Previous research has shown that the application of reduced doses of Silicon (Si) improves crop tolerance to water stress, which is common in commercial young peach trees because irrigation is not usually applied during their first two years. In this study, aerial images were used to monitor the impact of different Si and water treatments on the hyperspectral response of peach trees. An experiment with 60 young (under 1 year old) peach trees located at the Musser Fruit Research Center (Seneca, SC, USA) was assessed in three different dates. The small trees were planted on pots and placed in a umbraculum, although were moved outdoors during image acquisition. The treatments consisted of 30 water-stressed trees and 30 irrigated trees, and then each group was divided into 5 subsets of 6 trees each, to which doses of 2 and 4 ppm of two Si products were applied, plus the remaining subset being the control. One product was pure Si at such concentrations, and the other product was Si of a commercial brand, which were applied at various times throughout the study (September 16^th, September 27^th, October 4^th, October 11^th, October 17^th, October 24^th and November 1^st, 2019). Information on the nutrient and water tree status was frequently measured with leaf analysis and a Scholander pressure chamber, respectively. The aerial images were collected with the HSC-2 Senop camera mounted in a hexacopter drone model DJI Matrice 600 Pro on September 19^th, October 2^nd and November 13^th, 2019. This camera took the images at 20 m altitude and between 500-900 nm of spectral range, 1.0 nm of bandwidth, 1 megapixel of resolution (1,024 x 1,024 pixels), and 12 bits of radiometric resolution. The images had a spatial resolution of 2.5 cm/pixel. The processing of the hyperspectral images involved the following phases: 1) image georeferencing and mosaicking, 2) radiometric correction and transformation of raw pixel values to top-of-canopy reflectance, 3) image segmentation and classification of individual trees, and 4) retrieving of tree canopy values and analysis of hyperspectral signatures. A customized algorithm based on the object-based image analysis (OBIA) paradigm was also developed with the eCognition developer software to automatically isolate each peach tree and to retrieve spectral information at tree level. The comparison of the three ortho-mosaics of the peach experiment did show evidence of reflectance differences between extreme treatments, mainly in the green and near-infrared regions. The largest differences were observed between non-stressed trees withouth Si application (control trees) and non-stressed trees with pure Si application at a dose of 2 ppm in the green region, and between stressed trees with commercial Si application at a dose of 2 ppm and non-stressed trees with pure Si application at a dose of 4 ppm in the infrared region. However, further statistical multi-variable analysis will be applied to define those relevant wavelengths or vegetation indices to be used as indicators of Si nutrient content and water stress status with UAV-based hyperspectral images.