Proposal of a system based on direct and indirect techniques and their correlation by chlorophyll quantification

Abstract

The prediction of normalized vegetation indices in coffee crops using multispectral images obtained by aerial mapping aims to generate a technological strategy using aerial mapping employing drones (RPAS) to predict normalized vegetation index (ENDVI) in coffee crops. During the research process, reference is made to the ENDVI according to the multispectral footprints generated by the different nutrients on the plants in the production stage of the coffee crop, using RPAS for the realization of aerial mapping works in precision agriculture. This reflects the importance of implementing technological tools to improve the planning of agricultural activities, predict damage and decide in situations that affect the development of coffee crops. This study took multispectral images of coffee crops from aerial mapping in the coffee plantations of the Popayan plateau region. It will also analyze the health status of the plants using a chlorophyll meter. From this comparative analysis of the different ENDVI, it is possible to define management alternatives to improve production. However, the images will be captured with unique cameras incorporated in the RPAS, allowing the identification of the variations of the lots and coffee plants in the formative stage of their phenological development, the absorption of nutrients, and the water stress of the crop. Finally, some strategies for integrating expert systems in aerial mapping are proposed.