly stable potentiometric sensor with reduced graphene oxide aerogel as a solid contact for detection of nitrate and calcium ions. J. Electroanal. Chem. 897, 115553 (2021).

    Article  CAS  Google Scholar 

  104. Jiao, Y. et al. in Int. Conf. Solid-State Sensors Actuators Microsystems Eurosensors XXXIII 37–40 (IEEE, 2019).

  105. Lu, Y. et al. Multimodal plant healthcare flexible sensor system. ACS Nano 14, 10966–10975 (2020).

    Article  CAS  Google Scholar 

  106. Oren, S., Ceylan, H., Schnable, P. S. & Dong, L. High-resolution patterning and transferring of graphene-based nanomaterials onto tape toward roll-to-roll production of tape-based wearable sensors. Adv. Mater. Technol. 2, 1700223 (2017).

    Article  Google Scholar 

  107. Kim, J. J., Allison, L. K. & Andrew, T. L. Vapor-printed polymer electrodes for long-term, on-demand health monitoring. Sci. Adv. 5, eaaw0463 (2019).

    Article  CAS  Google Scholar 

  108. Lee, K. et al. In-situ synthesis of carbon nanotube–graphite electronic devices and their integrations onto surfaces of live plants and insects. Nano Lett. 14, 2647–2654 (2014). Direct application of electrochemical sensors onto the leaf surface for the detection of gaseous analytes.

    Article  CAS  Google Scholar 

  109. Koman, V. B. et al. Persistent drought monitoring using a microfluidic-printed electro-mechanical sensor of stomata: in planta. Lab Chip 17, 4015–4024 (2017).

    Article  CAS  Google Scholar 

  110. Chauhan, S., Srivastava, H. S. & Patel, P. Wheat crop biophysical parameters retrieval using hybrid-polarized RISAT-1 SAR data. Remote Sens. Environ. 216, 28–43 (2018).

    Article  Google Scholar 

  111. Grimnes, S. & Martinsen, Ø. G. Bioimpedance and Bioelectricity Basics 179–254 (Elsevier, 2015).

  112. Xu, Q. et al. Microsensor in vivo monitoring of oxidative burst in oilseed rape (Brassica napus L.) leaves infected by Sclerotinia sclerotiorum. Anal. Chim. Acta 632, 21–25 (2009). Insertable Pt-based sensor for detecting successive bursts of ROS in plants with fungal infection.

    Article  CAS  Google Scholar 

  113. Tangkuaram, T., Ponchio, C., Kangkasomboon, T., Katikawong, P. & Veerasai, W. Design and development of a highly stable hydrogen peroxide biosensor on screen printed carbon electrode based on horseradish peroxidase bound with gold nanoparticles in the matrix of chitosan. Biosens. Bioelectron. 22, 2071–2078 (2007).

    Article  CAS  Google Scholar 

  114. Lu, S.-Y., Chen, Y., Fang, X. & Feng, X. Hydrogen peroxide sensor based on electrodeposited Prussian blue film. J. Appl. Electrochem. 47, 1261–1271 (2017).

    Article  CAS  Google Scholar 

  115. Niemeyer, J., Scheuring, D., Oestreicher, J., Morgan, B. & Schroda, M. Real-time monitoring of subcellular H2O2 distribution in Chlamydomonas reinhardtii. Plant Cell 33, 2935–2949 (2021).

    Article  Google Scholar 

  116. Hernández-Barrera, A. et al. Using hyper as a molecular probe to visualize hydrogen peroxide in living plant cells: a method with virtually unlimited potential in plant biology. Methods Enzymol. 527, 275–290 (2013).

    Article  Google Scholar 

  117. Ugalde, J. M., Schlößer, M., Dongois, A., Martinière, A. & Meyer, A. J. The latest HyPe(r) in plant H2O2 biosensing. Plant Physiol. 187, 480–484 (2021).

    Article  CAS  Google Scholar 

  118. Lew, T. T. S. et al. Real-time detection of wound-induced H2O2 signalling waves in plants with optical nanosensors. Nat. Plants 6, 404–415 (2020).

    Article  CAS  Google Scholar 

  119. Giraldo, J. P. et al. Plant nanobionics approach to augment photosynthesis and biochemical sensing. Nat. Mater. 13, 400–408 (2014).

    Article  CAS  Google Scholar 

  120. Giraldo, J. P. et al. A ratiometric sensor using single chirality near-infrared fluorescent carbon nanotubes: application to in vivo monitoring. Small 11, 3973–3984 (2015).

    Article  CAS  Google Scholar 

  121. Gan, T., Hu, C., Chen, Z. & Hu, S. A disposable electrochemical sensor for the determination of indole-3-acetic acid based on poly(safranine T)-reduced graphene oxide nanocomposite. Talanta 85, 310–316 (2011).

    Article  CAS  Google Scholar 

  122. Li, H. et al. A highly sensitive electrochemical impedance immunosensor for indole-3-acetic acid and its determination in sunflowers under salt stress. RSC Adv. 7, 54416–54421 (2017).

    Article  CAS  Google Scholar 

  123. Sun, L. J. et al. Paper-based electroanalytical devices for in situ determination of salicylic acid in living tomato leaves. Biosens. Bioelectron. 60, 154–160 (2014).

    Article  CAS  Google Scholar 

  124. Yang, L. et al. Ratiometric electrochemical sensor for accurate detection of salicylic acid in leaves of living plants. RSC Adv. 10, 38841–38846 (2020).

    Article  CAS  Google Scholar 

  125. Li, Y.-W., Xia, K., Wang, R.-Z., Jiang, J.-H. & Xiao, L.-T. An impedance immunosensor for the detection of the phytohormone abscisic acid. Anal. Bioanal. Chem. 391, 2869–2874 (2008).

    Article  CAS  Google Scholar 

  126. Brunoud, G. et al. A novel sensor to map auxin response and distribution at high spatio-temporal resolution. Nature 482, 103–106 (2012).

    Article  CAS  Google Scholar 

  127. Waadt, R. et al. FRET-based reporters for the direct visualization of abscisic acid concentration changes and distribution in Arabidopsis. eLife 3, e01739 (2014).

    Article  Google Scholar 

  128. Larrieu, A. et al. A fluorescent hormone biosensor reveals the dynamics of jasmonate signalling in plants. Nat. Commun. 6, 6043 (2015).

    Article  CAS  Google Scholar 

  129. Zhang, H. & Wang, J. Detection of age and insect damage incurred by wheat, with an electronic nose. J. Stored Prod. Res. 43, 489–495 (2007).

    Article  Google Scholar 

  130. Li, C., Krewer, G. & Kays, S. J. in 2009 Reno, Nevada, June 21–June 24 Vol. 8 5289–5301 (American Society of Agricultural and Biological Engineers, 2009).

  131. Sankaran, S., Mishra, A., Ehsani, R. & Davis, C. A review of advanced techniques for detecting plant diseases. Comput. Electron. Agric. 72, 1–13 (2010).

    Article  Google Scholar 

  132. Baker, M. J., Hughes, C. S. & Hollywood, K. A. Biophotonics: Vibrational Spectroscopic Diagnostics Ch. 3 (Morgan & Claypool, 2016).

  133. Nißler, R. et al. Detection and imaging of the plant pathogen response by near-infrared fluorescent polyphenol sensors. Angew. Chem. Int. Ed. 61, e202108373 (2022).

    Google Scholar 

  134. Galieni, A. et al. Past and future of plant stress detection: an overview from remote sensing to positron emission tomography. Front. Plant Sci. 11, 609155 (2021).

    Article  Google Scholar 

  135. Weiss, M., Jacob, F. & Duveiller, G. Remote sensing for agricultural applications: a meta-review. Remote Sens. Environ. 236, 111402 (2020).

    Article  Google Scholar 

  136. Wójtowicz, M., Wójtowicz, A. & Piekarczyk, J. Application of remote sensing methods in agriculture. Commun. Biometry Crop Sci. 11, 31–50 (2016).

    Google Scholar 

  137. Huang, S., Tang, L., Hupy, J. P., Wang, Y. & Shao, G. A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. J. For. Res. 32, 1–6 (2021).

    Article  Google Scholar 

  138. Beisel, N. S. et al. Utilization of single-image normalized difference vegetation index (SI-NDVI) for early plant stress detection. Appl. Plant Sci. 6, e01186 (2018).

    Article  Google Scholar 

  139. Zubler, A. V. & Yoon, J. Y. Proximal methods for plant stress detection using optical sensors and machine learning. Biosensors 10, 193 (2020).

    Article  CAS  Google Scholar 

  140. Gao, Z., Luo, Z., Zhang, W., Lv, Z. & Xu, Y. Deep learning application in plant stress imaging: a review. AgriEngineering 2, 430–446 (2020).

    Article  Google Scholar 

  141. Ma, J. et al. A recognition method for cucumber diseases using leaf symptom images based on deep convolutional neural network. Comput. Electron. Agric. 154, 18–24 (2018).

    Article  Google Scholar 

  142. Esgario, J. G. M., Krohling, R. A. & Ventura, J. A. Deep learning for classification and severity estimation of coffee leaf biotic stress. Comput. Electron. Agric. 169, 105162 (2020).

    Article  Google Scholar 

  143. Pérez-Clemente, R. M. et al. Biotechnological approaches to study plant responses to stress. BioMed. Res. Int. 2013, 654120 (2013).

    Article  Google Scholar 

  144. Arbona, V., Manzi, M., Ollas, Cde & Gómez-Cadenas, A. Metabolomics as a tool to investigate abiotic stress tolerance in plants. Int. J. Mol. Sci. 14, 4885–4911 (2013).

    Article  CAS  Google Scholar 

  145. Shulaev, V., Cortes, D., Miller, G. & Mittler, R. Metabolomics for plant stress response. Physiol. Plant 132, 199–208 (2008).

    Article  CAS  Google Scholar 

  146. Krishnan, P., Kruger, N. J. & Ratcliffe, R. G. Metabolite fingerprinting and profiling in plants using NMR. J. Exp. Bot. 56, 255–265 (2005).

    Article  CAS  Google Scholar 

  147. Widodo, W. et al. Metabolic responses to salt stress of barley (Hordeum vulgare L.) cultivars, Sahara and Clipper, which differ in salinity tolerance. J. Exp. Bot. 60, 4089–4103 (2009).

    Article  CAS  Google Scholar 

  148. Michaletti, A., Naghavi, M. R., Toorchi, M., Zolla, L. & Rinalducci, S. Metabolomics and proteomics reveal drought-stress responses of leaf tissues from spring-wheat. Sci. Rep. 8, 5710 (2018).

    Article  Google Scholar 

  149. Djoukeng, J. D., Arbona, V., Argamasilla, R. & Gomez-Cadenas, A. Flavonoid profiling in leaves of citrus genotypes under different environmental situations. J. Agric. Food Chem. 56, 11087–11097 (2008).

    Article  CAS  Google Scholar 

  150. Sprenger, H. et al. Metabolite and transcript markers for the prediction of potato drought tolerance. Plant Biotechnol. J. 16, 939–950 (2018).

    Article  CAS  Google Scholar 

  151. Li, Z. et al. Non-invasive plant disease diagnostics enabled by smartphone-based fingerprinting of leaf volatiles. Nat. Plants 5, 856–866 (2019). A colorimetric-based VOC fingerprinting smartphone sensing setup with diagnosis of infection through modelling.

    Article  CAS  Google Scholar 

  152. Lee, G., Wei, Q. & Zhu, Y. Emerging wearable sensors for plant health monitoring. Adv. Funct. Mater. 31, 2106475 (2021).

    Article  CAS  Google Scholar 

  153. Nassar, J. M. et al. Compliant plant wearables for localized microclimate and plant growth monitoring. npj Flex. Electron. 2, 24 (2018).

    Article  Google Scholar 

  154. Tang, W., Yan, T., Ping, J., Wu, J. & Ying, Y. Rapid fabrication of flexible and stretchable strain sensor by chitosan-based water ink for plants growth monitoring. Adv. Mater. Technol. 2, 1700021 (2017).

    Article  Google Scholar 

  155. Diacci, C. et al. Diurnal in vivo xylem sap glucose and sucrose monitoring using implantable organic electrochemical transistor sensors. iScience 24, 101966 (2021).

    Article  CAS  Google Scholar 

  156. Rawson, T. M. et al. Microneedle biosensors for real-time, minimally invasive drug monitoring of phenoxymethylpenicillin: a first-in-human evaluation in healthy volunteers. Lancet Digit. Health 1, e335–e343 (2019).

    Article  Google Scholar 

  157. Stavrinidou, E. et al. In vivo polymerization and manufacturing of wires and supercapacitors in plants. Proc. Natl Acad. Sci. USA 114, 2807–2812 (2017).

    Article  CAS  Google Scholar 

  158. Liu, J. et al. Syringe-injectable electronics. Nat. Nanotechnol. 10, 629–636 (2015).

    Article  CAS  Google Scholar 

  159. Olenik, S., Lee, H. S. & Güder, F. The future of near-field communication-based wireless sensing. Nat. Rev. Mater. 6, 286–288 (2021).

    Article  CAS  Google Scholar 

  160. Romanholo, P. V. V. et al. Biomimetic electrochemical sensors: new horizons and challenges in biosensing applications. Biosens. Bioelectron. 185, 113242 (2021).

    Article  CAS  Google Scholar 

  161. Li, B. et al. Toward long-term accurate and continuous monitoring of nitrate in wastewater using poly(tetrafluoroethylene) (PTFE)–solid-state ion-selective electrodes (S-ISEs). ACS Sens. 5, 3182–3193 (2020).

    Article  Google Scholar 

  162. Liu, X., You, S., Ma, F. & Zhou, H. Characterization of electrode fouling during electrochemical oxidation of phenolic pollutant. Front. Environ. Sci. Eng. 15, 53 (2021).

    Article  CAS  Google Scholar 

  163. Hanssen, B. L., Siraj, S. & Wong, D. K. Y. Recent strategies to minimise fouling in electrochemical detection systems. Rev. Anal. Chem. 35, 1–28 (2016).

    Article  CAS  Google Scholar 

  164. Kusoglu, A. & Weber, A. Z. New insights into perfluorinated sulfonic-acid ionomers. Chem. Rev. 117, 987–1104 (2017).

    Article  CAS  Google Scholar 

  165. Kwak, S. Y. et al. Chloroplast-selective gene delivery and expression in planta using chitosan-complexed single-walled carbon nanotube carriers. Nat. Nanotechnol. 14, 447–455 (2019).

    Article  CAS  Google Scholar 

  166. Demirer, G. S. et al. High aspect ratio nanomaterials enable delivery of functional genetic material without DNA integration in mature plants. Nat. Nanotechnol. 14, 456–464 (2019).

    Article  CAS  Google Scholar 

  167. Voke, E., Pinals, R. L., Goh, N. S. & Landry, M. P. In planta nanosensors: understanding biocorona formation for functional design. ACS Sens. 6, 2802–2814 (2021).

    Article  CAS  Google Scholar 

  168. Xu, Y., Zhang, P., Liu, X., Wang, Z. & Li, S. Preparation and irreversible inhibition mechanism insight into a recombinant Kunitz trypsin inhibitor from Glycine max L. seeds. Appl. Biochem. Biotechnol. 191, 1207–1222 (2020).

    Article  CAS  Google Scholar 

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Acknowledgements

F.G. thanks the Bill and Melinda Gates Foundation (Grand Challenges Explorations scheme under grant number OPP1212574) and the US Army (U.S. Army Foreign Technology (and Science) Assessment Support programme under grant number W911QY-20-R-0022) for their generous support. L.G.-M. acknowledges the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 101025390. F.G., P.C. and A.S.P.C. thank EPSRC (EP/L016702/1) and BBSRC DTP (reference 2177734). T.B. acknowledges BBSRC (BB/T006102/1) for their support. F.G. and P.C. thank the Imperial College Centre for Processable Electronics (CPE). F.G. also acknowledges Agri Futures Lab.

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Authors and Affiliations

  1. Department of Bioengineering, Royal School of Mines, Imperial College London, London, UK

    Philip Coatsworth, Laura Gonzalez-Macia, Alexander Silva Pinto Collins & Firat Güder

  2. Department of Life Sciences, Royal School of Mines, Imperial College London, London, UK

    Tolga Bozkurt

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P.C., L.G.-M. and F.G. conceived the structure of the manuscript. P.C. led the writing of the manuscript. All authors contributed to the writing and reviewed and agreed on the manuscript before submission.

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Glossary

Avirulent

Not capable of causing disease.

Bioimpedance spectroscopy

A non-invasive electrochemical spectroscopic technique for the measurement of electrical impedance of biological samples.

Effector-triggered immunity

(ETI). A stronger immune response triggered upon detection of effector proteins released by the pathogen.

Electrical impedance

The opposition to electrical flow.

Electrodic technique

A technique measuring properties at the electrode–electrolyte interface.

Genetic transformations

Insertion and incorporation of exogenous genetic material into a host organism.

Oomycetes

Fungus-like filamentous microorganisms.

PAMP-triggered immunity

(PTI). The primary plant immunity response, triggered when PAMPs are detected by recognition receptors in plants.

Pathogen-associated molecular patterns

(PAMPs). Structural molecular components of pathogens that are recognized by receptors in plants, triggering an immune response.

Phloem

Living tissue that transports soluble organic compounds (especially sugars) produced during photosynthesis around the plant.

Protease inhibitors

Large variety of antiherbivore molecules (mostly proteins) that inhibit protease enzyme function to reduce herbivore digestion.

Stomata

Pores on the epidermis of leaves that control exchange of CO2 and water vapour with the environment.

Stomatal aperture

The width of the pore size of a stoma as controlled by the two guard cells.

Synthetic-aperture radar

A remote imaging technique involving the transmission and reception of sequential electromagnetic waves by a device on a moving platform.

Virulent

Capable of causing disease.

Xylem

Vascular tissue that transports water and dissolved nutrients up from the roots to other organs.

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Coatsworth, P., Gonzalez-Macia, L., Collins, A.S.P. et al. Continuous monitoring of chemical signals in plants under stress. Nat Rev Chem 7, 7–25 (2023). https://doi.org/10.1038/s41570-022-00443-0

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