Modeling of operational performance parameters applied in mechanized harvest of coffee

Abstract

In super-mechanized coffee harvesting system, all operations are performed mechanically. In order to improve the logistics of mechanized agricultural operations, the knowledge on the variables that affect the operational performance can generate models to accurately estimate these parameters. The use of response surface methodology (RSM) allows to verify the influence of different independent variables and the generated response to allow for a great value. This study aimed to verify, using RSM, the influence of speed, mean length of rows and the slope of the areas on the operational performance parameters in different mechanized operations in coffee production, such as: harvest, sweeping and gathering. The results show that the slope directly influences the operational performance of the mechanical harvesting of coffee. The RSM proved to be an important tool to verify the effect of variables on performance parameters, and the generated models showed high significance.