EVALUATION OF THE AUTOMATIC BASE-CUTTER CONTROL SYSTEM IN THE AUSTRALIAN SUGARCANE INDUSTRY
By M ESQUIVEL; S MARRERO; E PONCE; A GUERRERO; T STAINLAY; J VILLARUZ; AW WOOD; LP DIBELLA
SUGARCANE HARVESTING is one of the more costly operations in sugar
production. The efficiency and quality of this process still relies very much on
the skills of harvester operators. The height control of the base-cutter system
requires a lot of concentration of effort from operators. Bad results not only have
negative economic impacts, but also environmental impacts due to sucrose
losses in the field. An automated base-cutter system, initially developed in Cuba
and later intensively tested and widely adopted in Brazil by Techagro, has been
also evaluated in the Australian sugarcane industry. It works on the basis of
measuring the pressure on base-cutter disks several times a second with a
pressure sensor, and then processing the signal with an on-board computer that
automatically controls the base-cutter height according to settings previously
defined by the operator. A total of 12 harvesters, including Austoff, Cameco and
new John Deere, were fitted with the system during 2007 harvesting season.
There were six at Tully, five at the Herbert and one in the Burdekin. Trials were
conducted under several field conditions, which included light sandy soils to
heavier alluvial soils; fields with dual and single rows; plant and ratoon crops;
and different row profiles. Evaluations included field measurements of stool
damage, stubble height and estimated losses. Quality data were measured at the
mill when possible, as fibre content, CCS, juice purity and soil content. The
results of the trials varied slightly with field conditions and operators, but in
general showed several benefits with the use of the automated base-cutter
control system. Average values showed reduced stool damage by 5.7%; similar
soil levels; reduced stubble height by 22.5 mm; and reduced cane losses by
1.7 t/ha. Differences in fibre, CCS and juice purity were small (0.1%) and not
statisticaly significant. Factors influencing the adoption of this technology are
discussed. These include not only the economic and environmental impact, but
also some social components such as the increasing lack of skilled operators.