Contribution of UAV-airborne imagery in the study of machine-soil-plant interaction in potato cultivation

Abstract

The use of new technologies in precision agriculture remains a solution for global demographic change and its food needs in the face of climate change. The experiment was based on the vegetative cycle monitoring of a "Spunta" variety potato crop grown at different inter-lines, spacing and planting depths based on the RGB imaging technique using a sophisticated drone-mounted sensor. In order to improve the production system and adapt it to the context of global warming through the different settings on the potato planter machine, vegetation indices have been calculated from the captured images such as the GA, GGA, CSI, NGDRI et TGI indices, indicators of the plant biomass and its healthy state thus leading to a correct decision in terms of nutrient input and phytosanitary treatment. The following factors combination of inter-row spacing, plant spacing and planting depth IL = 90 cm, IP = 28 cm, and P = 10 cm respectively proved potato size and yield better results.