Detecting Apple Valsa Canker (AVC) at an Early Stage Using Micro-SERS Combined with Chemical Imaging Analysis
摘要
Surface-enhanced Raman scattering (SERS) spectroscopy with simplified detection procedures and improved detection efficiency is a potential method for plant disease detection. This chapter details how to detect Apple Valsa canker (AVC) with early incubation using micro-SERS combined with chemical imaging analysis. Chemometrics was used to eliminate the interference of baseline shifts. Machine learning methods were utilized to establish discriminative models to detect of the AVC disease stage. Further, chemical distribution imaging was successfully applied to the analysis of disease dynamics.