3D printed leaf biosensor

  • Mohamed Hassan

Student thesis: Phd


This interdisciplinary research project addresses the design and development of a multilayer and multi-material 3D printed leaf biosensor that enables the instantaneous on-site detection of Puccinia striiformis. The main challenge with the detection of this disease is that it can only be visually detected on the leaf surface after 14 days of infection, by when it’s too late for the use of fungicide, resulting in a significant yield loss. The objective of this research project is to develop an innovative and compact biosensor using advanced materials and additive manufacturing (3D Printing) allowing the early detection of Puccinia striiformis f. sp. tritici in the field enabling fast countermeasures to be taken. The biosensor will consist of 3 layers. The first layer will mimic the top layer of the leaf which is the cuticle layer that covers the leaf. The second layer consists of a sucrose/agar mixture to act as a substrate and growth cue. The third layer will consist of a nonenzymatic glucose sensor that produces a signal once the Puccinia striiformis f. sp. tritici invertase gets in contact with the second layer and produces glucose.
Date of Award1 Aug 2023
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorBruce Grieve (Supervisor) & Paulo Jorge Da Silva Bartolo (Supervisor)


  • Bioenginerring
  • Electrospinning
  • Electrochemistry
  • Characterisation
  • Yellow Rust
  • 3D printing
  • Biosensor
  • Smart materials

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