Multi-modal optical imaging system for seed pathogen viability testing
A multi-modal imaging system combining multi-spectral imaging and laser biospeckle imaging to assess seed health and pathogen viability in solanaceous crops affected by tobamoviruses. The non-destructive approach captures complementary optical and biological activity signals, supporting differentiation between viable and non-viable pathogens. AI models can be trained to improve interpretation, with performance intended to be comparable to PCR while remaining scalable and cost-effective for agricultural use.
Overview
The proposed multi-modal optical imaging system integrates multi-spectral imaging (MSI) and laser biospeckle imaging (LBI) to improve evaluation of seed health, specifically for detecting pathogen viability in solanaceous crops affected by tobamoviruses. This combination provides a non-destructive method that captures both optical and biological activity data, aiming to deliver more comprehensive analysis than monomodal systems.
The system is intended to produce outcomes comparable to PCR results, while offering a scalable, adaptable, and cost-effective solution for agricultural applications.
Technical specifications
The system includes:
- A laser with a stable current driver
- A broadband light source
- Optical filters for wavelength selection
- Linear polarizers to reduce specular reflections
- A camera for data capture
MSI measures changes in optical properties, while LBI captures biological activity signatures. Together, these modalities support differentiation between viable and non-viable pathogens. The approach is designed to be adaptable across different crops and pathogens, with AI models trained to enhance data interpretation.
Technology readiness level
Currently at Technology Readiness Level 4, the system has been constructed and calibrated in preliminary studies. Initial data collection and evaluation have been conducted using relevant seed samples. Future work includes further validation and optimization to refine system parameters and improve AI model training.
About Xi’an Jiaotong-Liverpool University
Xi’an Jiaotong‑Liverpool University is a Sino‑British joint university in Suzhou, operating as a research‑led, internationally oriented institution. Its main campus in the Suzhou Dushu Lake Science and Education Innovation District of Suzhou Industrial Park gives companies access to a dense innovation ecosystem and nearby advanced manufacturing. The Entrepreneur College in Taicang runs industry‑themed schools and an embedded co‑education model that aligns talent pipelines and applied R&D with partner firms in a nearby high‑tech zone. Research is supported by competitive national, provincial and municipal programs in China, including awards from the National Natural Science Foundation of China. A dedicated Research Engagement and Innovation Office enables collaboration, technology transfer and IP management.
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