Hyperspectral analysis for plant characterization and discrimination

Hyperspectral analysis as a tool in the context of plant analysis (e.g., characterization and discrimination) has been demonstrating an enormous potential, and the number of applications is steadily increasing over the past decade. Combining plant spectral fingerprints (e.g., near-infrared, Raman, fluorescence, and THz spectroscopy) with imaging is actually an enormous advantage for these applications. Hyperspectral analysis requires a fundamentally different data analysis approach (if compared to the single point spectroscopy). Image analysis methods, combined with conventional spectral processing methods, are fundamental as the spatial mode is absolutely relevant for the analysis of hyperspectral data. This chapter provides a comprehensive review on the recent applications of hyperspectral analysis, considering different spectroscopic methods but focusing on vibrational spectroscopy, for plant analysis. A major relevance was given to applications dealing with plant species and cultivars discrimination.