Hyperspectral imaging can generate spatial chemical information in plants. The imaging acquisition system is basically composed of a radiation source, sample stage, objective lens, spectrograph, CCD camera and a computer to store and process derived data. Most hyperspectral imaging acquisition approaches are nondestructive in nature and require minimum sample preparation, thus producing chemically rich information without modifying a sample’s features. Data processing is mainly performed via multivariate image analysis (MIA), where computed-based methods are employed for preprocessing, feature extraction and multivariate analysis towards classification. Applications vary according to the desired information of interest, but they mainly include textural analysis, chemical and biochemical analysis and plant disease identification. Successful studies in these areas reinforce the sensitivity and versatility of hyperspectral imaging in plants.