Precision agriculture for rice crops with an emphasis in low health index areas

Abstract

The delimitation of affected areas by low health index in crops is a useful tool that let farmers implement a differentiated rice-crop management. The objective of this research was to analyze and determine these areas in rice crops. For this purpose, health index maps were combined with RGB maps, digital elevation models (DEM), and tridimensional models to monitor this culture. The study was conducted in farms located in the regions of Tortí and Darién in Panama. Unmanned aerial vehicles (UAV) or drones with multispectral and RGB cameras were used to obtain orthomosaics (RGB, NIR). A specialized mapper software was used to generate the calibrated health map, and Google Earth and AgriYttium (mobile app) were used as crop visualization tools for farmers. The virtual tour above farm plot through visual and tridimensional models facilitated inspection of crop zones with difficult access. Map analysis allowed identifying areas with low health index, low plant density, weed problem, yellowing, competition with other crops and steep slopes. This information was presented to the producers through printed and digital reports with detailed information about the polygonal surfaces and the proportion of affected areas in crops and recommendations regarding areas for reseeding, land leveling, and corrections in pesticide/fertilizer applications. This tool led to saving agrochemical products since the applications can be made on precise sites.