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

  • Philip Coatsworth
  • , Yasin Cotur
  • , Atharv Naik
  • , Tarek Asfour
  • , Alex Silva Pinto Collins
  • , Selin Olenik
  • , Zihao Zhou
  • , Laura Gonzalez-Macia
  • , Dai Yin Chao
  • , Tolga Bozkurt
  • , Firat Güder
  • Imperial College London
  • Department of Bioengineering
  • Chinese Academy of Sciences

Research output: Contribution to journalArticlepeer-review

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Abstract

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.

Original languageEnglish
Number of pages14
JournalScience Advances
Volume10
Issue number5
DOIs
Publication statusPublished - 2 Feb 2024

Data Availability Statement

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.

Acknowledgements

We would like to thank the department of Bioengineering at the imperial College london and the imperial College Centre for Processable electronics (CPe).

Funding

this work was supported by ePSRC, eP/l016702/1 (to F.G. and P.C.); BBSRC dtP, Reference:2177734 (to F.G. and A.S.-P.C.); the Bill and Melinda Gates Foundation (Grand Challenges explorations scheme under grant number: OPP1212574 and investment id inv- 038695) (toF.G. and l.G.-M.); the US Army [US Army Foreign technology (and Science) Assessment Support program under grant number: W911QY-20- R- 0022] (to F.G.); the european Union’s horizon2020 research and innovation program under the Marie Sklodowska-Curie grant agreement no. 101025390 (to l.G.- M.); BBSRC, BB/t006102/1 (to t.B.); the imperial President’s Ph.d. Scholarship (to S.O.); the turkish Ministry of education (to Y.C.); ePSRC iAA (to Y.C.); the AgriFutures lab (to F.G.); and innovate UK (grant reference: 10004425) (to t.A.).

ASJC Scopus subject areas

  • General

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