Quality of coffee planting techniques by aerial sensors and statistical process control

Abstract

Planting is considered one of the most essential steps in coff ee growing. Lack of uniformity in planting may compromise future operations. Therefore, verifying planting operations quality is fundamental to optimizing production processes and reducing costs. This study aimed to investigate planting techniques through Statistical Process Control (SPC) and aerial images. Carried out in two areas, managed manually and semi-mechanized in the Bom Jardim Farm (MG -Brazil). Data were collected through Remotely Piloted Aircraft (RPA). Quality control charts and density maps were used to identify variations in distribution and spacing between plants and planting rows. It was found that the planting carried out manually was 4.7% wider than projected due to spacing reduction from 0.5 m to 0.48 m. The semi-mechanized system displayed a defi cit of 7% compared to the projected planting system, using 0.55 m between plants. The density map showed the most signifi cant planting alignment variations. Despite displaying lower results than the manual system, the semi-mechanized system improvements are valid for their minimal average variations. Thus, correcting points found outside the limits can increase the effi ciency of semi-mechanized planting.