Losses in the mechanized harvesting of sugarcane as of speed function of two harvester models in Tropical Savanna Environment

Abstract

The aim of this study was to evaluate the losses that occur in the sugarcane crop during the harvesting, based on the performance of two harvester models operated at different displacement speeds. The variety harvested was CTC4, with total productivity of 95.0 Mg ha-1. The experimental design was completely randomized in a 2 x 3 factorial scheme with five replications. The treatments consisted of two harvester models (John Deere 3520 and John Deere CH570), operated in three different displacement speeds (3.0 km h-1, 4.0 km h-1 and 5.0 km h-1) in sugarcane harvesting. The quality indicators that assessed after sugarcane harvesting were the following loss types: stump cane, whole cane, tip cane, loose piece cane, shrapnel cane and total cane loss in Mg ha-1. The increase in displacement speed resulted in lower total losses in sugarcane harvesting. The 3520 harvester was superior to the CH570 at the highest speed tested. The reduction of sugarcane harvesting loss indexes was proportional to the increase of the displacement speeds for the parameters such as stump cane, whole cane, tip cane, loose piece cane and total loss cane for 3520 harvester and stump cane, whole cane and total loss cane for CH570 harvester, showing strong negative correlations (> 0.85).

Sensor Fusion with NARX Neural Network to Predict the Mass Flow in a Sugarcane Harvester

“…These data support engine rotation control, harvester speed, clean system rotation, chopper blade rotation, and feeder roll speed. The automation of these systems can bring benefits such as a decrease in the damage to the billets [ 1 ], uniform billet lengths [ 2 ], quality of cleaning, and reduction of losses of the harvested product [ 3 , 4 ]. The mass flow predicted in the harvester provides data necessary for the localized management of sugarcane plantations.…”