Project Overview

The overarching goal of this project is to rapidly, accurately, and cost-effectively detect incipient pathogens within greenhouses and more generally in agricultural operations. We will pursue this goal by developing, validating and translating an innovative PoPC technology which integrates cutting-edge technologies from the fields of nanophotonics, chemical synthesis, spectroscopy, artificial intelligence and automation.

This integration is enabled via seven principal sub-projects wherein the synergy there between results in a validated and commercially viable PoPC technology for the benefit of greenhouse operations in Ontario and beyond. Details of the sub-projects are defined bellow:

1 – Optimization of NPS element for maximal SERS intensity at the sensing surface:

The patented NPS element offers high electromagnetic field intensity localized within its nanofeatures. Considering the Raman scattering cross-section of molecules within pathogens, optimal plasmonic nanostructures will be designed to yield maximum achievable SERS intensity across multiple sensing wavelengths whereby the scattered Raman signal is not saturated nor damages the sample molecules. COMSOL Multiphysics modeling will be used to optimize the plasmonic nanostructure geometry and dimensions including accounting for the refractive index of the biomolecular species surrounding the high field regions (hotspots).

2 – Surface functionalization of the NPS elements (using antibodies to capture virulent pathogenic particles):

An immuno-functionalization method will be used wherein a Raman reporter is cross-linked between the antibody and the surface of the NPS element. Molecular weight and structure of different pathogenic particles will shift the SERS spectra of the Raman reporter. A detailed study will be performed to calibrate the shifts to the type and quantity of the pathogens.

3 – Designing a programmable robotic system for automatic and precise sample preparation:

Plant juice extraction from leaves includes parallel pipetting, transfer of liquid aliquots, and automatic centrifugation of the samples. The robotic system will transfer low volumes of the supernatants onto the exact coordinates of the NPS platform, reducing human error and increasing accuracy and efficiency.

4 – Design of a portable Raman spectrometer for a PoC detection system:

We will design a portable Raman spectrometer through the integration of various components amenable for point-of-care applications. The NPS element will be dropped (plugged) into the system – optimally situated on a piezoelectric stage to permit maximal laser light illumination and collection of scattered Raman photons.

5 – Detection of relevant pathogens using label-free and surface functionalization methods:

Examples of relevant pathogens include ToBRFV or tomato mosaic viruses, CGMMV or PMMV. Plant juice will be processed, first manually in a pilot phase and then automatically using robotics, followed by SERS detection of virulent strains using two methods (label-free and surface functionalization).

6 – Accurate and real-time data analysis using AI-ML based data processing techniques:

The SERS signal from label-free sensing will be processed using advanced AI techniques to detect, quantify and thus determine types and levels of virulent strains. Similar data analysis will be carried out for the SERS signal from surface-functionalized sensing elements to detect the spectral shift of the Raman reporter with respect to the captured pathogen.

7 – Technology validation of the PoPC technology through alpha and beta testing:

The developed technology will undergo multiple phases of proof-of-concept testing and will be updated/modified to precisely meet requirements for on-site plant disease testing. This is an important step for technology validation and ultimate commercialization of the product – that is, to assure its successful deployment in relation to traditional technologies.