RELEASE 2Q15 Crescimento do Lucro Bruto de 4.7% frente ao 1Q14

Transcription

1 RELEASE 2Q15 Crescimento do Lucro Bruto de 4.7% frente ao 1Q14 EARNINGS RELEASE 3Q16 INDICE Page 1 of 35

2 TABLE OF CONTENTS TABLE OF CONTENTS... 2 TABLE OF REFERENCES - TABLES... 3 TABLE OF REFERENCES FIGURES AND CHARTS... 4 MESSAGE FROM MANAGEMENT... 5 MARKET OVERVIEW... 8 CORN OPERATING PERFORMANCE FINANCIAL ANALYSIS INDICATORS LOCATION OF UNITS Q16 CONFERENCE CALL DISCLAIMER CONTACTS EXHIBIT 1: AGRICULTURAL WEIGHTS AND MEASURES EXHIBIT 2: BALANCE SHEET - ASSETS EXHIBIT 3: BALANCE SHEET - LIABILITIES EXHIBIT 4: INCOME STATEMENT FOR THE FISCAL YEAR EXHIBIT 5: STATEMENT OF CASH FLOWS EXHIBIT 6: STATEMENT OF VALUE ADDED Page 2 of 35

3 TABLE OF REFERENCES - TABLES Table 1 Summarized Financial Results... 5 Table 2 Planted Area Crop Mix... 6 Table 3 Currency and Agricultural Commodity Hedge... 7 Table 4 World Cotton Supply and Demand... 9 Table 5 United States Soybean Supply and Demand Table 6 United States Corn Supply and Demand Table 7 Yields Table 8 Planted Area by Crop Table 9 Planted Area by Land Ownership Table 10 Land Development Table 11 Property Portfolio Table 12 Property Appraisal Table 13 Machinery and Storage Capacity Table 14 EBITDA Conciliation Table 15 Net Revenue Table 16 Volume Invoiced Table 17 Biological Assets in Net Revenue Table 18 Cost of Goods Sold Table 19 Biological Assets in COGS Table 20 Gross Income Table 21 Gross Margin of Cotton Lint and Cotton Seed Table 22 Soybean Gross Margin Table 23 Corn Gross Margin Table 24 Breakdown of Production Cost by Crop Table 25 Production Cost by Hectare Table 26 Selling Expenses Table 27 General and Administrative Expenses Table 28 Net Financial Income (Expense) Table 29 Gains (Losses) from Derivative Operations Table 30 Adjusted Net Financial Income (Expense) Table 31 Net Income Table 32 Currency and Agricultural Commodity Hedge Table 33 CAPEX Table 34 Financial Net Debt Table 36 Return on Net Assets Table 37 Return on Invested Capital Table 38 Net Asset Value Table 39 Changes in Working Capital Page 3 of 35

4 TABLE OF REFERENCES FIGURES AND CHARTS Figure 1 Corn Prices in the International Market vs. Brazil... 5 Figure 2 Soybean Price in International Market vs. Brazil... 5 Figure 3 Photo of Soybean Field in Mato Grosso... 7 Figure 4 Commodity Price Variation... 8 Figure 5 Cotton Price in the International Market vs. Brazil... 8 Figure 6 Cotton Stocks... 9 Figure 7 Soybean Price in International Market vs. Brazil Figure 8 Soybean Yield in the United States Figure 9 Soybean Planted Area in Brazil Figure 10 Annual Variation in Soybean Planted Area Figure 11 Corn Prices in the International Market vs. Brazil Figure 12 Corn Production in Brazil Figure 13 Photo of Field, Mato Grosso Figure 14 Amortization Schedule of Adjusted Net Debt in 3Q Figure 15 Gross Debt Profile in 3Q Page 4 of 35

5 US$/bushel US$ /bushel 3Q16 Earnings Release Porto Alegre, November 8, 2016 SLC AGRÍCOLA S.A. (Bovespa: SLCE3; ADR: SLCJY; Bloomberg: SLCE3BZ; Reuters: SLCE3. SA), one of Brazil s largest producers of grains and fibers, announces today its results for the third quarter of The following financial and operating information is presented in accordance with International Financial Reporting Standards (IFRS). The information was prepared on a consolidated basis and is presented in thousands of Brazilian real, except where stated otherwise. Table 1 Summarized Financial Results (R$ Thousand) 9M15 9M16 AH 3Q15 3Q16 AH Net revenue 1,177,964 1,030, % 342, , % Gross income 315,371 41, % 87,645 40, % Gross margin (1) 33.9% 4.1% p.p 32.9% 12.4% p.p Operating income 215,849 (73,584) n.m. 55,812 1, % Operating margin (1) 23.2% -7.2% p.p 21.0% 0.5% p.p Net profit 85,836 (98,407) % 9,515 (21,215) % Net Margin (1) 9.2% -9.6% p.p 3.6% -6.6% p.p Adjusted EBITDA (2) 187,902 89, % 44, % Adjusted EBITDA Margin (2) 20.2% 8.7% p.p 16.9% 7.4% -9.5 p.p Net debt (3) 1,241,338 1,217, % 1,241,338 1,217, % (1) As a ratio of net revenue excluding the effects from Biological Assets. (2) Excludes the effects from Biological Assets (revenue and cost), since they are noncash. (3) Net Debt adjusted for gains and/or losses in derivative instruments linked to Investments and Debt. NOTE: 3Q15 and 3Q16 refer to the cumulative three-month period from July through September of the years 2015 and 2016, respectively, 9M15 and 9M16 refer to the cumulative nine-month period from January through September of the years 2015 and 2016, respectively. HA refers to the horizontal percentage variation between two periods and VA refers to the vertical percentage variation of a given total. MESSAGE FROM MANAGEMENT As expressed in our comments over the course of the year, 2016 was very unusual in terms of weather, with one of the strongest impacts from the El Niño of the last 50 years, according to leading meteorological sources. This climate anomaly was so intense that it caused losses of 35.2% in grain production in the Northeast of Brazil and 18.2% in the Midwest, according to CONAB data. Considering the stability of production in the South, Brazilian grain production was down 11.6% from the initial forecast. In comparison, the Company suffered a shortfall in grain production of 20.0% (average of main crops), which had never happened before. Naturally, this crop shortfall had an impact on our financial results, as detailed below. The impact from such a shortfall in Brazilian production was so significant that it affected sales prices. As seen in the following charts, corn and soybean traded, in Brazil, at relevant premiums over their international prices, given their shortage in the domestic market, particularly as of midyear. This was a positive result of the shortfall in production, because we took advantage of this scenario of higher prices. Figure 1 Corn Prices in the International Market vs. Brazil CBOT - US$/bu Esalq - US$/bu 3 01/01/15 1Q1501/04/15 2Q15 01/07/15 3Q1501/10/15 4Q15 01/01/161Q16 01/04/16 2Q16 01/07/16 3Q16 01/10/16 Source: ESALQ-USP, CBOT/CMA Figure 2 Soybean Price in International Market vs. Brazil Preço da Soja no Mercado Internacional x Brasil CBOT US$/bu Esalq US$/bu 8 01/01/15 1Q15 01/04/152Q15 01/07/153Q15 01/10/15 4Q1501/01/16 1Q1601/04/16 2Q1601/07/16 3Q16 01/10/16 Source: ESALQ-USP, CBOT/CMA Faced with this significant water stress (unprecedented in our history in the Cerrado region), our management adopted a series of measures over the course of the year to protect the Company's Page 5 of 35

6 balance sheet and start this new crop with a more comfortable financial position. These measures included: Reduction in the CAPEX plan by approximately R$40 million; Postponement in disbursements related to 2016/17 crop fertilizers, to the harvest period, in the amount of R$60 million; Reduction in costs and expenses on all spending not directly related to improving efficiency; and Revision on the Agricultural Plan for the 2016/17 crop year, focusing expansion on second-crop areas and on reducing exposure in areas subject to higher weather risk. Note that our expectation for the fourth quarter is to invoice approximately 56,000 tons of cotton, 81,000 tons of soybean and 110,000 tons of corn. The average invoice price is expected to reach R$6,100/ton for cotton, R$1,250/ton for soybean and R$600/ton for corn, in accordance with the agreements and hedges already negotiated. The analysis of volumes and prices, combined with the average cost per ton in the year, allows us to infer that the net loss in the year to date will be reversed, accompanied by a significant recovery in Adjusted EBITDA by year-end, which would keep the Net Debt/EBITDA ratio below 4 times. We can see, thus, that this year there was a fairly uneven distribution of results across quarters, which was already pointed out in the 2Q16 earnings release. This is due to the distribution of hedging (commodity and currency) and the flow of shipments contracted at farms, with the farms posting better operating performances (i.e. lower unit cost) to ship the highest share of volume in the fourth quarter. Outlook for 2016/17 The initial forecast for planted area in the year is 396,400 hectares, up 5.1% from the previous crop year, mainly due to the maximization of second-crop potential. Table 2 Planted Area Crop Mix Planted Area Planted Area Shares 2015/ /17 (1) 2016/17 Crop Mix ha % Δ% Cotton 93,405 87, Cotton 1 st crop 74,404 60, Cotton 2 nd crop 19,002 26, Soybean (Commercial + Seeds) 212, , Corn 66,975 76, Corn 1 st crop 1,294 1, Corn 2 nd crop 65,681 75, Others Crops (2) 4,293 3, Total Area 377, , (1) Weather factors may affect the planted area forecast. (2) Wheat, corn seed and sugarcane. Bear in mind that the outlook for the next crop year remains very encouraging. To date (base date Nov. 07) we already have planted 48% of the soybean, which is presenting excellent development, ensuring the area for the planting of second-crop cotton and corn. One of the factors worth reinforcing is the probability of the formation of the La Niña phenomenon, which, as opposed to the El Niño, historically brings higher precipitation to our operating region and, therefore, would reverse the situation seen in 2015/16 crop year. The probability of the phenomenon s occurrence is still greater than 55%, at least by February 2017, which should be followed by a neutral scenario, which also is positive for crop development. Page 6 of 35

7 Figure 3 Photo of Soybean Field in Mato Grosso New crop field in Mato Grosso with excellent development (photo taken in second half of October) Furthermore, as shown in the Material Fact notice dated October 17, we expect to reduce production costs in Brazilian real by approximately 3% compared to the previous crop year, due to lower fertilizer prices and the currency s appreciation. Another important factor is the expectation for better prices in 2017, as shown in the following hedge table. Table 3 Currency and Agricultural Commodity Hedge Fiscal Year FX Rate (1) Hedge (%) R$ / US$ Hedge (%) R$ / US$ HX Hedge Commitments (1) Total Cotton Hedge (%) US / libra (2) Hedge (%) US / libra (2) Commercial Hedge Financial Hedge (4) Cotton - Total Hedge Soybean Hedge (%) US$ / bushel (2) Hedge (%) US$ / bushel (2) Commercial Hedge Financial Hedge (4) Commitments (3) Soybean - Total Hedge (1) Commitments with debt payments in U.S. dollar. (2) Based on FOB Port (prices at our production units are also influenced by transport expenses and possible quality discounts). (3) Natural hedge with payments related to land acquisitions and leasing agreements in soybean bags. (4) Includes transactions involving futures, swaps and accumulators. Reference price on 11/07/2016: Cotton ICE DEC/16 /lb Cotton ICE DEC/17 /lb Soybean CBOT Nov/16 US$/bushel 9.91 Soybean CBOT MAY/17 US$/bushel Page 7 of 35

8 U$ cents/libra R$ cents/libra 3Q16 Earnings Release MARKET OVERVIEW Figure 4 Commodity Price Variation January 2015 to October Cotton - ICE: Soybean - CBOT: Corn - CBOT:89 Nymex: Commercial Dolar: /01/15 1Q15 01/04/15 2Q15 01/07/153Q15 01/10/15 4Q1501/01/16 1Q1601/04/16 2Q16 01/07/16 3Q1601/10/16 Source: CMA (02/01/2015 = 100) (17/10/2016) COTTON The cotton price on ICE Futures US increased 11.5% in 3Q16 compared to 2Q16. The main factor supporting prices was the significant drop in world cotton stocks during the 2015/16 and 2016/17 crop years. According to the USDA, stocks fell 13.4% in the 2015/16 crop year and are expected to fall another 9.6% in the 2017 crop year. The last two crops ended a sequence of builds in stocks, which should fall to their lowest level since 2011/12. Figure 5 Cotton Price in the International Market vs. Brazil ICE US$ c/lb Esalq US$ c/lb Esalq R$ c/lb Q15 2Q15 01/01/1501/04/1501/07/1501/10/1501/01/1601/04/1601/07/1601/10/16 3Q15 4Q15 1Q16 2Q16 3Q Source: ESALQ-USP, CBOT/CMA Page 8 of 35

9 Million of bales Stocks/Consumption 3Q16 Earnings Release China is leading the decline in world cotton stocks. After a cycle of stockpiling between 2011 and 2014, followed by stagnation in 2015, the Chinese government sold more than 12 million bales between April and September The higher-than-expected demand from Chinese manufacturers accelerated the drawdown in stocks in both China and globally, which led to upward revisions in cotton consumption estimates and to the expectation that the high world cotton stocks would be consumed earlier than expected. Figure 6 Cotton Stocks World China Other Countries World cotton stocks also have been falling due to the contraction in planted area and production in major producing countries. In the 2015/16 crop year, the world planted area decreased 10.8%, and in 2016/17 is expected to decline a further 3.4%, according to the USDA. Among major producing countries, the highest decreases expected for 2016/17 are in Pakistan (-14.3%), India (-9.7%) and China (-8.2). Due to the smaller planted area in 2016/17, once again world production will significantly lag consumption, reducing stocks and playing a major role in sustaining cotton prices. Table 4 World Cotton Supply and Demand World 2006/7 2007/8 2008/9 2009/ / / / / / / /17** Area (ha) 34,713 32,889 30,630 30,233 33,713 36,100 34,407 32,726 34,159 30,468 29,435 Yield (kg/ha) Beginning Stocks Production Imports Total Supply Exports Consumption Ending Stocks Stocks/comsuption (%) % 100.4% * Estimated ** Projected Source: USDA October/2016 In Brazil, Companhia Nacional de Abastecimento (CONAB) published the first estimate for the 2016/17 crop year. The planted area was estimated between 899,500 and 947,900 hectares, representing contractions of 5.8% and 0.7%, respectively, on the previous crop year. According to CONAB, adverse weather conditions in the last crop year, especially in the Northeast, and the fact that the crop has a high production cost, are influencing the decision to reduce planted areas by producers. Page 9 of 35

10 1965/ / / / / / / / / / / / / / / / / /17** kg/hectare US$ /bushel 3Q16 Earnings Release Despite the smaller area, production should recover supported by a recovery in yields. CONAB estimates production in 2016/17 of between 1,408,500 and 1,483,600 tons, increasing 9.3% and 15.1% from the previous year. SOYBEAN Soybean futures quoted on the Chicago Board of Trade (CBOT) fell in 3Q16. The decline in prices is directly related to the record crop being harvested in the United States in 2016/17. Figure 7 Soybean Price in International Market vs. Brazil CBOT US$/bu Esalq US$/bu 01/01/151Q15 01/04/152Q15 01/07/153Q15 01/10/154Q15 01/01/161Q16 01/04/162Q16 01/07/163Q16 01/10/16 Source: ESALQ-USP, CBOT/CMA In the United States, weather conditions were favorable in virtually all regions and during the entire crop cycle. The high yields obtained should support the more intense rebuilding of stocks in the country. Figure 8 Soybean Yield in the United States Productivity (kg/ha) Linear (Productivity (kg/ha)) y = 29,358x , Page 10 of 35

11 1990/ / / / / / / / / / / / / / / / / / / / / / / / / / /17* 1990/ / / / / / / / / / / / / / / / / / / / / / / / / / /17* Million of Tons Million of Tons Million of Tons Thousand Tons 3Q16 Earnings Release With estimates calling for good yields, the USDA expects soybean stocks to rebuild in the United States. Production should reach million tons in 2016/17, and stocks are expected to grow from 5.3 to 10.7 million tons. Table 5 United States Soybean Supply and Demand United States 2008/9 2009/ / / / / / / /17** Area (ha) 30,222 30,907 31,003 29,856 30,814 30,858 33,423 33,076 33,608 Yield (kg/ha) 2,672 2,960 2,924 2,823 2,687 2,962 3,198 3,231 3,457 Production 80,749 91,470 90,663 84,291 82,791 91, , , ,180 Imports ,103 1, Total Supply 86,690 95,628 95,162 90,582 88,504 97, , , ,360 Exports 34,817 40,798 40,959 37,186 36,129 44,594 50,143 52,668 55,112 Crushing 45,230 47,673 44,851 46,348 45,967 47,192 50,975 51,335 53,070 Consumption 48,112 50,724 48,351 48,786 48,550 50,070 54,955 54,634 56,509 Ending Stocks 3,761 4,106 5,852 4,610 3,825 2,504 5,188 5,363 10,739 Stocks/consumption (%) * Estimated ** Projected Source: USDA October/2016 Despite higher stocks in the United States, a more extensive rebuilding of world stocks in 2016/17 still depends on the soybean crop in South America, which is currently in the planting and initial development phase. In Argentina, the high export duties (which, in the case of soybean, is 30% on the product s FOB port value) are discouraging farmers in the country to plant the crop. Wheat and corn are not subject to export duties, therefore a larger area is being allocated to these crops. According to the Buenos Aires Grain Exchange, the soybean planted area in Argentina should reach 19.6 million hectares, down 2.5% from the previous crop year. In Brazil, data from CONAB points to a slower growth pace in the soybean planted area. The planted area for the 2016/17 crop year is projected at between 33.4 and 33.1 million hectares. Based on the center of this range, this means growth of 1.65% on the prior year. The challenges in expanding the planted area stem from the competitiveness of first-crop corn, which offers higher profitability, as well as financial and credit problems, particularly in the regions that suffered production shortfalls in the previous season. Brazil's total soybean crop in 2016/17 is estimated at between and million tons Figure 9 Soybean Planted Area in Brazil Figure 10 Annual Variation in Soybean Planted Area (2.1) Page 11 of 35

12 Million of bales US$/bushel 3Q16 Earnings Release CORN Corn futures quoted on the Chicago Board of Trade (CBOT) also registered lower prices in 3Q16. The decline in prices is directly related to the expansion in planted area and to the record yields being achieved in the United States in the 2016/17 crop year. Despite the lower international prices, prices in Brazil have found support at high levels, due to the contraction in the production of second-crop corn, which reduced corn supply in the market. Figure 11 Corn Prices in the International Market vs. Brazil CBOT - US$/bu Esalq - US$/bu /01/15 1Q1501/04/15 2Q1501/07/15 3Q1501/10/15 4Q15 01/01/161Q16 01/04/16 2Q16 01/07/16 3Q16 01/10/16 Source: ESALQ-USP, CBOT/CMA In the United States, the world s largest producer, the planted area expanded by 7.4%, according to the USDA, and, given the record yields, the U.S. crop should reach approximately million tons in 2016/17, which would support a rebuilding of the country s exports and stocks. Table 6 United States Corn Supply and Demand United States 2009/ / / / / / /16* 2016/17** Area (ha) 32,169 32,960 33,945 35,356 35,390 33,644 32,678 35,141 Yield (kg/ha) 10,318 9,576 9,215 7,727 9,926 10,733 10,572 10,884 Begging Stocks 42,504 43,380 28,644 25,122 20,859 31,292 43,974 44,141 Production 331, , , , , , , ,476 Imports , ,714 1,270 Exports 50,270 46,508 39,096 18,545 48,790 47,421 48,202 56,518 Consumption 280, , , , , , , ,434 Ending Stocks 43,389 28,644 25,122 20,859 31,292 43,974 44,141 58,938 Stocks/consumption (%) In Brazil, the lower yield and reduction in second-crop corn production reduced corn supply in the domestic market and made it impossible to rebuild domestic stocks, and even has resulted in corn imports into regions with lower supplies. With high prices, the expectation is for expansion in the first-crop corn planted area in the South and Southeast, especially due to the higher profitability compared to soybean. This increase reverses a trend of various years of reductions in the first-crop corn planted area in Brazil. According to CONAB, the first-crop corn planted area should expand by 1.5% on average in the period. This expansion should reach 6.4% in the South and 4.3% in the Southeast. Page 12 of 35

13 Milhões de hectares 3Q16 Earnings Release Figure 12 Corn Production in Brazil Second crop area First crop area *2016/17 estimated Source: CONAB October/2016 OPERATING PERFORMANCE 2015/16 CROP YEAR The 2015/16 crop year was marked by weather anomalies caused by the El Niño phenomenon, which was one of the most intense of the last 50 years. The high precipitation in January at farms in the Northeast followed by a long drought also affected second-crop production in the Midwest, as explained in the 1Q16 and 2Q16 earnings releases. In 3Q16, we concluded the cotton harvest on 93,405 ha (1 st and 2 nd crop) and the harvesting of secondcrop corn. Soybean The Soybean yield was 2,580 kg per hectare, down 19.1% from the projected 3,189 kg per hectare. Cotton 1 st crop With the conclusion of harvesting on 74,404 ha dedicated to the crop, the estimated cotton lint yield (which still depends on finalizing processing) is 1,250 kg/ha, down 24.8% from the estimate of 1,662 kg/ha. Cotton 2 nd crop The harvesting of 19,002 ha was concluded and the current cotton lint yield estimate is 1,389 kg/ha, down 10.4% from the projection of 1,560 kg/ha, due to the impact of the drought in the Center-West region. Page 13 of 35

14 Corn 1 st crop Harvesting was concluded on July 20, with a yield of 7,774 kg/ha, down 18.6% from the projection of 9,553 kg/ha. Corn 2 nd crop Harvesting on 65,566 was completed on August 29, with yield of 5,378kg/ha, or 20.9% lower than the projection of 6,796 kg/ha. 2016/17 CROP YEAR The 2016/17 crop year began in September with the planting of super-early soybean varieties on the farms located in the states of Mato Grosso and Mato Grosso do Sul, as well as on irrigated areas in the state of Bahia. Soybean The planting of super-early and early soybean varieties, which enables the planting of second-crop cotton and corn, was begun in the second half of September. The area planted by November 07 was 110,769 ha (total) in the states of Mato Grosso (86%), Mato Grosso do Sul (100%) and Maranhão (43%), which represents 48% of the estimated soybean area. We implemented 100% of the super-early and early soybean varieties, and to date the crops have presented excellent development, which ensures the second-crop cotton area (planted after the soybean harvest). As shown in Figure 13, the conditions of the crops planted are excellent, with a general aspect of excellent development. Figure 13 Photo of Field, Mato Grosso Soybean field in Mato Grosso in the second half of October presenting excellent development. Page 14 of 35

15 YIELD Table 7 Yields Yield (kg/ha) Achieved 2015/16 Initial Estimate 2016/17 % Cotton Lint 1 st crop 1,250 1, Cotton Lint 2 nd crop 1,389 1, Cotton Seed 1,679 2, Soybean 2,580 3, Corn 1 st crop 7,774 7, Corn 2 nd crop 5,378 6, PLANTED AREA The following table presents the latest data on planted area for the 2016/17 crop year and a comparison with the previous season. Table 8 Planted Area by Crop Planted Area Planted Area Share 2015/ /17 (1) 2016/17 Crop Mix ha % Δ% Cotton 93,405 87, Cotton 1 st crop 74,404 60, Cotton 2 nd crop 19,002 26, Soybean (Commercial + Seeds) 212, , Corn 66,975 76, Corn 1 st crop 1,294 1, Corn 2 nd crop 65,681 75, Others crops (2) 4,293 3, Total Area 377, , (1) Weather factors may affect the planted area forecast. (2) Wheat, corn seed and sugarcane. Table 9 Planted Area by Land Ownership Planted Area Planted Area Share 2015/ /17 (1) 2016/17 Area Mix ha % Δ% 1 st crop 290, , Owned Area 124, , Leased Area 93,867 97, Joint Ventures Area (2) 41,375 38, SLC LandCo Area 30,301 35, nd crop 86, , Owned Area 49,318 59, Leased Area 24,533 24, Joint Ventures Area (2) 7,570 10, SLC LandCo Area 5,486 9, Total Area 377, , (1) Weather factors may affect the planted area forecast. (2) Areas owned by Grupo Dois Vales and Mitsui. (3) A SLC Agrícola holds an interest of 81.23% in SLC LandCo. Page 15 of 35

16 LAND DEVELOPMENT In the 2015/16 crop year, we concluded clearing operations on the 2,553 hectares of the Paineira Farm, where we will carry out first-year soil correction during the 2016/17 crop year. At the Piratini Farm, we concluded soil correction on 4,000 ha. Table 10 Land Development Areas in transformation Areas in licensing process SLC Agricola Farms (ha) (ha) Palmares Parnaíba - 1,464 Parnaguá 1,005 5,347 Parceiro 9,162 6,698 Paineira 2,553 - Sub Total 12,720 14,110 Areas in transformation Areas in licensing process SLC LandCo Farms (ha) (ha) Parnaíba (1) - 4,749 Piratini 9,993 - Parceiro (1) 1,115 1,530 Sub Total 11,108 6,279 Total 23,828 20,389 (1) Areas acquired by SLC LandCo to be developed jointly with these farms. Note: The estimate of areas in the licensing process could change due to georeferencing. PROPERTY PORTFOLIO The portfolio of properties under our management on November 8, 2016 is presented below: Table 11 Property Portfolio 2015/16 Crop Year (ha) Owned (1) SLC LandCo (2) Leased Joint Ventures Under Control Total Planted Area (3) Farm State ha Pamplona GO 17,385 3,898 21,283 20,671 Planalto MS 17,437 1,646 19,083 20,517 Planorte MT 23,784 23,784 31,332 Paiaguás MT 34,257 10,337 44,594 65,177 Perdizes (5) MT 28,857 13,288 42,145 23,350 Pioneira (4) MT 19,469 19,469 30,084 Panorama BA 10,374 14,263 24,637 21,789 Paladino (5) BA 19,355 19,355 19,355 Piratini BA 25,355 4,901 30,256 13,377 Palmares BA 16, ,073 32,784 25,247 Parnaíba MA 37,180 10,200 26,402 73,782 58,197 Planeste MA 23,325 15,606 38,931 47,390 Parceiro BA 32,983 3, ,404 11,595 Paineira (6) PI 12,040 12,040 - Parnaguá PI 24,603 24,603 8,323 Total - 244,694 86,765 93,867 38, , ,402 (1) Own property, includes Legal Reserve. (2) SLC Agrícola currently owns 81.23% of SLC LandCo, while the Valiance fund owns 18.77%. (3) Including the second crop. Weather factors may affect the planted area forecast. (4) The Pioneira Farm is part of the joint arrangement with Grupo Dois Vales. (5) The Perdizes and Paladino Farms are part of the joint arrangements with Mitsui in SLC-Mit. (6) Leased farm. LAND PORTFOLIO APPRAISAL We present below updated figures on the value of the company s properties, which was prepared internally based on an independent appraisal in the case of the farms of SLC LandCo, and on other market sources in the case of the other farms, including data from brokerages and specialty magazines, among other independent sources. The average hectare of property owned by the Company appreciated 5.2% from the previous year, excluding variations in areas. Page 16 of 35

17 Including the land acquisitions between the periods (notably the 13,268 hectares acquired by SLC LandCo in 2015, as announced in a Notice to the Market on September 24, 2015), the total value of the company's own land portfolio stands at R$3,685,361 thousand. Table 12 Property Appraisal 2015 Appraisal 2016 Appraisal Region Total land Appraisal(ha) R$ thd R$/ha Total land Appraisal(ha) R$ thd R$/ha Midwest 114,159 1,706,260 14, ,426 1,911,925 15,004 Northeast 194,561 1,695,580 8, ,103 1,733,436 9,090 Total 308,719 3,401,840 11, ,529 3,685,361 11,426 MACHINERY AND STORAGE CAPACITY The following table presents the machinery owned by the Company. Table 13 Machinery and Storage Capacity Machinery Quantity Tractors 189 Grain Combines 184 Cotton Pickers 80 Planters 189 Self-propelled sprayers 137 Storage Capacity Grains Cotton Tons 613, ,981 % Production (1) 66% 86% (1) Estimate based on the estimated planted area and yield for 2015/16. FINANCIAL ANALYSIS EBITDA Table 14 EBITDA Conciliation (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Net revenue 1,177,964 1,030, % 342, , % (-) Cost of Goods and/or Services Sold (862,593) (988,348) 14.6% (255,053) (277,417) 8.8% Gross Income 315,371 41, % 87,645 40, % (-) Sales Expenses (54,830) (62,553) 14.1% (17,620) (23,607) 34.0% (-) General and administrative expenses (42,161) (45,966) 9.0% (13,813) (12,099) -12.4% (-) Sales Expenses (29,553) (33,634) 13.8% (10,310) (10,042) -2,6%. (-) General and administrative (4,692) (1,664) -64.5% (1,162) 245 n.m. (-) Management compensation (7,916) (10,668) 34.8% (2,341) (2,302) -1,7% (-) Other operating revenues (loss) (2,531) (6,727) 165.8% (400) (2,911) 627.8% (=) Income from Activity 215,849 (73,584) n.m. 55,812 1, % (+) Depreciation and amortization 74,819 77, % 24,577 23, % EBITDA 290,668 3, % 80,389 25, % (-) Biological Assets on revenue (note 25*) (248,663) (3,276) -98.7% (76,398) 5,896 n.m. (+) Biological Assets on costs (note 26*) 145,897 82, % 40,891 (11,971) n.m. (+) Low Fixed Assets - 6, ,0% - 4, ,0% Adjusted EBITDA (1) 187,902 89, % 44,882 24, % Adjusted EBITDA Margin (2) 20.2% 8.7% p.p 16.9% 7.4% -9.5 p.p (1) Excludes the effects from Biological Assets, since they are noncash. (2) As a ratio of net revenue excluding the effects from Biological Assets. * Note in the Quarterly Information (ITR) In 3Q16, adjusted EBITDA was R$24,004 thousand, with adjusted EBITDA margin of 7.4%, down 9.5 percentage points from adjusted EBITDA margin in 3Q15 (16.9%). In 9M16, adjusted EBITDA decreased 52.5% (R$187,902 in 9M15 to R$89,161 in 9M16), with margin declining 11.5 percentage points. The decrease in adjusted EBITDA in both analysis periods is related to the lower Gross Income (excluding Biological Assets) from cotton (lint and seed) and soybean, which decreased by R$15,468 thousand and R$3,765 thousand, respectively, in 3Q16 compared to 3Q15. This margin compression is directly related Page 17 of 35

18 to the production shortfall due to low precipitation. Gross income in 9M16 contracted by R$73,123 thousand for cotton and R$13,666 thousand for soybean. Adjusted EBITDA should present significant recovery during the fourth quarter, due to expected volumes and hedged prices, as mentioned on the Message from Management. The Net Debt/EBITDA ratio should also be kept under the annual limit, that is, below 4 times. NET REVENUE Net Revenue in 3Q16 contracted 7.3% on the year-ago period. Excluding the non-cash effect from Biological Assets, net revenue grew 21.5%, due to the lower volume of soybean invoiced between the periods, which was partially offset by the higher volume of cotton and corn invoiced. In 9M16, net revenue, also excluding the effect from Biological Assets, increased 10.5%, due to the higher volume invoiced of cotton and corn and the better prices for soybean, cotton and corn. Table 15 Net Revenue (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Net Revenue 1,177,964 1,030, % 342, , % Cotton lint invoiced 362, , % 113, , % Cotton seed invoiced 49,555 64, % 35,033 49, % Soybean invoiced 561, , % 95,815 25, % Corn invoiced 55, , % 34,343 87, % Others (invoiced) 39,582 20, % 17,213 6, % Hedge income (139,125) (82,427) -40.8% (29,298) 17,104 n.m. Biological Assets 248,663 3, % 76,398 (5,896) n.m. Table 16 Volume Invoiced (Tons) 9M15 9M16 AH 3Q15 3Q16 AH Volume Invoiced 1,021, , % 372, , % Cotton lint 78,945 86, % 20,997 28, % Cotton seed 114, , % 79,665 89, % Soybean 573, , % 87,624 20, % Corn 164, , % 109, , % Others 90,672 81, % 74,908 63, % Table 17 Biological Assets in Net Revenue (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Effect of Biological Asset on Net Revenue 248,663 3, % 76,398 (5,896) n.m. Cotton lint 131,848 (40,946) n.m. 66, % Cotton seed 12,661 (4,108) n.m. 6, % Soybean 99,366 29, % Corn 4,788 21, % 3,501 (7,082) n.m. Others - (2,547) -100,0% Biological assets are calculated as follows: market price, net of taxes and selling expenses (freight), less costs incurred. The apportionment of biological assets to net revenue in the quarter was negative, impacted by the apportionment of biological assets for the corn crop, due to the additional decline in yield, as explained in the section on the operational scenario. In 9M16, the apportionment of biological assets amounted to R$3,276 thousand, reflecting the expectation of low margins with the apportionment of biological assets. COST OF GOODS SOLD Cost of goods sold increased 8.8% in 3Q16 compared to 3Q15. Excluding the impact from biological assets, cost of goods sold increased 35.1%, due to the increase in costs per hectare, combined with the lower yield in the 2015/16 crop year compared to 2014/15 and the higher volume invoiced of cotton and corn in the period. Page 18 of 35

19 In 9M16, cost of goods sold increased 14.6% from 9M15. Excluding biological assets allocated at cost, the increase in relation to 9M15 was 35.1%. This increase is also attributed to the higher cost per hectare and to the lower yield in the 2015/16 crop year compared to the 2014/15 crop year. The higher volume invoiced of cotton and corn also was an important factor. Table 18 Cost of Goods Sold (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Cost of Goods Sold (862,593) (988,348) 14.6% (255,053) (277,417) 8.8% Cotton lint (233,868) (336,248) 43.8% (68,539) (122,062) 78.1% Cotton seed (35,677) (66,178) 85.5% (23,411) (53,964) 130.5% Soybean (388,834) (405,911) 4.4% (87,482) (35,857) -59.0% Corn (40,605) (74,323) 83.0% (25,981) (67,096) 158.3% Other (17,712) (23,449) 32.4% (8,749) (10,409) 19.0% Biological Assets Allocated at Cost (145,897) (82,239) -43.6% (40,891) 11, % Table 19 Biological Assets in COGS (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Biological Assets Allocated at Cost (145,897) (82,239) -43.6% (40,891) 11, % Cotton lint (34,840) (28,557) -18.0% (18,587) 26,573 n.m. Cotton seed (5,881) 3,769 n.m. (4,864) 4,951 n.m. Soybean (103,802) (43,017) -58.6% (16,172) (5,299) -67.2% Corn (1,490) (14,434) 868.7% (1,268) (14,254) n.m. Others ,0% GROSS INCOME Table 20 Gross Income (R$ mil) 9M15 9M16 AH 3Q15 3Q16 AH Gross Profit 315,371 41, % 87,645 40, % Cotton lint 61,604 3, % 18,911 19, % Cotton seed 13,878 (1,434) n.m. 11,622 (4,449) n.m. Soybean 103,158 89, % 6,176 2, % Corn 12,095 31, % 6,965 20, % Others 21,870 (2,834) -1130% 8,464 (3,961) n.m. Biological Assets 102,766 (78,963) n.m. 35,507 6,075-82,9% Gross Income in 3Q16 was R$40,198 thousand, down 54.1% from 3Q15. In 9M16, Gross Income also declined, by 86.8%. In both analysis periods, the increase in costs per hectare and decrease in yields in the 2015/16 crop year compared to 2014/15 were the main factors contributing to the reduction in gross margin, despite the slight improvement in sales prices. ANALYSIS OF MARGINS BY CROP To contribute to a better understanding of margins, in this section, hedge income (loss) is allocated among cotton, soybean and corn. Cotton Lint and Cotton Seed Of the cotton invoiced in 3Q16, 89% is associated with the 2015/16 crop year. Cotton unit margin decreased 23.0% in 3Q16 compared to 3Q15 and was mainly impacted by the 33.0% increase in unit cost. In 9M16, gross margin fell 94.5% from the year-ago period. These variations are due to the increase in unit cost, which was partially offset by the higher unit prices. Table 21 Gross Margin of Cotton Lint and Cotton Seed Cotton Invoiced 9M15 9M16 AH 3Q15 3Q16 AH Cotton Lint Invoiced Volume Invoiced Ton 78,945 86, % 20,997 28, % Net Revenue R$ Mil 362, , % 113, , % Result of currency hedge R$ Mil (67,115) (96,314) 43.5% (25,744) 4,338 n.m. Net inc. ad.for the res. of curr.hedging R$ Mil 295, , % 87, , % Unit Price R$ / Ton 3,740 3, % 4,165 5, % Cost Total R$ Mil (233,868) (336,248) 43.8% (68,539) (122,062) 78.1% Unit Cost R$ / Ton (2,962) (3,880) 31.1% (3,264) (4,340) 33.0% Unitary Margin R$ / Ton % % Page 19 of 35

20 9M15 9M16 AH 3Q5 3Q16 AH Cotton Seed Invoiced Volume Invoiced Ton 114, , % 79,665 89, % Net Revenue R$ Mil 49,555 64, % 35,033 49, % Unit Price R$ / Ton % % Cost Total R$ Mil (35,677) (66,178) 85.5% (23,411) (53,964) 130.5% Unit Cost R$ / Ton (312) (561) 79.8% (294) (604) 106.9% Unitary Margin R$ / Ton 120 (12) n.m. 146 (50) n.m Soybean Soybean margin in the quarter and nine months increased due to the increase in unit price, which was partially offset by the increase in unit cost. The higher production cost per hectare compared to the 2014/15 crop year and the lower yield contributed to the higher unit cost in both periods. Table 22 Soybean Gross Margin Soybeans Invoiced 9M15 9M16 AH 3Q15 3Q16 AH Volume Invoiced Ton 573, , % 87,624 20, % Net Revenue R$ Mil 561, , % 95,815 25, % Result of currency hedge R$ Mil (69,400) 13,887 n.m. (2,157) 12,766 n.m. Net inc. ad.for the res. of curr.hedging R$ Mil 491, , % 93,658 38, % Unit Price R$ / Ton 858 1, % 1,069 1, % Cost Total R$ Mil (388,834) (405,911) 4.4% (87,482) (35,857) -59.0% Unit Cost R$ / Ton (678) (894) 31.9% (1,000) (1,740) 74.0% Unitary Margin R$ / Ton % % Corn Corn unit margin increased 55.6% in 3Q16 and 81.1% in 9M16, mainly due to the increase in unit price, which was partially offset by the increase in unit cost. The price increase is explained by the shortage of corn in the domestic market caused by the high volume of exports following the depreciation in the Brazilian real against the U.S. dollar, which was exacerbated by the shortfall in second-crop corn in Brazil. There also was an increase in the volume of sales with freight paid by the Company, which improves the invoice price, though with a proportional increase in selling expenses, which are not recognized in gross income. Table 23 Corn Gross Margin Corn Invoiced 9M15 9M16 AH 3Q15 3Q16 AH Volume Invoiced Ton 164, , % 109, , % Net Revenue R$ Mil 55, , % 34,343 87, % Result of currency hedge R$ Mil (2,610) ,0% (1,397) ,0% Net income ad.for the res.of currency hedging R$ Mil 52, , % 32,946 87, % Unit Price R$ / Ton ,9% % Cost Total R$ Mil (40,605) (74,323) 83.0% (25,981) (67,096) 158.3% Unit Cost R$ / Ton (247) (315) 27.5% (238) (322) 35.3% Unitary Margin R$ / Ton % % Page 20 of 35

21 PRODUCTION COST The breakdown of our total production costs is shown below: Table 24 Breakdown of Production Cost by Crop % Cotton Soybean Corn Average 2016/17 Average 2015/16 Variable Costs Seeds Fertilizers Defensives Air Spraying Fuels and Lubrificants Labor Gining Maintenance of machines and instumets Others Fixes Costs Labor Depreciation and Amortization Leasing Others Our estimates of total production cost per hectare for the 2016/17 crop year are presented below: Table 25 Production Cost by Hectare A B C R$/ha) (1) Total ( Budget 2015/16 Achieved 2015/16 Budget 2016/17 B/A C/A Cotton 1 st crop 7,592 7,096 7, % -5.7% Cotton 2 nd crop 6,157 5,868 6, % 0.1% Soybean 2,229 2,206 2, % 1.0% Corn 1 st crop 2,910 3,011 2, % -4.2% Corn 2 nd crop 1,841 1,548 1, % -3.3% Average Cost total (2) 3,271 3,104 3, % - (1) Based on the position at September 30, Figures may suffer changes by the end of cotton processing and the sale of grains. (2) Total average cost weighted by area. In an analysis of cost per hectare in the 2015/16 crop year compared to the budget, the decrease was 5.93% or approximately R$80 million, reflecting the lower yield and actions to contain costs. Total average production cost per hectare estimated for the 2016/17 crop year presented a slight decrease of 2.8% in relation to the budget for the 2015/16 crop year, despite inflation of approximately 10% in the period. SELLING EXPENSES Selling expenses increased 34.0% in 3Q16 compared to 3Q15. In 9M16, selling expenses increased 4.7% compared to 9M15. In 3Q16, the increase in freight was mainly due to the higher volume of corn invoiced with freight paid by the Company and to the higher volume of cotton invoiced, for which freight is always paid by the Company. In 9M16, the higher nominal increase was also due to freight, compared to 3Q15, reflecting the higher volumes of cotton and corn invoiced. In 3Q16, selling expenses corresponded to 7.3% of Net Revenue (excluding the effect from Biological Assets), up from 6.1% in 3Q15. In 9M16, this ratio stood at 6.1%, compared to 5.9% in 9M15. Page 21 of 35

22 Table 26 Selling Expenses (R$ mil) 9M15 9M16 AH 3Q15 3Q16 AH Freight 22,591 29, % 7,598 11, % Storage 14,306 15, % 4,415 4, % Commissions 5,720 4, % 2,104 1, % Classification of Goods 937 1, % % Export Expenses 10,969 9, % 2,830 2, % Others 307 3, % 157 2,934 n.m. Total 54,830 62, % 17,620 23, % % Net Revenue 5.9% 6.1% 0.2 p.p 6.6% 7.3% 0.7 p.p GENERAL AND ADMINISTRATIVE EXPENSES Excluding the impact from the Employee Profit Sharing Program, which varies in accordance with the Company's Net Income, general and administrative expenses decreased 2.6% in 3Q16 and increased 13.8% in 9M16. As shown in Table 27 below, the variation in the quarter and nine-month period mainly reflects the increase in the following items: (i) (ii) (iii) (iv) Personnel Expenses, due to wage increases under the collective bargaining agreement and the apportionment of the share bonus plans for managers; Fees with third-party services, which were affected by expenses with legal advisors related to a tax lawsuit with judgment for plaintiff; Increase in expenses with software maintenance and renewal of licenses; Contingencies impacted by the reversal of provision due to the reduction of the risk (probable amount). In 9M16, General and Administrative Expenses corresponded to 3.4% of Net Revenue (excluding the effect from Biological Assets), declining 0.2 percentage point from 3.7% in 9M15. Table 27 General and Administrative Expenses (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Expenses with personnel 14,641 17, % 5,230 5, % Fees 2,299 2, % 769 1, % Depreciations and amortizations 2,253 1, % % Expenses with travels 1,140 1, % % Software maintenance 1,793 2, % % Marketing/Advertisement 1,242 1, % % Expenses with Communications 1,790 1, % % Rentals % % Labor, Tax and Environmental Contingencies % 234 (462) n.m. Electricity % % Taxes and other fees % % Contribuitions and donations 1, % % Other 1,894 1, % % Subtotal 29,553 33, % 10,310 10, % Provision for profit share program 4,692 1, % 1,162 (245) n.m. Total 34,245 35, % 11,472 9, % % Net Revenue 3.7% 3.4% -0.3 p.p 4.3% 3.0% -1.3 p.p Page 22 of 35

23 NET FINANCIAL INCOME (EXPENSE) In 3Q16, we recorded a net financial expense of R$40,689 thousand, compared to an expense of R$44,990 thousand in 3Q15, a decrease of 9.6% or R$4,300 thousand. In 9M16, the net financial expense declined by 7.4% or R$7,015 thousand. Table 28 Net Financial Income (Expense) (R$ thousand) 9M15 9M16 AH 3Q15 3Q16 AH Revenues (expenses) with derivatives 132,358 (126,422) n.m. 100,069 (15,060) n.m. Interest (51,988) (44,824) -13.8% (24,769) (20,043) -19.1% Monetary variation (1,632) (1,556) -4,7% (1,302) (2,914) 123.8% FX variation (167,469) 92,582 n.m. (115,452) 4,214 n.m. Other financial revenues (expenses) (6,362) (7,857) 23.5% (3,536) (6,886) 94.7% Total (95,093) (88,077) -7.4% (44,990) (40,689) -9.6% % Net Revenue -10.2% -8.6% 1.6 p.p -16.9% -12.6% 4.3 p.p Table 29 Gains (Losses) from Derivative Operations (R$ thd) 9M15 9M16 AH 3Q15 3Q16 AH Swap of debt in Dollar to Reais 113,656 (128,701) n.m. 85,894 (15,059) n.m. Swap of Financial asset in Reais to Dollar 17, ,0%. 13, ,0% Commodities Hedge 1, ,8% ,0% FX Hedge (not designed as hedge accounting) (363) 2,266 n.m. 9 (1) n.m. Total 132,358 (126,422) n.m. 100,069 (15,060) n.m. Note: In accordance with Note 19 of the Quarterly Information (ITR) Note that, since a portion of debt in USD was swapped to BRL, as shown in table 29, and another portion is designated as hedge accounting, whose effects are recorded as Sales Revenue, when realized, the exchange variation on debt in USD does not affect Net Financial Income (Expense) when we analyze the aggregate figures (derivative gains and losses and exchange variation). For a better understanding of this impact, we suggest analyzing below Table 30 - Adjusted Net Financial Income (Expense). Table 30 Adjusted Net Financial Income (Expense) (R$ thd) 9M15 9M16 AH 3Q15 3Q16 AH Interest (57,301) (66,620) 16.3% (20,979) (29,429) 40.3% FX variation net of swap operations (29,798) (11,744) -60.6% (19,173) (1,460) -92.4% Monetary Variation (1,632) (1,556) -4.7% (1,302) (2,914) 123.8% Other financial revenues (expenses) (6,362) (7,858) 23.5% (3,536) (6,887) 94.8% Total (95,093) (88,078) -7.4% (44,990) (40,689) -9.6% % Net Revenue % -8.6% 1.7 p.p % % 4.3p.p. Variations in the quarter included lower exchange variation loss net of swapped transactions, of R$1,460 thousand, compared to the loss of R$19,173 thousand in 3Q15, when the Brazilian real depreciated sharply against the U.S. dollar. Interest expenses increased 40.3% in the period, from R$20,979 in 3Q15 to R$29,429 in 3Q16. In 3Q15, the interest income of R$13,488 from Investment Swap from BRL to USD (see Table 29) helped to prevent a reduction in net interest in 3Q16, since the operation was settled. The increase of R$3,351 in the Other financial expense in 3Q16 was due to a discount ICMS sale that did recur in 3Q15. NET INCOME Table 31 Net Income (R$ thd) 9M15 9M16 AH 3Q15 3Q16 AH Income before Income Taxes 120,756 (161,661) n.m. 10,822 (39,108) n.m. Income Tax and Social Contribution (34,920) 63,254 n.m. (1,307) 17,893 n.m. Net Income for the period 85,836 (98,407) n.m. 9,515 (21,215) n.m. Page 23 of 35

24 The company posted a net loss of R$98,407 thousand in 9M16, compared to the net income of R$85,836 thousand in 9M15. In 4Q16, we estimate a reversal in the accumulated net loss based on the projected volumes and prices hedged. Volumes and hedged prices for the fourth quarter will contribute to the reversal of the Net Result, which was impacted mainly by the abnormal climate situation caused by the El Niño phenomenon in 2015/16. CURRENCY AND AGRICULTURAL COMMODITY HEDGE The Company s sales revenues are generated mainly by the trading of agricultural commodities such as cotton, soybean and corn, which are quoted in U.S. dollar on international exchanges, such as the Chicago Board of Trade (CBOT) and the Intercontinental Exchange Futures US (ICE). Therefore, we are actively exposed to variations in foreign exchange rates and in the prices of these commodities. To protect from currency variation we use derivative instruments, with the portfolio of these instruments basically comprising non-deliverable forwards (NDFs) and option contracts. In line with the Company s Risk Management Policy, whose purpose is to obtain a pre-established Adjusted EBITDA margin with a combination of factors such as Price, Foreign Exchange and Cost, most of the instruments for protecting against commodity price variation are accomplished through advanced sales directly with our clients (forward contracts). We also use futures and options contracts negotiated on the exchange and swap and option transactions contracted with financial institutions. The mark-to-market adjustments of future, swap and option transactions are recorded under financial income (expense). The hedge position on October 31, 2016 for commodities (in relation to the estimated total volume invoiced) and currency (in relation to the total estimated revenue in U.S. dollar) is shown below broken down by commercial hedge and financial hedge: Table 32 Currency and Agricultural Commodity Hedge Fiscal Year FX Rate (1) Hedge (%) R$ / US$ Hedge (%) R$ / US$ HX Hedge Commitments (1) Total Cotton Hedge (%) US / libra (2) Hedge (%) US / libra (2) Commercial Hedge Financial Hedge (4) Cotton - Total Hedge Soybean Hedge (%) US$ / bushel (2) Hedge (%) US$ / bushel (2) Commercial Hedge Financial Hedge (4) Commitments (3) Soybean - Total Hedge (1) Commitments with debt payments in U.S. dollar. (2) Based on FOB Port (prices at our production units are also influenced by transport expenses and possible quality discounts). (3) Natural hedge with payments related to land acquisitions and leasing agreements in soybean bags. (4) Includes transactions involving futures, swaps and accumulators. Reference price on 11/07/2016: Cotton ICE DEC/16 /lb Cotton ICE DEC/17 /lb 68,75 - Soybean CBOT NOV/16 US$/bushel 9.91 Soybean CBOT MAY/17 US$/bushel Page 24 of 35

25 PROPERTY, PLANT AND EQUIPMENT / INTANGIBLE ASSETS The main investments in 3Q16 were: (i) (ii) Acquisition of agricultural machinery and tools at the Planeste, Panorama and Palmares farms; Land clearing and soil correction, in the amount of R$7,588 thousand, mainly at the Planeste, Parceiro and Parnaíba farms. Table 33 CAPEX CAPEX (R$ thousand) 9M15 AV 9M16 AV 3Q16 AV Machinery, implements and equipment 32, % 19, % 14, % Land acquisition 85, % 2 0.0% 2 0.0% Soil correction 17, % 10, % 7, % Buildings and facilities 18, % 12, % 4, % Cotton ginning plant 4, % 1, % - 0.0% Grains storage 8, % % % Soil cleaning 7, % 8, % 5, % Vehicles 1, % % % Software % % % Others 2, % 2, % % Total 178,710 57,244 33,724 FINANCIAL NET DEBT Adjusted gross debt in 3Q16 increased by 3.96%, from R$1,171,066 thousand in 2Q16 to R$1,217,338. The main variations were: (i) (ii) (iii) Amortization of R$250,650 thousand in Rural Credit Working Capital transactions in the 2015/2016 crop year; Renewal and expansion of R$178,328 thousand in transactions with the Northeast Constitutional Fund; Renewal of Rural Credit for the 2016/17 crop year of R$255,694 thousand to fund firstcrop planting. Table 34 Financial Net Debt Average Interest rate (%) Consolidated (R$ thd) Index 3Q16 (R$ thd) Index 3Q16 Applied in Fixes Assets Finame BNDES Pré e TJLP¹ 7.04% 6.99% 173, Constitutional Funds² Pré 7.23% 7.32% 6, Financing of Investments US$ + Libor³ 6.30% 5.97% 7, , Applied in working capital Rural Credit Pré 12.86% 10.89% 316, Constitutional Funds² Pré 10.50% 10.50% 303, Working Capital Pré 15.50% 15.46% 20, Working Capital CDI 15.20% 15.20% 363, External Loans CDI 15.33% 15.32% 449, External Loans US$, Libor³+Pré 5.42% 5.09% 155, ,609, Total Indebtedness 12.33% 12.09% 1,797, Gain and losses with derivates connect with applications and debts (5) (16.657) (14.188) (=) Adjusted Debt 1,814, (-) Cash 596, (=) Adjusted Debt 1,217, EBITDA of last 12 months ,877 Adjusted Net Debt/Adjusted EBITDA (4) 5.05x 4,47x Adjusted Net Debt 27.2% 32.0% (1) Long-Term Interest Rate (TJLP) (2) To calculate the average cost of the Constitutional Funds, we considered a discount of 15% relative to the performance bonus applicable to these operations. (3) London Interbank Offer Rate (Libor): Interest rate charged by London banks used as a reference for most loans in the international financial system. (4) Adjusted EBITDA in the last 12 months. (5) Transactions with gains and losses from Derivatives (note 19 of the Quarterly Information). Page 25 of 35

26 The Adjusted Net Debt/Adjusted EBITDA ratio increased from 4.47 times in 2Q16 to 5.05 times in 3Q16, since adjusted net debt increased 3.96% and Adjusted EBITDA decreased 5.88%. The Adjusted Net Debt/Net Asset Value ratio ended the quarter at 27.2%, compared to 32.0% in 2Q15. Figure 15 Gross Debt Profile in 3Q % (1) 90,98% Figure 14 Amortization Schedule of Adjusted Net Debt in 3Q16 895,041 56,17% 43,83% 403, (2) 9,02% Short Term Long Term R$ US$ 268, ,810 22,809 61, After 2020 (1) Weighted average debt cost in BRL. (2) Weighted average debt cost in USD INDICATORS The Company believes that the calculation of Return on Equity, Return on Net Assets and Return on Invested Capital should consider, in addition to operating income in the period, the net annual appreciation (based on the report of an independent auditor prepared every year) in the value of its land. Table 30 Return on Equity (R$ million) Net Profit Net Land Appreciation SLC Agricola (1) Net Land Appreciation LandCo (1)(2) Subtotal Shareholder s Equity (3) 1,839 2,063 2,407 2,924 3,608 3,748 Return on Equity 1.3% 16.4% 12.8% 16.1% 13.8% 7.0% (1) Based on the independent appraisal report (Deloitte), net of taxes, updated in July (2) Adjusted by the interest of 81.23% held by SLC Agrícola in SLC LandCo. (3) Adjusted by the appreciation in the value of land properties. Table 35 Return on Net Assets (R$ million) Net Profit Net Land Appreciation (1) (36) Subtotal Invested Capital 2,598 3,196 3,635 4,113 4,696 4,906 Working Capital Fixed Asset (2) 2,203 2,692 3,009 3,472 3,963 4,278 Retorno 0.9% 10.6% 8.5% 11.4% 10.6% 5.3% (1) Based on the independent appraisal report (Deloitte), net of taxes, updated in July (2) Adjusted by appreciation of land. Page 26 of 35

27 Table 36 Return on Invested Capital (R$ million) Operating Income Taxes 30.1% 33.7% 49.8% 23.1% 21.3% 27.3% Taxes Nominal (38) (87) (72) (35) (40) (78) Adjusted Operating Income Net Land Appreciation (1) (36) Operating Result Working Capital 2,110 2,527 2,987 3,753 4,329 4,788 Gross Debt (CP e LP) (2) ,170 1,332 1,711 Cash (2) Net Debt (2) ,040 Shareholder s Equity (3) 1,771 2,018 2,333 2,781 3,352 3,748 Return on Invested Capital 2.5% 13.8% 11.5% 13.0% 13.3% 7.2% (1) Based on the independent appraisal report (Deloitte), net of taxes, updated in July (2) Adjusted by the interest held in the subsidiaries.. (3) Adjusted by appreciation of land. Table 37 Net Asset Value (R$ million) 9M16 SLC Agrícola Farms (1) SLC LandCo Farms (2) 638 Infrastructure (excl. land) (3) 777 Accounts Receivable (excl. derivates) (3) 259 Inventories (3) 791 Biological Assets (3) 132 Cash (3) 568 Subtotal Suppliers (3) 160 Adjusted Gross Debt (3)(4) Outstanding debt related to land acquisitions (3) 63 Subtotal Net Asset Value Net Asset Value per share 39,3 (1) Based on an internal study considering market information updated in June 2016, net of taxes. (2) Based on the independent appraisal report (Deloitte), net of taxes, updated in June 2016 and adjusted by the interest held by SLC Agrícola in the subsidiary. (3) Adjusted by the interest held by SLC Agrícola in the subsidiaries. (4) Gross Debt adjusted by operations with derivative instruments and the interest held by SLC Agrícola in the subsidiaries. Table 38 Changes in Working Capital Working Capital (R$ thd) M16 Assets Trade Accounts Receivable 85, , , ,519 Hedge Accounting (Non-Cash) (5,278) (8,936) (26,639) (115,505) Investories 514, , , ,322 Biological Assets + (Non-Cash) (42,280) (20,185) (58,164) (12,810) Recoverable Taxes 78,361 98,566 89,321 80,347 Biological Assets 378, , , ,786 Biological Assets (Não-Caixa) (27,009) (17,684) (31,200) - Expenses incurred in advance 3,793 2,712 5,469 5,658 Subtotal 986,221 1,194,705 1,412,708 1,170,317 Liabilities Suppliers 236, , , ,994 Tax and Social Obligations 27,480 24,270 20,465 28,106 Others 223, , , ,625 Land payables (126,494) (49,689) (75,564) (71,001) Hedge Accounting (Non-Cash) (31,433) (51,651) (120,544) (62,789) Provisions 16,187 17,724 20,415 19,485 Subtotal 345, , , ,420 Total 640, , , ,897 Change in WC 10,017 92,678 5, ,319 Page 27 of 35

28 LOCATION OF UNITS REGIÃO DO CERRADO Propriedades da SLC Agrícola Propriedades da SLC LandCo Joint Venture com Grupo Dois Vales Joint Venture com Mitsui Co. MATRIZ PORTO ALEGRE - RIO GRANDE DOSUL. 3Q16 CONFERENCE CALL Date: Tuesday, November 9, 2016 Portuguese November 09, :00 a.m. (Brasilia) 8:00 a.m. (New York) 1:00 p.m. (London) Dial-in: +55 (11) Replay :+55(11) English November 09, :00 p.m. (Brasilia) 10:00 a.m. (New York) 3:00 p.m. (London) Dial-in: +55 (11) Dial-in NY: DISCLAIMER This release makes statements concerning future events that are subject to risks and uncertainties. These statements are based on the beliefs and assumptions of our Management and on the information currently available to the Company. Forward-looking statements include information on our current plans, beliefs or expectations, as well as those of the Company s directors and officers. Forward-looking statements include information on potential or assumed operating results as well as statements that are preceded, followed by or include the words "believe," "may," "will, "continue," "expect," "project," "intend," "plan," "estimate" or similar expressions. Forward-looking statements and information provide no guarantee of performance. Because they refer to future events, they involve risks, uncertainties and assumptions and as such depend on circumstances that may or may not occur. The Company's future results and creation of value for shareholders may differ significantly from the figures expressed or suggested in the forward-looking statements. Many factors that will determine these results and values are beyond our capacity to control or predict. Page 28 of 35