Non-invasive Raman spectroscopy for plant phenotyping and health diagnostics

Overview

This solution leverages Raman spectroscopy as a digital farming tool for plant phenotyping and confirmatory diagnostics of plant health. The technology probes plant metabolism, which changes in characteristic ways when plants experience biotic or abiotic stresses. Because these metabolic signatures are unique and detectable, Raman enables confirmatory identification of viral, bacterial, and fungal diseases, as well as stresses such as drought, salinity, and herbicide resistance. The approach can also differentiate isogenic lines, plant varieties, and species, making it valuable for both crop health management and breeding programs.

The method is label-free, non-invasive, and non-destructive, allowing repeated measurements on the same plant without damaging tissue or requiring sample preparation. This makes it well suited for in-field and greenhouse use, where speed and ease of use are critical.

Technical specifications

• Spectroscopic detection of plant metabolism enables confirmatory identification of biotic and abiotic stresses based on metabolic fingerprints
• Broad diagnostic range covers viral, bacterial, and fungal diseases, as well as drought, salinity, and glyphosate resistance in weeds
• Phenotyping capability allows differentiation of isogenic lines, plant varieties, and plant species
• Label-free and non-destructive measurements preserve plant integrity and enable repeated sampling
• Chemometric modeling is used to convert spectral data into confirmatory identification outputs
• Software integration is being developed for deployment on commercially available handheld Raman spectrometers, enabling use by plant breeders and farmers in field settings

Technology readiness level

The underlying Raman-based diagnostic approach has been validated through multiple peer-reviewed studies demonstrating its ability to detect and distinguish a range of plant stresses and phenotypes. Current and planned validation efforts focus on extending the technology to determine nematode resistance in peanuts, with collaboration from the Texas A&M Research Center to build a spectroscopic library of at least 20 nematode-resistant and susceptible peanut varieties. Chemometric models will be developed from this library to enable confirmatory identification of resistance. The ultimate commercialization goal is a software package combining spectroscopic libraries and chemometric models that can be uploaded onto handheld Raman spectrometers for use by breeders and farmers.