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Global population growth drives increasing food demand, which is anticipated to increase by at least 20% over the next 15 years. Rapid detection and identification of plant pathogens allows for up to a 50% increase in the total agricultural yield worldwide. Current molecular methods for pathogen diagnostics, such as polymerase chain reaction (PCR), are costly, time-consuming, and destructive. These limitations recently catalyzed a push toward developing minimally invasive and substrate general techniques that can be used in the field for confirmatory detection and identification of plant pathogens. Raman spectroscopy (RS) is a noninvasive, nondestructive, and label-free technique that can be used to determine chemical structure of analyzed specimens. In this study, we demonstrate that by using a hand-held Raman spectrometer, we can identify whether wheat or sorghum grains are healthy or not and identify present plant pathogens. We show that RS enables diagnosis of simple diseases, such as ergot, that are caused by one pathogen, as well as complex diseases, such as black tip or mold, which are induced by several different pathogens. The combination of chemometric analysis and RS allows for distinguishing between healthy and infected grains with high accuracy. We also show that RS can be used to determine states of disease development on grain. These results demonstrate that Raman-based approach for disease detection on plants is sample agnostic.
Egging et al. (Wed,) studied this question.