Multispectral images in the monitoring of coffee trees phytotechnical parameters after pruning

Abstract

The objective of this work was to monitor coffee plants (Coffea arabica L.) after pruning through multispectral images obtained with an unmanned aerial vehicle (UAV) containing a Mapir Survey 3 camera and estimate agronomic parameters based on simple regression parametric models. Growth evaluation was performed in 228 sampling points related to the coffee plants. The parameters analyzed were plant height, crown diameter, plagiotropic branch length, and the number of plagiotropic branches after the pruning point. The creation of mosaics was performed through the software Agisoft PhotoScan Professional 1.4.5, and radiometric calibration through Mapir Camera Control, georeferenced by QGIS and normalized by ENVI. Based on the models generated, data analysis permitted estimating coffee plants’ agronomic parameters after decote-type pruning (cutting off the orthotropic branch at 1.5 m and 2.0 m above ground) with high accuracy. Height was measured in April’s flight with the near-infrared band (Precision = 91.87%), crown diameter and plagiotropic branches length in April’s flight with the infrared band (Precision = 89.36% and 82.22%, respectively), number of nodes in February’s flight with the near-infrared band (Precision = 79.48%), and the number of plagiotropic branches after the pruning point in June’s flight with the near-infrared band (Precision = 69.57%).