Rapid detection and identification of crop pathogens is essential for improving crop yield. Typical pathogen assaying methods, such as polymerase chain reaction (PCR) or enzyme-linked immunosorbent assay (ELISA), are time-consuming and destructive to the sample. Raman spectroscopy (RS) is a noninvasive nondestructive analytical technique that provides insight on the chemical structure of the specimen. In this study, we demonstrate that using a hand-held Raman spectrometer, in combination with chemometric analyses, we can distinguish between healthy and diseased maize ( Zea mays) kernels, as well as between different diseases with 100% accuracy. Our analysis is portable and sample-agnostic, suggesting that it could be retooled for other crops and conducted autonomously.