Precision agriculture applied to coffee cultivation in agroforestry systems

Abstract

The search for more sustainable agricultural production systems is a goal of both agroforestry systems (AFS) and precision agriculture (PA). In this context, integrating PA technologies into coffee cultivation under AFS presents the potential to increase productive efficiency and sustainability. Thus, the objective of this study was to evaluate whether the variability of environmental conditions in coffee agroforestry systems can be estimated using technologies associated with PA. The studies were conducted on three coffee farms in Coimbra and Araponga, Minas Gerais, Brazil. For management zone delineation, combinations of apparent soil electrical conductivity (ECa), Normalized Difference Vegetation Index (NDVI), and Digital Terrain Model (DTM) were used. Microclimatic variability was evaluated using weather stations, considering different agroforestry management practices and altitude conditions in mountain coffee cultivation. Canopy cover was estimated by digital image processing techniques applied to aerial images obtained by an Unmanned Aerial Vehicle (UAV). The combination ECa + NDVI was efficient in delineating zones with distinct physical and chemical attributes. Agroforestry management practices and altitude influenced temperature and relative humidity. Tree canopy estimation proved viable to support management. It is concluded that PA is strategic for coffee cultivation in AFS, favoring site-specific and more sustainable management.