1 SYMPOSIA PRESENTATIONS SUGAR CANE PAYMENT SYSTEM IN BRAZIL. sampling and preparation

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1 ~ Cane 1 SYMPOSIA PRESENTATIONS SUGAR CANE PAYMENT SYSTEM IN BRAZIL J.F. Silva Jr Copersucar, Piracicaba Brasil 1 i I I t 1 I INTRODUCTION Sugar cane quality is one of the most important parameters of concern to the sugar and alcohol producer. If the cane quality is not known the grower and the miller have no basis on which to make improvements. Therefore it is necessary to have an equitable system to evaluate sugar cane quality an to pay for it. In Brasil the sugar cane payment based on quality started in 1978 in Alagoas State, 1983 in Sao Paulo and in 1984 in all others regions. THE SYSTEM The system is based on a sample taken from a load by a horizontal core sampler. The juice is extracted by an automatic hydraulic press under constant conditions. sampling and preparation Three cores are taken from the load by means of a horizontal core sampler. The core samples are mixed'and prepared in a cutter-grinder that gives a minimum preparation index of 85%. The number of loads to be sampled depends on the number of loads delivered by the growers, but has to be at least 50% during a two week period. 1 1 Juice extraction I The prepared sample is homogenized and a g subsample is treated in a hydraulic press at 25 Mpa (250 kg/cm2) for 1 min. Juice analysis The extracted iuice is analyzed for brix by refractometer and pol by automatic saccharimeter. The purity is calculated. 1 ; Fibre % cane (F) 1 Fibre % cane is obtained indirectly by means of a correlation equation with the press cake weight. The formula is: F = x PBU , where PBU = press cake weight. 1 The general use of this equation raises problems because of the variations found with different varieties, and the trash content present in the sample. Pol % cane I The press method, based on the iuice extracted has to be transformed to absolute juice by a pol coefficient (C), which is a function of the fibre % cane or press cake weight. Correlation studies made with the wet disintegrator method, produced the following formula: C = x F. As for fibre, this is a general equation for all the mills, and deviations may occur in

2 SYMPOSIA PRESENTATIONS different regions of the State. With the values of the C coefficient, fibre and the iuice pol, the pol % cane is calculated using the equation: Pol % cane = S x ( x F) x C Sugar cane value The payment system is based on a standard sugar cane with % pol and a juice purity of 83.87%. Then, using the biweekly weighted average for pol % cane and iuice purity for an individual grower, the sugar cane ton value is calculated using the following formula: V = PC, x R, x p,, PC, = grower's pol?'o cane R, = grower's recovery by SJM with molasses purity = 40 Pb = basic price of one ton of cane including transport but excluding taxes fixed by the government Basis of the system The standard cane with a pol value equal to % was obtained from the sugar and alcohol standard recovery and the process losses. These values are: For production: Sugar Molasses or Ethanol 94 kg/tc 37 kg/tc 11 I/tc For losses in pol % in cane: Extraction 8.0% Cane washing 1.5% Undetermined 2.0% Filter cake 0.5% Total 12.0% Cane payment regulations The system is regulated by a State Board comprising representatives of the growers (2), millers (2) and government (2). The duties of the Board are to arbitrate on matters of cane sampling, analyses and the application of the sugar cane payment act. The Board is also responsible for drawing up, each year, an act to cover the technical provisions of the system.

3 SYMPOSIA PRESENTATIONS EVALUATION OF THE SYSTEM Copersucar has maintained'continuously since 1983 a survey of the growers' cane quality. Table 1 shows the average values for each crop season, representative of 210 million tons of sugar cane. Table 1 - Average results for grower's cane quality for six season period Fibre purity pol % bonus/ Season % cane % juice cane penalty 1983/ / / / / / Average Total cane t Figs 1, 2 and 3 show the behaviour of fibre pol % cane and bonus/penalty for the past six crops. period Figure 1. Fibre % cane - averages for 1983/1984 to 1988/1989 crop seasons XCI

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5 SYMPOSIA PRESENTATIONS As can be seen in Fig. 4 growers' bonus and their cane deliveries follow the same pattern, because a relative payment is not used. dist. (%) -bonus (%) period Figure 4. Relationship between cane delivery and bonus/penalty The sugar cane payment system has brought benefits for both the growers and the millers, but it is necessary to look for improvements that will increase the benefits without creating inequities between the sectors involved. RESEARCH AND DEVELOPMENT During the past six years Copersucar has studied all the main points involved in the sugar cane payment system. influence of different types of soils Two types of soils, a and a sand, were added in amounts from zero to 10% to prepared cane samples. The amounts of soil in the press cake and in the iuice were measured by incineration and centrifugation followed by drying. Tables 2 and 3 and Figs 5 and 6 show the average values for five replications in the study. The main conclusions were:

6 Table 2 - Distribution of and soil added to sugar cane SYMPOSIA PRESENTATIONS added measured in juice (1) sand measured in press cake (2) sand measured in cane (1+2) sand Recovery sand Table 3 - Effect of differ4.sandy Figure 5. Effect of different soil types on fibre % cane

7 I I SYMPOSIA PRESENTATIONS Figure 6. Effect of difierent soil types on pol % cane more soil goes into the iuice than does sandy soil there is almost no effect of the soils on the brix and pol % juice the press cake, and consequently the fibre % cane, increased for the two types of soils, being high for the soil due to a lower juice extraction for the same amount of soil, the pol % cane and the ton value were lower for the soil. Therefore, if the sugar factory receives cane with sandy soil, the ton value will be higher than it would be for a soil, meaning that the press method does not compensate for this effect. Effect of sugar cane trash During four years almost 9000 loads were sampled using the same sampling procedures as for the payment system. The average values for the main parameters in Table 4 and Fig.7 represent the differences between dirty and clean cane loads. The results showed that the penalty due to trash was always less than was expected due to the amounts of trash observed. For trash contents higher than 2%, the load value for the dirty cane was higher than for clean cane. Thus the press method does not provide the necessary correction due to trash, and a factor based on fibre has to be included in the system to account for the problem. Lead subacetate influence on iuice pol The results obtained in two experiments showed that the lead subacetate used to clarify the iuice influences iuice pol. When the amount increased from 1.0 to 4.0 g per 100 ml, the pol increased on average by 0.10, as shown in Table 5 and Fig. 8. Therefore, the amount has to be maintained constant and should never exceed 2.0 g/100 ml. xcv

8 Table 4 - Effect of trash on the cane quality and load value Average By level of trash SYMPOSIA PRESENTATIONS Sample Total trash Veg trash Min Trash Fibre clean Fibre dirty Diff % Pol cane clean Pol cane dirty Diff? Load value clean Load value dirty Diff % % trash Figure 7. Percentage difference and load value between clean and dirty cane as function of the trash content

9 SYMPOSIA PRESENTATIONS Table 5 - Lead subacetate effect on pol % juice *I~qu~d chromatography + FIRST PERIOD + SECOND PERIOD I I I g/looml Figure 8. Lead suhacetate effect on pol % juice FUTURE IMPROVEMENTS The sugar cane payment system needs to be improved and to Include corrections wh~ch will make it more equitable. One of the improvements could be relative payment, because during the first two months of the crop, there are almost no deliveries by growers, and the factory has to m~ll only its own sugar cane at a loss. The trash problem has to be corrected in some way to eliminate the distortion that ex~sts, resulting in more payment for dirty than for clean cane, and the effect ~t has on sugar/alcohol recovery. At the same time the sampling and analytical procedures need to be automated or com-