How to avoid impurities when harvesting sugarcane

Field evaluation measures losses and impurities in three sugarcane harvesting systems in the state of São Paulo.

With the growth in demand for sugar cane and the competitiveness of product prices, the agricultural sector is seeking greater efficiency and better technology for the field, thus investing in equipment that provides less loss of raw material, reduced contamination of sugar cane with mineral impurities and, consequently, greater profitability.

The change in the sugarcane harvesting system, from manual cutting with mechanized loading to mechanized cutting without burning (raw cane), initially resulted in a sharp increase in sugarcane losses, which could exceed 15%, and an increase in vegetable and mineral impurities sent to the industry.

In mechanized sugarcane harvesting, inadequate adjustment of the harvester and its cleaning equipment depending on the conditions of the sugarcane field can increase the presence of vegetable and/or mineral impurities, as well as losses of raw material.

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The tools that can be very useful and help the producer and sugarcane mills in quality control in the impurity sampling process stages, especially in repetitive processes, are process control charts.

These charts can be considered an option for monitoring certain processes, analyzing results and subsequently making decisions about a certain activity related to mechanized agricultural operations, aiming to increase the quality level of the process.

In view of the above, we evaluated the quality of the harvested sugar cane, taking into account the amounts of mineral and vegetable impurities in shifts A, B and C, rotated from 7am to 15pm, from 15pm to 23pm and from 23pm to 7am , in three harvesting systems: semi-mechanized (SM) (in which the sugarcane was burned for subsequent harvesting), own mechanized (MP) and outsourced mechanized (MT).

Data collection was carried out on farms belonging to Usina Vale, totaling 1.700ha, in the municipality of Onda Verde (SP). The samples were obtained during the sugarcane harvest from March 23 to April 27, 2015, a sugarcane field ten years old at the first evaluation, cultivars RB835486, RB855035, RB855156, RB855453, RB925345 and RB966928, with total plant productivity of 77t/ha.

During the semi-mechanized harvesting of sugarcane, a Valtra tractor (180hp), with engine power of 1.800rpm, manufactured in 2001, was used. For the mechanized harvesting of sugarcane, a John Deere harvester, model 3520, manufactured in 2010 was used. with 342 hp of engine power at 2.100 rpm. In the outsourced mechanized sugarcane harvest, a John Deere harvester, model 3520, manufactured in 2014, with 380 hp of engine power at 2.200 rpm was used.

Data on impurities were obtained using an oblique probe that takes samples of raw material from the cargo, which are analyzed in the Usina Vale laboratory. After homogenizing the samples, 10kg of the material was weighed, and leaves, straw, tops and weeds were considered and separated as plant impurities. Then, the grinding wheels were separated from mineral impurities with the help of a 5mm mesh sieve.

The quantification of mineral impurities was carried out using the calcination method, the difference in ash between dirty cane (mineral and vegetable impurities) and clean cane (sample of ten wheels from each shift), extrapolating kilos of mineral impurities per ton of cane to the usual unit. transported.

These charts were used with the aim of evaluating the quality of the operation, using them as quality indicators for sampling vegetable and mineral impurities.

For the quality indicator involving mineral impurities, within shift A (Figure 1), both for the in-house mechanized sampling and for the outsourced mechanized sampling, points outside the upper control limit were found, demonstrating a low quality in the sampling process.

It was also observed that the outsourced mechanized front (MT), despite the occurrence of a point out of control, presented less variability, that is, better quality, with points little distant between the upper and lower control limits, due to the The fact that this system features newer machinery and technological innovations.

The absence of a floating mechanism in the machines used caused an increase in the levels of impurities in the load, which implies a reduction in the technological quality of the raw material supplied for grinding and losses of sugarcane in the field, in addition to the need for high power to cut and move the volume of ground.

In relation to mineral impurities from Shift B, illustrated in Figure 2, there were points out of control in the three harvesting systems, which probably contributed to the increase in process variability and, consequently, lower quality in the semi-mechanized system. , which may have been caused by loading the sugarcane together with mineral impurities for transshipment using the loaders' claws.

The own mechanized and outsourced mechanized systems presented points closer to the average impurities, 21,4kg/TC and 18,3kg/TC, respectively. Due to the more upright size of the sugarcane field and the use of tip cutters, this material is prevented from being taken along with the load in the transshipment vehicle and consequently the levels of vegetable impurities are lower.

The control charts for mineral impurities in Shift C (Figure 3) demonstrate the existence of out-of-control points in the three harvesting systems, which probably contributed to the loss of process quality in the systems. The own mechanized and outsourced mechanized systems presented points closer to the average impurities, 21,5kg/TC and 17,9kg/TC, respectively.

In Shift A, in relation to vegetable impurities (Figure 4), it was observed that within the three harvesting systems there was the presence of at least one point outside the upper limit of control, thus making an unstable process (low quality) . Regarding process variability, the three systems behaved similarly, with an average of 191kg/TC for the individual value chart.

For the company's own and outsourced mechanized systems, the increase in vegetable impurities may be related to the fact that it is raw sugarcane. Studies observed that without prior burning resulted in a 15% increase in vegetable impurities (straw, palm hearts and green leaves) and minerals added to industrial processing.

The maps obtained high sampling variability, that is, points far from the average, which possibly occurred due to the harvest time coinciding with the rainy season in the region, which hindered the efficient burning of sugarcane for subsequent harvesting, thus leaving a large amount of vegetable impurities in the semi-mechanized system.

Other authors found high values ​​of plant impurities, which was justified by the lack of use of tip cutters, as a result of the sugarcane field being lying flat, a fact that led to the high rate of pointers present in the harvested raw material.

According to Figure 5, plant impurity control charts from shift B, it is noted that the lowest variability occurred in the outsourced mechanized harvesting system, despite containing a point outside the upper control limit.

According to the plant impurity control charts from shift C, it is noted that the lowest variability occurred in the mechanized harvesting system itself, despite containing points outside the upper control limit, highlighting special causes in the process that may be related to the factors: machine, labor, environment, raw material, methods and measurement.

Finally, for mineral impurities, the in-house and outsourced mechanized systems showed similar behavior, both with better process quality. For vegetable impurities, the three shifts presented an unstable process and similar variability. Within quality control, the semi-mechanized system showed the greatest variability.

Aline Spaggiari Alcânatara, Antonio Tassio Santana Ormond, Paulo Roberto de Souza Júnior, Rouverson Pereira da Silva and Elizabeth Haruna Kazama, Lamma, Fcav/Unesp

Article published in issue 171 of Cultivar Máquinas