Record Grapes of Brazil in 2014

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2 Ministry of Agriculture, Livestock and Food Supply Strategic Management Offi ce Minister`s Offi ce PROJECTIONS OF AGRIBUSINESS Brazil 2013/14 to 2023/24 Long-Term Projections Brasília DF September 2014

3 2014 Ministério da Agricultura, Pecuária e Abastecimento. All rights reserved. Reproduction permitted provided the source is acknowledged. Responsibility for copyright texts and images of this work is the author. 5th edition. year 2014 Circulation: copies Preparation, distribution, information: MINISTRY OF AGRICULTURE, FISHERIES AND FOOD SUPPLY Strategic Management Office General Coordination of Strategic Planning Block D, 7th floor, room 752 CEP: Brasília / DF.: Tel (61) : Fax (61) [email protected] Customer Service: Editorial coordination: AGE / Mapa Impresso no Brasil / Printed in Brazil Catalogação na Fonte Biblioteca Nacional de Agricultura - BINAGRI Brazil. Ministry of Agriculture, Livestock and Food Supply. Projections of agribusiness : Brazil 2013/14 to 2019/20 Longterm Projections / Ministry of Agriculture, Livestock and Food Supply. Strategic Management Advisory Board. Brasília : MAPA/ACS, p. ISBN Agronegócio- Brasil. 2. Desenvolvimento Econômico. I. Título. II. Título : Brazil 2013/14 to 2019/20 Long-term Projections. AGRIS E71 CDU

4 TEAM: AGE/Mapa SGE/Embrapa João Cruz Reis Filho Renato de Oliveira Brito Geraldo da Silva e Souza Eliane Gonçalves Gomes José Garcia Gasques Eliana Teles Bastos Marco Antonio A. Tubino TECHNICAL PARTNERS: Alcido Elenor Wander (Embrapa) Aroldo Antônio O. Neto (Conab) Carlos Martins Santiago (Embrapa) Cid Jorge Caldas (Agroenergia/Mapa) Daniel Furlan Amaral (Abiove) Dirceu Talamini (Embrapa) Djalma F. de Aquino (Conab) Eledon Oliveira (Conab) Elieser Barros Correia (Ceplac) Erly Cardoso Teixeira (UFV) Fabio Trigueirinho (Abiove) Francisco Braz Saliba (Bracelpa) Francisco Olavo B. Sousa (Conab) Glauco Carvalho (Embrapa) Gustavo Firmo (Mapa) Joaquim Bento S. Ferreira (Esalq) Kennya B. Siqueira (Embrapa) Leonardo Botelho Zilio (Abiove) Lucilio Rogério Aparecido Alves (Esalq) Luis Carlos Job (Mapa) Luiz Antônio Pinazza (Abag) Milton Bosco Jr. (Bracelpa) Olavo Sousa (Conab) Tiago Quintela Giuliani (Mapa) Wander Sousa (Conab)

5 SUMMARY 1. INTRODUCTION 2. SCENARIOS OF PROJECTIONS 3. METHODOLOGY 4. RESULTS FOR BRAZIL a. Grains b. Coton Lint c. Rice d. Bean e. Corn f. Wheat g. Soybean Complex h. Coffee i. Milk j. Sugar k. Orange and Orange Juice l. Meat m. Pulp and Paper n. Tobacco o. Fruits 5. RESULTS OF REGIONAL PROJECTIONS 6. SUMMARY 7. BIBLIOGRAPHY ANNEX 1 - Methodological Note ANNEX 2 - Results Tables

6 LIST OF ACRONYMS ABIOVE - Associação Brasileira da Indústria de Óleos Vegetais ABRAF- Associação Brasileira de Produtores de Florestas Plantadas AGE - Assessoria de Gestão Estratégica BRACELPA- Associação Brasileira de Celulose e Papel CECAT - Centro de Estudos Estratégicos e Capacitação em Agricultura Tropical CNA - Confederação da Agricultura e Pecuária do Brasil CONAB - Companhia Nacional de Abastecimento CEPLAC - Comissão Executiva de Planejamento da Lavoura Cacaueira EMBRAPA Gado de Leite - Empresa Brasileira de Pesquisa Agropecuária FAO - Food and Agriculture Organization of the United Nations FAPRI - Food and Agricultural Policy Research Institute FGV - Fundação Getúlio Vargas IBGE - Instituto Brasileiro de Geografia e Estatística ICONE - Instituto de Estudos do Comércio e Negociações Internacionais IFPRI - International Food Policy Research Institute IPEA - Instituto de Pesquisa Econômica Aplicada MAPA - Ministério da Agricultura, Pecuária e Abastecimento OECD - Organization for Economic Co-Operation and Development ONU - Organização das Nações Unidas SGE- Secretaria de Gestão Estratégica UFV - Universidade Federal de Viçosa UNICA - União da Indústria de Cana-de-açúcar USDA - United States Department of Agriculture

7 6 1. INTRODUCTION This report is an update and revision of the report Projections of Agribusiness - Brazil 2012/13 to 2022/23, Brasília - DF, June 2013, published by the Strategic Management Office of Ministry of Agriculture, Livestock and Food Supply. The study aims to indicate possible directions of development and provide support to policy makers about the trends of the major agribusiness products. The results also seek to answer to a large number of users in various sectors of national and international economy for which the information now disclosed are of enormous importance. The trends indicated will identify possible trajectories, as well as to structure future vision of agribusiness in the global context for the country keep growing and conquering new markets. Projections of Agribusiness - Brazil 2013/14 to 2023/24 is a prospective view of the sector, the basis for strategic planning of MAPA - Ministry of Agriculture, Livestock and Supply. For their preparation the work of brazilian and international organizations were consulted, some of them based on models projections. Among the surveyed institutions highlight the work of the Food and Agriculture Organization of the United Nations (FAO), Food and Agricultural Policy Research Institute (FAPRI), International Food Policy Research Institute (IFPRI), Organization for Economic Co-Operation and Development ( OECD), United Nations (UN), United States Department of Agriculture (USDA), Policy Research Institute / Ministry of Agriculture, Forestry and Fisheries, Japan (PRIMAFF), Confederation of Agriculture and Livestock of Brazil (CNA), Fundação Getulio Vargas (FGV), Brazilian Institute of Geography and Statistics (IBGE), Institute for International Trade Negotiations (ICONE), Institute of Applied Economic Research (IPEA), National Supply Company (Conab), Embrapa Dairy Cattle, Energy Research Company (EPE), the Sugar Cane Industry Union (UNICA), Brazilian Association of Planted Forest Producers (ABRAF), Federation of Industries of São Paulo (FIESP), STCP Consulting, Engineering and Management, Brazilian Association of Pulp and Paper (BRACELPA), Brazilian Association of Vegetable Oil Industries (ABIOVE) and the Brazilian Agribusiness Association (ABAG). The study was conducted by a group of experts from the Ministry of Agriculture and Embrapa, which cooperated in various stages of preparation. Benefited also from the valuable contribution of people / institutions who analyzed the preliminary results and reported their

8 7 comments, views and ideas on the results of the projections. Observations related to these collaborations were included in the Report, without nominate partners, but the institutions to which they belong. 2. SCENARIOS OF PROJECTIONS The scenario of rising prices should remain in Figure 1 shows the quarterly prices received by U.S. farmers for crops and livestock. Despite the relative price fluctuations, the trend since 2005 has been lifting. Note that the prices of livestock products in 2014 have higher growth rates than crops. Fig. 1 - Prices Received by Farmers in the United States livestock Crops Index / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /2014 Source: NASS/USDA, 2014.

9 8 Domestic prices in Brazil have also shown a tendency to increase in some products as shown in Table 1. For some products, such as soybeans, corn, cattle, rice and cotton prices have shown a trend of growth in The prices for these products in 2014 are higher than the historical rates and also the prices of Table 1 Prices received by Farmers in Brazil Product Unit Historical price Wheat R$/t Soybean R$/SC 60kg Corn R$/SC 60kg Bovine R$/@ Rice R$/SC 50kg Cotton Cent./libra peso Source: Cepea/Usp. Position at 17/04/2014 Brazil expects a record grains harvest in 2014, estimated at million tons. 3. METHODOLOGY The projections cover the period 2013/14 to 2023/24. In general, the basic period of the projections cover 20 years. Taking into account the last year experience, we decided to use, this year as a basic reference period information after Between 1994 and today, as we know, entered a phase of economic stabilization and this allowed a reduction of uncertainty in variables.

10 9 The projections were performed using specific econometric models. They are time series models that have great use in forecasting series. The use of these models in Brazil, for the purpose of this report is unprecedented. We are not aware of published studies in the country who have worked with these models. Three statistical models were used: exponential smoothing, Box- Jenkins (Arima) and State-Space Model. There is a methodological note (Annex 1) which presents the main characteristics of the three models. The projections were performed for 26 agribusiness products: corn, soybeans, wheat, orange, orange juice, chicken, beef, pork, sugar cane, sugar, cotton, soybean meal, soybean oil, fresh milk, beans, rice, potatoes, cassava, tobacco, coffee, cocoa, grape, apple, banana, pulp and paper. The report, however, not discussed all products, but their data are shown in the tables that are part of the Annexes of the study. The choice of the most likely model was made as follows: 1 Consistency of results; 2 International comparisons of data production, consumption, export, import and trade in the country and the world.; 3 last trend of our data; 4 Growth Potential; 5. Consultations with experts. The projections were generally for production, consumption, export, import and planted area. Some tests with productivity of some crops were conducted. The tendency was to choose more conservative models and not those indicated bolder growth rates. This procedure was used for selecting the most selected results. The projections presented in this report are national, where the number of products studied is comprehensive; and regional, where the number of analyzed products is restricted and has specific interest.

11 10 The projections are accompanied by prediction intervals which become wider with time. The greatest breadth of these ranges reflects the greater uncertainty associated with more distant the last year of the series used as the basis of the projection forecasts. 4. RESULTS FORECASTS FOR BRAZIL a. Grains Projections of grains refers to the 15 products surveyed monthly by CONAB as part of their harvest surveys. This set of products is called grains by Conab. As of this update projections already has the data to the eighth survey of harvest (May survey) for the soy complex products, corn and other products, was used for the 2013/2014 harvest data released by Conab( 2014 ): soybean, soybean oil, soybean meal, corn, beans, meat (beef, chicken, pork), and sugar cane. Thus, the data from 2013/2014 are projections Conab. The projections in this report for these products starting in 2014/2015. The estimates of grain production point to a crop of million tons in 2013/14, and a planted area of 56.4 million hectares (Conab 2014). These two variables are the largest that have been achieved in Brazil over the years.

12 11 Table 2 Planted area and Production of Grains Year Production (thousand tons) Planted Area (thousand hectares) Projection Up limit. Projection Up limit 2013/14 193,566-56, /15 199, ,428 58,553 61, /16 205, ,469 59,741 65, /17 211, ,349 60,729 68, /18 217, ,257 61,654 70, /19 223, ,002 62,555 72, /20 228, ,458 63,448 75, /21 234, ,744 64,338 77, /22 240, ,874 65,227 78, /23 246, ,879 66,115 80, /24 252, ,778 67,004 82,624 Source: AGE/Mapa and SGE/Embrapa with Conab information. * Models used: Space states. Variation % 2013/14 to 2023/24 Production 30.4% Planted Area 17.8%

13 12 Fig. 2 Planted area and Production of Grains Planted Area (thousand hectares) Produc>on (thousand tons) 300, , , , , , ,000 56,861 67,004 50, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa For 2014/2015 the production expected to be between million and million tons of grains. This range of variation is a safety for the occurrence of changes over which one has or little control such as climate change droughts and rains. Projections for 2023/2024 are a crop around million tonnes, representing an increase of 30.4% over the current crop. At the upper end projection indicates a production of up to million tons in 2023/24. The grain area should increase 17.8% between 2013/14 and 2023/24, from 56.9 million in 2013/2014 to 67.0 million in 2023/2024, which corresponds to an annual increase of 1.6 %.

14 13 Table 3 Brazil: Planted Area with Five Main Grains 2004/ / / / / / / / / /14 Rice Bean Corn Soybean Wheat Total 3,916 3,018 2,967 2,875 2,909 2,765 2,820 2,427 2,400 2,417 3,949 4,224 4,088 3,993 4,148 3,609 3,990 3,262 3,075 3,359 12,208 12,964 14,055 14,766 14,172 12,994 13,806 15,178 15,829 15,726 23,301 22,749 20,687 21,313 21,743 23,468 24,181 25,042 27,736 30,105 2,756 2,362 1,758 1,852 2,396 2,428 2,150 2,166 2,210 2,617 46,131 45,317 43,554 44,799 45,368 45,263 46,947 48,075 51,250 54, / / / / / / / / / /24 Rice 2,318 2,220 2,121 2,022 1,924 1,825 1,726 1,627 1,529 1,430 Bean 3,245 3,131 3,016 2,902 2,788 2,674 2,559 2,445 2,331 2,217 Corn 15,659 15,874 15,993 16,080 16,188 16,303 16,412 16,520 16,630 16,739 Soybean 31,598 32,764 33,785 34,751 35,697 36,633 37,565 38,496 39,427 40,357 Wheat 2,676 2,734 2,793 2,851 2,910 2,968 3,027 3,085 3,144 3,203 Total 55,495 56,722 57,708 58,606 59,506 60,402 61,289 62,174 63,060 63,945 Source: AGE/Mapa and SGE/Embrapa

15 14 b. Cotton lint Cotton production is concentrated in the states of Mato Grosso, Goiás and Bahia, which account for in 2013/ % of the country s production. Mato Grosso has the lead with 56.2% of the national production been folloed by state of Bahia, with 29.8% of the Brazilian production, and Goiás, with 4.9%. COTTON LINT National Production Harvest Year 2013/2014 (Thousand tons) Major producing states % 1, MATO GROSSO GOIÁS BAHIA 29.8 MT BA GO Total 1, Source: Conab - survey june/2014 The projections for cotton lint production indicate 1.67 million tons in 2013/2014 and 2.35 million tons in 2023/24. This expansion corresponds to a growth rate of 3.1% per year over the projection period and an increase of 40.5% in production. Some analysts noted that the projected production is quite high. What has been argued is that with the emergence of new technologies is possible to obtain higher yields. However, what we have checked is that the research has reached a stage where progress in productivity levels is proving slow or stagnant. It was also observed that

16 the projection for 2014/15, 2,143 thousand tons may not occur and that the tendency is to fall short, close to 2013/14 production of 2013/14, 1,672 thousand tons of cotton lint. The consumption of this product in Brazil should grow at an annual rate lower than 1.0% in the next ten years, reaching a total of 939 thousand tons consumed in 2023/24. Exports are also forecast strong growth, 55.4% between 2013/14 a 2023/24 The report from the U.S. Department of Agriculture (USDA, 2014) indicates that Brazilian exports between 2013/14 and 2023/24 will more than double, with the country that should increase its exports in the next 10 years. Also according to this source, in a few years Brazil will overtake Central Asia as the third largest source of cotton for export. Brazil has exported to large number of countries, but the main importers in 2013 were South Korea, Indonesia, China, Argentina and Vietnam. 15

17 16 Table 4 Production, Consumption and Export of Cotton Lint (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 1, /15 2,143 2, , /16 1,900 2, , , /17 1,719 2, , , /18 2,099 2, , , /19 2,271 2, , , /20 2,072 2, , , /21 2,135 2, , , /22 2,411 3, , , /23 2,426 3, , , /24 2,350 2, , ,892 Source: AGE/Mapa and SGE/Embrapa with Conab information. * Models used: Production- Space states. Consumption and exports PRP Variation % 2013/14 to 2023/24 Production 40.5% Consumption 4.4% Exports 55.4%

18 17 Fig. 3 Production, Consumption and Exports of Cotton Lint Produc4on Consump4on thousand tons 3,000 2,500 2,000 1,500 1, ,672 2, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa c. Rice Although the rice is a common culture in most of the country, most of the production occurs in 5 states - Rio Grande do Sul, with predominantly irrigated rice concentrates 65.8% of production in 2013/14, Santa Catarina, 8.7% of production, Mato Grosso, 5.2%, Maranhão,5.4 % and Tocantins,4.4% of national production. In the Northeast, especially in the state of Ceará rice is irrigated and concentrated on irrigation projects. A small amount is also produced in the states crossed bythe São Francisco river pass, as Bahia, Sergipe, Alagoas and Pernambuco and these areas also receive irrigation.

19 18 MARANHÃO MATO GROSSO TOCANTINS RICE Harvest Year 2013/2014 (Thousand tons) % 5.2 National Production 12, RS Major producing states SC MA MT TO SANTA CATARINA RIO GRANDE DO SUL Total 10, Source: Conab - survey june/2014 The projected production for 2023/24 is 13.6 million tons, and consumption of 12.2 million tons. We projected to increase 11.3% in rice production over the next 10 years. This increased production is expected to occur mainly through the growth of irrigated areas. The projected increase in production is apparently low, but it is equivalent to the projection of consumption over the next 10 years. The relative stabilization of the projected consumption of rice is consistent with the data supply Conab in recent years, around 12 million tons in 2013/14 (Conab, 2014). The estimates for the projection of rice planted area show that the area reduction will occur in the coming years. According to the projections it may fall of 2.4 million hectares in 2013/14 to 1.40 million hectares in 2023/24. According Conab technicians consulted, the area reduction is not likely to occur. The same is shared by researchers at

20 Embrapa Rice and Beans. In Rio Grande do Sul, which is now at 1.0 million hectares should remain in that number or even decrease because rice has had to compete with soybean and corn. The new Brazilian Forest Code limits the incorporation of new areas and the opportunity for Highlands Rice for years to come is in the crop rotation, renovation, rehabilitation or renovation of degraded or even livestock grazing in the transition to agriculture (Santiago, Carlo. Embrapa, 2013). The productivity should be the main variable in the behavior of the product in the coming years. The projection indicates a productivity of 5.5 tonnes per hectare, about 300 kg more than the current productivity of 5.2 tonnes per hectare. But rice is concentrated in areas of Rio Grande do Sul where the current yield is 7.5 tons per hectare (Conab, 2014). The consumption of rice in the coming years is expected to grow at 0.2% per year. According to technicians of Embrapa, the projected consumption seems appropriate to the current reality, even if the calculations of apparent per capita consumption have shown declines in recent years. To change this long-term trend, only if Brazil can develop new ways to use and consumption of rice (made from grains of rice products, which depends on R & D and, especially industry, became interested in the subject, which did not can be seen today). 19

21 20 Table 5 Production, Consumption and Rice Imports (thousand tons) Year Production Consumption Imports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 12,251-12,000-1, /15 12,703 15,285 12,023 12, , /16 12,807 16,459 12,047 12, , /17 12,910 17,383 12,070 12, , /18 13,014 18,179 12,094 13, , /19 13,118 18,892 12,117 13, , /20 13,222 19,547 12,141 13, , /21 13,326 20,158 12,164 13, , /22 13,429 20,734 12,188 13, , /23 13,533 21,280 12,211 13, , /24 13,637 21,803 12,235 13, ,208 Source: AGE/Mapa and SGE/Embrapa with CONAB information * Models used: Production, Consumption and Imports, PRP Variation % 2013/14 to 2023/24 Production 11.3% 8.2% Consumption 2.0% Imports -32.9%

22 21 Fig. 4 - Production, Consumption and Rice Imports Produc4on Consump4on Imports thousand tons 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2, ,251 13,637 12,000 12,235 1, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa d. Bean The geographical distribution of the main producers of beans in the country can be seen on the map. The product is fairly distributed across several states, although the main are Paraná, Minas Gerais and Mato Grosso, which currently produce 74.9% of national production. Such as rice, beans are part of the basic diet of Brazilians. It is the product that more has the production, a trend that should continue in the next years production. Imports are always to fill a small gap between production and consumption (Santiago, C. Embrapa, 2013, and Conab, 2014).

23 22 CEARÁ 5.2 National Production 3, Major producing states PR MG BEAN Source: Conab - survey june/2014 Harvest Year 2013/2014 (Thousand tons) % MT BA GO CE Total 2, MATO GROSSO GOIÁS MINAS GERAIS PARANÁ BAHIA 8.1

24 According to technicians of Embrapa Rice and Beans, each year increases the discussions on production focused exclusively on the domestic market.there are some varieties of beans that can be used for export. If this new opportunity consolidates the projection of production will have to be adjusted upward. The variation designed for consumption is 3.6%, which is higher than the production variation. Annual average consumption has been 3.5 million tonnes, requiring small amounts of imports. If confirmed projections of production, should be no need to import beans in the coming years. Over the past five years, Brazil has imported annually between and tonnes of beans (Conab, 2014). The opinions of Conab and Embrapa technicians is that there may be major changes in the beans in the coming years. Productivity is expected to increase from current levels as producers of soybeans and corn are producing beans destined for export to China, India and some African countries. The Northeast, although a large producer of this product has imported beans from other states in periods of drought. Mato Grosso has produced beans for export. Some states such as São Paulo and Minas Gerais has been having problems with regards to pests and diseases that attack crops of this product and so far have struggled to adequately control these attacks. 23

25 24 Table 6 Production, Consumption and Bean Imports (thousand tons) Year Production Consumption Imports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 3,714-3, /15 3,179 3,835 3,463 3, /16 2,928 3,644 3,475 4, /17 3,268 3,990 3,488 4, /18 3,227 4,066 3,500 4, /19 3,036 3,949 3,513 4, /20 3,164 4,096 3,525 4, /21 3,205 4,193 3,538 4, /22 3,099 4,149 3,550 4, /23 3,129 4,209 3,563 4, /24 3,173 4,292 3,575 4, Source: AGE/Mapa and SGE/Embrapa with CONAB information *Models used: To Production, ARMA Models, to Consumption and Imports, PRP Variation % 2013/14 to 2023/24 Production -14.6% Consumption 3.6% Imports 24.0%

26 25 Fig. 5 Production, Consumption and Bean Imports thousand tons 4,000 3,500 3,000 2,500 2,000 1,500 1, Produc4on Consump4on Imports 3,714 3,575 3,450 3, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa e. Corn The national maize production in the country is relatively sparse. The main producing states, Mato Grosso, Paraná, Minas Gerais, Goiás, Mato Grosso do Sul and Rio Grande do Sul should answer in 2013/14 by 70.0% of national production. But the major producing regions are South, the with 31.5% of the national production and Midwest with 42.0%. In South leadership is of Paraná, and in the Midwest, Mato Grosso. These are currently the main producers of corn in the country. But Minas Gerais, Goias and Rio Grande do Sul Minas also account for an important part of national production as shown on the map

27 26 MT PR CORN National Production Harvest Year 2013/2014 (Thousand tons) Major producing states 77, ,839.3 % , MS 7, MG 6, GO 7, RS 5, MATO GROSSO DO SUL MATO GROSSO 21.6 PARANÁ GOIÁS MINAS GERAIS RIO GRANDE DO SUL BAHIA 4.2 SÃO PAULO SANTA CATARINA SP 3, SC 3, BA 3, Total 70, Source: Conab - survey june/2014 The forecast for corn production in Brazil for 2013/14 is estimated at 77.9 million tonnes (Conab, 2014). For 2014/15 the projected production is between 80.7 and 93.9 million tons as the upper limit of the projection. But the tendency is the production lie nearest the projection. For 2023/24 production is projected million tons. As is well known, in Paraná and Mato Grosso, the biggest producers, soybean areas release space for planting corn. In Mato Grosso it is usual to plant soybeans around 15 September and harvest in January to then start the second maize crop. The limit for this planting is February because the risk of loss due the dry season are great if this period is exceeded. The corn area will increase by 6.4% between 2013/14 and 2023/24, from 15.7 million hectares in 2013/14 to 16.7 million, reaching 22,1 million

28 hectares in 2023/24. There will be no need for new areas to expand this activity as soybean areas release the majority of the areas required by corn. The increase in projected area 6.4% is below the growing rate of the past 10 years, that was 25.5%. But the corn had in recent years high productivity gains resulting in less need for additional areas. The domestic consumption of corn in 2013/14 represents 69.0 % of production should decrease to 62.2 %. Corn exports must pass 21 million tons in 2013/14 to 33.7 million tons in 2023/24. To maintain domestic consumption projected of 64.0 million tons and ensure a reasonable volume level of ending stocks and exports projected, the projected production shoult be of million tons, sufficient to meet the demand in According to technicians working with this culture area should increase more than is being projected and perhaps get closer to its upper limit of growth (See Figure 8) 27

29 28 Table 7 Production Consumption and Corn Export (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 77,887-53,818-21, /15 80,717 93,896 54,876 56,652 22,806 30, /16 83, ,811 55,868 58,892 25,001 35, /17 86, ,583 56,868 60,927 25,910 37, /18 88, ,940 57,899 62,859 26,790 39, /19 91, ,488 58,936 64,675 28,018 41, /20 93, ,947 59,967 66,396 29,192 44, /21 96, ,846 61,000 68,055 30,298 46, /22 98, ,980 62,034 69,665 31,425 48, /23 101, ,617 63,068 71,234 32,565 50, /24 103, ,603 64,102 72,770 33,698 52,237 Source: AGE/Mapa and SGE/Embrapa with CONAB information * Models used: To production, Consumption and Exports, State Space Models. Variation % 2013/14 to 2023/24 Production 32.4% Consumption 19.1% Exports 60.5%

30 29 Fig. 6 Corn Production Projec4on Up limit. 160, , ,603 thousand tons 120, ,000 80,000 60,000 77, ,121 40,000 20, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa Fig. 7 Corn Consumption Projec4on Up limit. 80,000 72,770 70,000 60,000 50,000 40,000 30,000 20,000 53,818 64,102 10, / / / / / / / / / / /24 thousand tons Source: AGE/Mapa and SGE/Embrapa

31 30 Fig. 8 Planted Area of Corn Up limit. ProjecAons 22,149 15,726 16, / / / / / / / / / /23 thousand tons 2023/24 Projection Variation(%) 20013/14 a 2023/24 6,4 to a 40,8% Source: AGE/Mapa and SGE/Embrapa

32 31 f. Wheat Wheat production in the country is concentrated in the South, and Rio Grande do Sul and Paraná are the major producers. In 2013/14 harvest, the forecast indicates that Paraná are responsible for 51.9% of the country s production and Rio Grande do Sul by 40.4%. The participation of other states, is of the order of 7.7%. This participation is distributed between Santa Catarina, São Paulo, Minas Gerais and Mato Grosso do Sul. WHEAT Harvest Year 2013/2014 (Thousand tons) % National Production 7, ,0 Major producing states RS 2, PR 3, Total 6, Source: Conab - survey june/ PARANÁ RIO GRANDE DO SUL Wheat production in 2013/14 crop is being estimated by Conab in 7.4 million tons; this is the largest crop that Brazil already had. The projected production for 2023/24 is 10.0 million tons, and consumption of 14.3 million tons in the same year. The domestic consumption of wheat in the country is expected to grow 17.4% between 2013/14 and 2023/2024.

33 32 The domestic supply will require imports of 5.3 million tonnes in 2023/24. In recent years, imports has been set between 5.8 and 7.0 million tons, and the most frequent import volume has been 6 million tonnes with an outflow in nearly 2.4 billion dollars in Although the increase in wheat production in coming years by more than 30%, Brazil should remain as one of the world s largest importer. The USDA report estimated Brazilian wheat imports of 8 million tons in 2023/24 (USDA, 2014). Table 8 Production, Consumption and Imports of Wheat (thousand tons) Year Production Consumption Imports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 7,373-12,192-5, /15 7,635 10,519 12,405 13,443 5,478 7, /16 7,897 11,975 12,617 14,086 5,456 7, /17 8,158 13,154 12,830 14,628 5,433 8, /18 8,420 14,188 13,042 15,119 5,411 8, /19 8,682 15,131 13,255 15,577 5,389 9, /20 8,944 16,008 13,468 16,011 5,367 9, /21 9,205 16,836 13,680 16,428 5,345 9, /22 9,467 17,625 13,893 16,830 5,322 10, /23 9,729 18,381 14,105 17,221 5,300 10, /24 9,991 19,111 14,318 17,602 5,278 10,728 Source: AGE/Mapa and SGE/Embrapa with CONAB information. * Models used: To Production and Consiumptiion, State Space model, and to Export, PRP model. Variation % 2013/14 to 2023/24 Production 35.5% Consumption 17.4% Imports -4.0%

34 33 Fig. 9 - Production, Consumption and Import of Wheat Produc4on Consump4on Imports thousand tons 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2, ,318 12,192 7,373 9,991 5,500 5, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

35 34 g. Soybean Complex Soybean Soybean production expected in the country in 2013/14 is 86.1 million tons Soybean production in Brazil is led by the states of Mato Grosso, with 31.4% of national production; Paraná with 17.1%, Rio Grande do Sul with 14.8%, and Goiás, 10.0%. But, as shown on the map, soybean production is also evolving into new areas in Maranhão, Tocantins, Piauí and Bahia, which in 2013/14 accounted for 10.1% of Brazilian production which corresponds to a production of 8.7 million tons of soybean. This is a region located in the center northeast of the country, which has shown strong potential for grain production, called Matopiba. Despite its deficiencies infrastructure, still attractive price land, the climate, the possibility of deploying large areas and favorable relief, have been several factors that have motivated investments in the region. SOYBEAN National Production 86, Major producing states MT 27, PR Harvest Year 2013/2014 (Thousand tons) % 14, MATO GROSSO DO SUL MATO GROSSO 31.4 PARANÁ Goiás 17.1 BAHIA 3.8 RS 12, GO 8, MS 6, BA 3, Total 72, Source: Conab - survey june/ RIO GRANDE DO SUL

36 The projection of soybeans for 2023/24 is million tonnes. This number represents an increase of 36.9% over the production of 2013/14. But it is a percentage that is lower than the growth recorded in the last 10 years in Brazil, which was 64.5% (Conab, 2014). Consumption projections indicate that there must be a large increase in demand for soybean in the international and domestic market. In this market, besides the demand for animal feed, is expected a strong increase in consumption of soybean for bio diesel production, estimated in 2014 by ABIOVE between 10.4 and 12 million tons. This variation depends on the scenario regarding the participation of soybean oil for biodiesel production (ABIOVE matching ). Domestic consumption of soybean is expected to reach 50.4 million tonnes by the end of the projection. Consumption is projected to increase 25.8% by 2023/24. This estimate is close to the growth observed in recent years by Conab of 23.0% within 6 years. There should be an additional consumption of soybean in relation to 2013/14 of around 10.0 million tonnes. As is well known, soybean is an essential component in the manufacture of animal feeds and is gaining importance in human nutrition. The soybean area should increase 10.3 million hectares over the next 10 years, arriving in 2024 to 40.4 million hectares. It is a crop that will more expand area over the next decade. It represents an increase of 34.1% over the area with soybeans in 2013/14. In the new areas of the Center Northeast of Brazil, comprising the region of Matopiba, the soybean area should expand greatly according to Conab technicians. This information goes in the same direction as the results obtained in this work. In the present work, the area of grains in this region should expand by 16.3% over the next 10 years. This equates to reach the region area of 8.4 million hectares, which at its upper limit can reach 10.9 million hectares. In Paraná state, area can grow in the coming years taking areas of other cultures. In Mato Grosso expansion should occur over degraded pastures and new areas, but mostly the first areas. But the trend in Brazil is that the expansion of the area occurs mainly on natural pasture lands. Exports of soybeans designed for 2023/2024 is 65.2 million tonnes, Representing an increase of 19.9 million tonnes for the quantity exported by Brazil in 2013/14. 35

37 36 The expected change in 2024 relative to 2013/14 is an increase in volume of soybeans exports in the order of 44.0%. The soybean export projections in this report are very similar to USDA projections, released in February this year. They design 66.5 million of exports for soybeans at the end of the next decade. This estimate is almost the same as that of this report, 65.2 million tons in 2024.

38 37 Table 9 Production, Consumption and Soybean Export (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 86,052-40,080-45, /15 89,831 98,215 41,233 45,698 47,292 52, /16 93, ,825 42,358 47,988 49,286 57, /17 96, ,549 43,391 49,739 51,281 60, /18 99, ,376 44,401 51,612 53,276 64, /19 102, ,921 45,414 53,329 55,270 67, /20 105, ,309 46,417 54,969 57,265 70, /21 108, ,624 47,420 56,583 59,260 73, /22 111, ,846 48,423 58,152 61,254 76, /23 114, ,999 49,425 59,688 63,249 79, /24 117, ,097 50,427 61,200 65,244 82,563 Source: AGE/Mapa and SGE/Embrapa with CONAB information. * Models used: To Production and Consiumptiion, State Space model, and to Export, PRP model. Variation % 2013/14 to 2023/24 Production 36.9% Consumption 25.8% Exports 44.0%

39 38 Fig. 10 Soybean Production Projec4on Up limit. thousand tons 160, , , ,000 80,000 60,000 40,000 20, , / / / / / / / / /22 139, , / /24 Source: AGE/Mapa and SGE/Embrapa Fig. 11 Soybean Consumption Projec4on Up limit. 70,000 60,000 61,200 thousand tons 50,000 40,000 30,000 20,000 40,080 50,427 10, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

40 39 Fig. 12 Soybean Export Projec4on Up limit. thousand tons 90,000 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10, , / / / / / / / / / /23 82,563 65, /24 Source: AGE/Mapa and SGE/Embrapa The expansion of soybean production in the country will give by the combination of area expansion and productivity. As production increases planned over the next 10 years is 36.9%, the expansion of the area is 34.1%. In recent years soybean productivity yield has remained stable at 2.7 tons per hectare, and that number is projected to be 3.0 tonnes per hectare in the next 10 years. Soybean should expand through a combination of frontier expansion in regions where there is still available land, pasture land occupation and substituting orther crops where there is no land available for incorporation. But the trend in Brazil is that the expansion occurs mainly on natural pasture lands. Figure 13 illustrates the projected area expansion in sugar cane and soybean, which are two activities that compete for the area in Brazil. Together these two activities in the coming years should presentan expansion area of 12.6 million hectares, 10.3 million hectares of soybean and 2.3 million hectares of cane sugar. The other crops should have little variation in area in the coming

41 40 years. However, it is estimated that expansion should occur in areas of great productive potential, as areas of cerrado understood in what is now called Matopiba for understanding land located in the states of Maranhão, Tocantins, Piauí and Bahia. Mato Grosso will lose strenghts in this process of expansion of new areas, mainly due to the price of land in this state that are more than double the price of crop land in the states of Matopiba (FGV-FGVDados). Because these new ventures regions include areas of great extent, the price of land is a decisive factor. Fig. 13 Area of Soybean and Sugar Cane Soybean Sugar cane** , , 30,105 8, , , 2013/ / / / / / / / / / /24 thousand hectare Soybean- Variation ,1 % Sugar cane - Variation ,2 % Source: AGE/Mapa and SGE/Embrapa * Area with soybean and cane will grouth 12.6 million hectare **refers to sugar - cane intended to production of alcohol and sugar.

42 41 Meal and Soybean Oil Meal and soybean oil showed moderate dynamism of production in the coming years. The soybean meal production should increase by 25.1% and 25.9% oil. These percentages are slightly higher than what has been observed in the last decade for both products. However, consumption of meal will have stronger growth than soybean oil, 35.2% and 23.1%, respectively. Exports of meal should increase 15.6% between 2014 and 2024 and 18.4% oil. Exports are presented in the coming years more dynamic domestic consumption in the case of soybean oil.

43 42 Table 10 Production, Consumption and Soybean Meal Export (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 28,105-14,100-13, /15 28,676 31,078 14,529 15,234 14,166 15, /16 30,079 33,173 15,046 16,085 14,389 17, /17 30,534 33,935 15,548 16,793 14,715 18, /18 31,041 34,918 16,019 17,463 14,783 18, /19 31,910 36,218 16,538 18,181 14,939 19, /20 32,562 37,158 17,049 18,851 15,128 20, /21 33,135 38,043 17,543 19,492 15,257 20, /22 33,856 39,082 18,050 20,143 15,394 21, /23 34,539 40,031 18,559 20,783 15,557 21, /24 35,168 40,919 19,061 21,407 15,701 22,422 Source: AGE/Mapa and SGE/Embrapa with CONAB information * Models used: To Production, Consumption and Export, Space state models. Variation % 2013/14 to 2023/24 Production 25.1% Consumption 35.2% Exports 15.6%

44 43 Table 11 Production, Consumption and Soybean Oil Export (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 7,118-5,500-1, /15 7,353 8,125 5,566 5,911 1,530 2, /16 7,510 8,481 5,642 6,225 1,562 2, /17 7,706 8,827 5,755 6,564 1,598 2, /18 7,886 9,164 5,880 6,913 1,622 2, /19 8,066 9,472 6,016 7,258 1,631 3, /20 8,247 9,773 6,161 7,597 1,637 3, /21 8,425 10,064 6,309 7,928 1,637 3, /22 8,604 10,347 6,461 8,250 1,635 3, /23 8,783 10,624 6,616 8,563 1,631 3, /24 8,961 10,896 6,772 8,869 1,626 4,036 Source: AGE/Mapa and SGE/Embrapa with CONAB information * Models Used: To Production, Consumption and Exports, State- Space Models. Variation % 2013/14 to 2023/24 Production 25.9% Consumption 23.1% Exports 18.4%

45 44 Fig. 14 Production, Consumption and Export of Soy- bean Meal Produc4on Consump4on Exports 40,000 thousand tons 35,000 30,000 25,000 20,000 15,000 10,000 5, ,105 35,168 19,061 14,100 15,701 13, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa Fig. 15 Production, Consumption and Exports of Soybean Oil thousand tons 10,000 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1, ,118 5,500 Source: AGE/Mapa and SGE/Embrapa 8,961 6,772 1,374 1, / /15 Produc4on Consump4on Exports 2015/ / / / / / / / /24

46 The domestic consumption of soybean oil forecast for 2023/24 is estimated at 6.8 million tons. Represents around 75.6% of projected production. Most of the oil is intended for human consumption and another part has been used to produce Biodiesel. According to ABIOVE in 2014, the average use of soybean oil for biodiesel should be between 2.0 and 2.3 million tons. This represents between 28.0 and 32.3% of soybean oil in 2013/14 harvest. For soybean meal, in the next decade, about 54.0% should be directed to domestic consumption, and 44.6% for exports. We analyzed the data sent by ABIOVE (2014), at our request, in the form of comments to these projections, and it generally converge toward the results presented in this report. 45

47 46 h. Coffee MG COFFEE Produção Nacional Harvest Year 2013/2014 (Thousand tons) Major producing states 2, ,511.8 % MINAS GERAIS ESPIRITO SANTO 26.0 ES Total 2, Source: IBGE - survey - june/2014 Coffee production has been showing unusual behavior in2014. Though a period called the High, the expected production this year is supposed to be lower than last year. This crop has a cycle called bienalidade where years there has been a high production and low production the next. Due to weather problems that occurred earlier this year affecting the main producing regions, the harvest expected in 2014 should be equal to or less than last year. Estimates for 2014 indicate a harvest of 46.9 million 60-kg bags, while last year was 49.2 million bags (DCAF-CONAB-ABIC-MDI / SECEX-OIC-CEPEA / ESALQ, BM & F, 2014 )

48 The projections show that the related production in 2023/24 should rise 30.6% compared to 2013/14. This change is equivalent to an annual growth rate of 2.5%. Consumption is estimated to grow 28.9% by 2023/24, the result of an annual growth rate of 2.4%. The consumption in Brazil has grown to an average annual rate of 4.8% according to the International Coffee Organization, OIC, while the world average has been 2.7% per year. The latest estimates of the Ministry of Agriculture indicate an average annual rate of per capita consumption in Brazil of 5.7% per year in the period (MAPA / DCAF, ABIC, Conab, 2014). Coffee exports are projected for 2023/24 at 40.0 million bags of 60 kg. This projected volume represents an increase of 24.0% compared to the exports of 2013/14, representing an average annual rate of 2.2%. It is expected that the country will continue as the world s largest producer and leading exporter as well as keep the usual buyers and valued partners in 129 countries in U.S., Germany, Japan and Italy imported 62.7% of the volume exported by Brazil in

49 48 Table 12 Production, Consumption and Exports of Coffee (million bags) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/ / / / / / / / / / / Source: AGE/Mapa e and SGE/Embrapa with Mapa/SPAE/DCAF and CONAB Information * Models Used: To production, consumption and Exports, State- Space Models. Variation % 2013/14 to 2023/24 Production 30.6% Consumption 28.9% Exports 24.0% i. Milk Milk was considered a product that has high growth potential. The production is expected to grow at an annual rate between 2.6% and 3.4%. This corresponds to a production of 44.7 billion liters of raw milk at the end of the period of the projections, 29.8% higher than the production year 2013/14.

50 49 According to technicians of Embrapa Dairy Cattle, the projected growth rates for production should be slightly above the projected in this report. According to them the milk production in Brazil rose more than 4.0% per year in recent years. Tabela 13 - Production, Consumption and Exports of Milk (million liters) Year Production Consumption Imports Exports Projection Up limit. Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 34,408-36,298-1, /15 36,322 37,897-37,310 40,069-1,047 2, /16 36,473 38,885 38,302 41,810 1,037 3, /17 38,377 41,016 39,290 43,420 1,028 3, /18 38,523 41,826 40,278 44,948 1,018 3, /19 40,425 43,927 41,265 46,419 1,008 4, , /20 40,569 44,623 42,253 47, , , /21 42,470 46,696 43,240 49, , , /22 42,613 47,315 44,228 50, , , /23 44,514 49,368 45,215 51, , , /24 44,657 49,933 46,203 53, , ,391 Source: AGE/Mapa e and SGE/Embrapa with IBGE/MDIC/Embrapa Gado de Leite information. * Models used: To Production and Consumption, ARMA model, to Imports and Exports, PRP models. Variation % 2013/14 to 2023/24 Production 29.8% Consumption 27.3% Imports -9.2% Exports 34.7%

51 50 Fig. 16 Milk Production Projec4on Up limit. thousand tons 60,000 50,000 40,000 30,000 20,000 34,408 49,933 44,657 10, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa Fig. 17 Production and Consumption of Milk. Produc4on Consump4on 50,000 46,203 thousand tons 40,000 30,000 20,000 10,000 36,298 34,408 44, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

52 51 Fig. 18 Import and Export of Milk Imports Exports thousand tons 1,200 1, , / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

53 52 Consumption is expected to grow at an annual rate between 2.4 and 3.3%, thus following the production of the country, but putting the consuption at a level slightly above the national production, it will require some import. j. Sugar The estimates obtained by AGE and SGE for Brazilian sugar production indicate an average annual growth rate of 3.3% in the 2013/2014 to 2023/2024 period. This rate should lead to a production of 52.9 million tons in Such production corresponds to an increase of 39.7% compared to 2013/14. These projections may be affected if the current situation is maintened where the prospects of the sugar and alcohol sector are not favorable. Investments have not been made in new units, several production units have paralyzed its activities over the past 3 seasons and many companies are indebted (Mapa / Agroenergia, 2014).

54 53 Table14 Production, Consumption and Sugar Exports (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 37,878-12,233-27, /15 40,330 44,074 12,261 13,640 27,824 32, /16 41,265 45,774 12,694 14,300 29,207 34, /17 42,937 48,304 12,963 14,881 30,352 37, /18 44,264 50,305 13,299 15,442 31,577 39, /19 45,749 52,415 13,607 15,970 32,775 41, /20 47,163 54,394 13,927 16,485 33,982 43, /21 48,608 56,365 14,242 16,983 35,186 44, /22 50,040 58,288 14,559 17,471 36,391 46, /23 51,478 60,190 14,875 17,949 37,596 48, /24 52,913 62,066 15,192 18,419 38,801 50,378 Source: AGE/Mapa and SGE/Embrapa with Mapa /SPAE/DCAA; Mapa /SRI and CONAB. information * Models used: To Production and Exports, Space State model, and to Consumption, ARMA model. Variation % 2013/14 to 2023/24 Production 39.7% Consumption 24.2% Exports 42.9% The projected rates for exports and domestic consumption for the next 10 years are, respectively, 3.7% and 2.3% per year. For exports, the forecast for 2023/2024 is a volume of 38.8 million tonnes.

55 54 Fig. 19 Production, Consumption and Sugar Exports 60,000 Produc4on Consump4on Exports thousand tons 50,000 40,000 30,000 20,000 10,000 37,878 52,913 27, ,233 15, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa Fig. 20 Sugar Production Projec4on Up limit. 70,000 60,000 62,066 thousand tons 50,000 40,000 30,000 20,000 37,878 52,913 10, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

56 55 Fig. 21 Sugar Exports Projec4on Up limit. thousand tons 60,000 50,000 40,000 30,000 20,000 27,154 50,378 38,801 10, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa k. Orange and Orange Juice The orange production should increase from 16.3 million tons in 2013/14 crop to 17.5 million tonnes in 2023/24. This variation corresponds to an annual growth rate of 0.7%. The area planted with orange should be reduced in the coming years. It should move from the current 717 thousand hectares hectares to 627 thousand. This indicates an annual reduction in the growth rate of 1.3% per year. Brazil is expected to export 2.6 million tonnes of orange juice at the end of the projection period. But that number may reach, at its upper limit, to 3.2 million tonnes of juice. Trade restrictions in the form of barriers to trade are the main limiting factor for the expansion of the orange juice.

57 56 Table 15- Production of Orange and Exports of Orange Juice (thousand tons) Year Production Projection Up limit. Projection Up limit. 2013/14 16,333-2, /15 16,452 19,051 2,179 2, /16 16,571 20,247 2,215 2, /17 16,689 21,191 2,272 2, /18 16,808 22,007 2,320 2, /19 16,927 22,739 2,372 2, /20 17,046 23,413 2,423 2, /21 17,165 24,042 2,474 2, /22 17,283 24,635 2,525 3, /23 17,402 25,200 2,575 3, /24 17,521 25,741 2,626 3,187 Source: AGE/Mapa and SGE/Embrapa with IBGE and SECEX/MDIC information * Models used: To Production, PRP model, and to Exports, Space States model. Exports Variation % 2013/14 to 2023/24 Production 7.3% Exports 25.4%

58 57 Fig. 22 Orange Production and Orange Juice Export Produc4on Exports thousand tons 20,000 16,000 12,000 8,000 4,000 16,333 17,521 2,094 2, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa

59 58 i. Meat Before presenting the projections of meat, we seek to illustrate the current distribution of cattle in Brazil, with respect to the number of animals slaughtered in Slaughtered this year were 34.4 million head across the country, and Mato Grosso, Mato Grosso do Sul, São Paulo, Minas Gerais, Goiás, Para and Rondonia, leading the slaughter, with 72.0% of slaughters in the country. PARÁ 7.1 National Production MT MS BOVINES Slaughtered Animals 2013/14 (head) Major producing states 34,411, ,837,857 % ,120, RONDÔNIA 6.7 MATO GROSSO DO SUL MATO GROSSO GOIÁS TOCANTINS MINAS GERAIS BAHIA SÃO PAULO SP 3,548, GO 3,466, MG 3,032, PA 2,447, RO 2,289, RS 1,920, PR 1,424, BA 1,309, TO 1,195, Total 30,593, Source: IBGE - quarterly survey of slaughtered animals - march/ RIO GRANDE DO SUL

60 59 Projections of meat for Brazil show that this sector should present strong growth in the coming years. Among meat, the projecting higher growth rates of production in the period are chicken, which is expected to grow annually at 3.1%, and swine, whose projected growth for this period is 2.8% per year. The beef production has a projected growth of 1.9% per year, which also represents a relatively high value because it can supply domestic consumption and exports. The total meat production will increase from 26.0 million tons in 2014 to 33.8 million in 2024, an increase of 30.0%.

61 60 Table 16 Meat Production (thousand tons) Year BEEF PORK CHICKEN Projection Up limit. Projection Up limit. Projection Up limit ,753-3,553-12, ,762 10,799 3,666 4,067 13,081 14, ,309 11,921 3,778 4,346 13,519 14, ,632 12,573 3,891 4,586 13,972 15, ,451 12,661 4,004 4,806 14,432 16, ,589 13,091 4,116 5,013 14,894 16, ,027 13,600 4,229 5,212 15,358 17, ,105 13,699 4,342 5,403 15,822 18, ,159 13,799 4,454 5,589 16,286 18, ,615 14,314 4,567 5,771 16,751 19, ,975 14,707 4,680 5,948 17,216 19,979 Source:a AGE/Mapa and SGE/Embrapa with CONAB. information * Models used: To Beef, ARMA model, to Pork, PRP models and to Chicken, State - Space. Variation % 2014 to 2024 Beef 22.8% Pork 31.7% Chicken 35.7%

62 61 Fig. 23- Beef Production thousand tons 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2, , Projec3on Up limit ,707 11, Source: AGE/Mapa and SGE/Embrapa Fig. 24 Pork Production Projec3on Up limit. thousand tons 7,000 6,000 5,000 4,000 3,000 2,000 1, , ,948 4, Source: AGE/Mapa and SGE/Embrapa

63 62 Fig. 25- Chicken Production Projec3on Up limit. thousand tons 25,000 20,000 15,000 10,000 5,000 12,691 19,979 17, Source: AGE/Mapa and SGE/Embrapa Projections show the consumption preferences of Brazilian consumers for chicken. The projected annual growth for the consumption of chicken is 2.9% in the period This is an increase of 33.1% in consumption for the next 10 years. Pork takes second place in consumption growth at an annual rate of 2.6% in the coming years. In the lower level of growth is located if the projection of beef consumption 1.5% per year next ten years.

64 63 Table 17 Meat Consumption (thousand tons) Year BEEF PORK CHICKEN Projection Up limit. Projection Up limit. Projection Up limit ,744-3,032-8, ,615 8,332 3,120 4,750 8,976 9, ,866 8,880 3,209 5,513 9,263 10, ,089 9,198 3,297 6,119 9,551 10, ,992 9,189 3,385 6,644 9,838 11, ,082 9,399 3,474 7,117 10,125 11, ,421 9,752 3,562 7,553 10,412 11, ,501 9,841 3,650 7,961 10,699 12, ,502 9,906 3,738 8,347 10,987 12, ,759 10,230 3,827 8,715 11,274 13, ,953 10,451 3,915 9,068 11,561 13,580 Source: AGE/Mapa and SGE/Embrapa with CONAB Information * Models: To Beef, ARMA Model, Pork and Chicken, PRP Variation % 2014 to 2024 Beef 15.6% Pork 29.1% Chicken 33.1%

65 64 Fig. 26 Meat Consumption Beef Pork Chicken thousand tons 14,000 12,000 10,000 8,000 6,000 4,000 8,689 7,744 3,032 11,561 8,953 3,915 2, Source: AGE/Mapa and SGE/Embrapa Regarding exports, the projections indicate high growth rates for the three types of meat analyzed. Estimates project a favorable environment for Brazilian exports. The chicken and pork lead the annual growth rates of exports in the coming years - the annual rate provided for chicken is 3.8% and for pork 3.9%. Exports of beef should be located on an annual average of 3.4%. Meat exports has led to numerous countries. In 2013 the beef was destinated to 143 countries, with the main Hong Kong; chicken was destinated for 144 countries, with Saudi Arabia the main buyer and finally the pork had 72 destination countries, whose main Russia. The expectation is that these markets are increasingly consolidate so that the projections are feasible.

66 65 Table 18 Meat Export (thousand tons) Year BEEF PORK POLTRY Projection Up limit. Projection Up limit. Projection Up limit , , ,143 2, ,181 4, ,223 2, ,323 4, ,305 3, ,527 5, ,388 3, ,680 5, ,471 3, ,890 6, ,555 3, ,029 5,046 6, ,638 4, ,082 5,258 6, ,722 4, ,133 5,415 6, ,805 4, ,182 5,627 7, ,889 4, ,230 5,784 7,478 Source: AGE/Mapa and SGE/Embrapa with CONAB information. *Models used: To Beef and Chicken meat, State Space models, to Pork, PRP Variation % 2014 to 2024 Beef 39.7% Pork 46.9% Poltry 44.5%

67 66 Fig. 27 Beef Export thousand tons 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, , Projec3on Up limit ,715 2, Source: AGE/Mapa and SGE/Embrapa Fig. 28 Export of Pork Projec3on Up limit. thousand tons 1,400 1,200 1, , Source: AGE/Mapa and SGE/Embrapa

68 67 Fig. 29 Export of Chicken thousand tons 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1, , Projec3on Up limit ,478 5, Source: AGE/Mapa and SGE/Embrapa m. Pulp and Paper Forest products represent the fourth rank in the value of exports of brazilian agribusiness, below the soybean complex, meat and sugar and alcohol complex. In 2013 the value of exports of forest products was $ 9.64 billion, and pulp and paper accounted for 74.3% of export value (Mapa / Agrostat, 2014). Pulp and paper and wood and articles thereof comprise this segment of agribusiness.

69 68 Table 19 Production, Consumption and Export of Pulp (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 15,736-6,327-9, /15 16,173 17,106 6,392 6,862 10,240 11, /16 16,675 17,952 6,531 7,034 10,621 11, /17 17,183 18,681 6,654 7,224 11,022 12, /18 17,651 19,410 6,759 7,356 11,403 13, /19 18,156 20,116 6,889 7,531 11,794 13, /20 18,640 20,789 7,001 7,678 12,183 14, /21 19,128 21,459 7,120 7,829 12,569 14, /22 19,622 22,113 7,241 7,984 12,959 15, /23 20,108 22,755 7,356 8,129 13,347 15, /24 20,599 23,392 7,476 8,279 13,735 16,375 Source: AGE/Mapa and SGE/Embrapa with BRACELPA information. *Models used: Production, Consumption amd Exports, Space States model. Variation % 2013/14 to 2023/24 Production 30.9% Consumption 18.2% Exports 39.4%

70 69 Fig Pulp Production Projec4on Up limit. 25,000 23,392 thousand tons 20,000 15,000 10,000 15,736 20,599 5, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa Fig Production, Consumption and Pulp Export Produc4on Consump4on Exports thousand tons 25,000 20,000 15,000 10,000 5, ,736 9,853 6, / / / / / / / / / /23 20,599 13,735 7, /24 Source: AGE/Mapa and SGE/Embrapa

71 70 Table 20 Production, Consumption and Paper Export (thousand tons) Year Production Consumption Exports Projection Up limit. Projection Up limit. Projection Up limit. 2013/14 10,759-10,125-1, /15 10,992 11,237 10,333 10,820 1,995 2, /16 11,267 11,565 10,598 11,243 2,055 2, /17 11,516 11,848 10,863 11,595 2,079 2, /18 11,776 12,136 11,102 11,923 2,122 2, /19 12,035 12,429 11,377 12,267 2,142 2, /20 12,289 12,704 11,601 12,562 2,190 2, /21 12,553 13,000 11,881 12,905 2,213 2, /22 12,805 13,269 12,102 13,188 2,261 3, /23 13,070 13,564 12,385 13,529 2,284 3, /24 13,320 13,830 12,605 13,805 2,332 3,229 Source: AGE/Mapa and SGE/Embrapa with BRACELPA Information * Models used:to Production, Consumption and Export, State Space Models. Variation % 2013/14 to 2023/24 Production 23.8% Consumption 24.5% Exports 20.4%

72 71 Fig. 32 Paper Production Projec4on Up limit. 16,000 14,000 12,000 10,000 8,000 6,000 4,000 10,759 13,830 13,320 2, / / / / / / / / / / /24 thousand tons Source: AGE/Mapa and SGE/Embrapa

73 72 Fig. 33 Production, Consumption and Paper Export thousand tons 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Produc4on Consump4on Exports 13,320 10,759 12,605 10,125 1,937 2, / / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa With regard to the paper, to supply domestic consumption growth of 2.2% annually over the next 10 years, and 1.8% of exports, it will be necessary to expand production faster than the projected rate, which is 2.2 % per year until 2023/2024. According to Bracelpa technicians production and paper consumption have historically accompanied the growth of GDP. Although the paper can find some demand problem, the projected growth in this report for the production seems small. For cellulose, the projection indicates that would be possible production can meet the growth in domestic consumption and exports of the sector.

74 73 n. Tobacco The inclusion of the projections of some variables related to Tobacco is justified by the importance of the product in the Brazilian trade balance and income formation in the producing regions. Its production occurs mainly in Rio Grande do Sul, Santa Catarina and Paraná. In 2014, these three states have planted an area of 392 thousand hectares, a total of 417 thousand hectares of land. In Northeast Brazil, there is some production in Alagoas and Bahia. In 2013, tobacco and its products have generated export revenues of $ 3.27 billion. The projected production for 2023/2024 is 1,060 tons. The projected area is 472 thousand hectares, obtained through an annual growth of 1.2% from 2013/14 until the end of the projections

75 74 Table 21- Tobacco Production Source: AGE/Mapa and SGE/Embrapa with IBGE information * Models used: To production, State - Space.. Production Year Projection Up limit. 2013/ / , / , / , / , / , / , /21 1,007 1, /22 1,021 1, /23 1,046 1, /24 1,060 1,483 Variation % 2013/14 to 2023/24 Production 22.6%

76 75 o. Fruits Among the fruits analyzed in this study, banana is the most widespread throughout the country. But 67.8% of production is in the states of São Paulo, Bahia, Minas Gerais, Santa Catarina, Ceará and Pará. Apple has its production located in Rio Grande do Sul and Santa Catarina and grape in Rio Grande do Sul, Pernambuco and Sao Paulo. The fruits have been growing in importance in the country, both domestically and internationally. In 2013, the export value of fresh fruit was U.S. $ million, slightly below the value exported in 2012, of $ 910 million (Agrostat / Mapa, 2014). Grapes, mangoes and melons are the fastest growing exports in terms of value. As can be seen in the maps of location, banana is the most widespread in the country, while apples and grapes have their more restricted to South and Northeast regions of production.

77 76 Harvest Year APPLE 2013/2014 % (Thousand tons) National Production 1,271, Major producing states RS 687, SC 530, Total 1,218, Source: IBGE - Systematic Survey of Agricultural Production - March / SANTA CATARINA RIO GRANDE DO SUL BAHIA 4.2 PERNAMBUCO 17.4 Harvest Year GRAPE 2013/2014 % (Thousand tons) National Production 1, Major producing states RS PE 759, , SP 158, PR 79, BA 56, SC 52, PARANÁ SANTA CATARINA RIO GRANDE DO SUL SÃO PAULO Total 1,343, Source: IBGE - Systematic Survey of Agricultural Production - March / 2014

78 77 PARÁ CEARÁ BAHIA 16.2 PERNAMBUCO 5.4 Harvest Year BANANA 2013/2014 % (Thousand tons) National Production 7,146, Major producing states SP BA 1,191,547 1,160, MG 764, PARANÁ MINAS GERAIS SÃO PAULO SANTA CATARINA ESPÍRITO SANTO 3.7 SC 649, PA 576, CE 501, PB 389, PR 269, ES 262, Total 5,765, Source: IBGE - Systematic Survey of Agricultural Production - March / 2014 Due to limited data, the projections were restricted to changing production and planted are of grape, apple and banana area. Unlike the orange area which is relatively significant, these fruits have much more restricted areas, and, as is the case of the grape which are cultivated under irrigation and high technological level. Among the three fruits, bananas are the one with the largest area. The projections of production until 2023/2024, show that the largest expansion will occur in apple production, 2.6% growth per year, followed by grapes, 1.9% per year for the banana, 0.9% per year. A joint production of apples, grapes and bananas should represent 4.0 million tons in 2023/24, representing an increase of 21.7% over 2014.

79 78 Table 22- Fruit Production (thousand tons) Year BANANAS (thousand bunche) APPLE GRAPE Projection Up limit. Projection Up limit. Projection Up limit ,271-1, ,306 1,488 1,413 1, ,344 1,560 1,424 1, ,381 1,638 1,459 1, ,418 1,707 1,483 1, ,456 1,774 1,513 1, ,493 1,838 1,539 1, ,530 1,900 1,567 1, ,568 1,961 1,595 2, ,605 2,020 1,622 2, ,642 2,078 1,650 2,117 Source: AGE/Mapa and SGE/Embrapa with IBGE information. * Models used: Banana, PRP and to Apple and Grapes, State Space model Fig. 34- Fruit Production (thousand tons) thousand tons 1,800 1,600 1,400 1,200 1, BANANAS (thousand bunche) APPLE GRAPE 1,650 1,361 1,642 1, Fonte: AGE/Mapa e SGE/Embrapa

80 79 5. RESULTS OF REGIONAL OUTLOOK Regional projections were made with the objective of identifying possible trends of selected products in major producing regions, and also show the predictions of a slightly more disaggregated. They are divided into two parts: regional projections of consolidated areas, and areas of recent expansion, located in central Brazil, and part of the Northeast. They are: Rice in Rio Grande do Sul; Corn in Mato Grosso, Paraná, Minas Gerais; Soybean in Mato Grosso, Rio Grande do Sul and Paraná; Wheat, Paraná and Rio Grande do Sul; and sugar cane in São Paulo, Paraná, Mato Grosso, Minas Gerais and Goiás. Was included, the area and production projections for the states of Maranhão, Tocantins, Piauí and Bahia, called MATOPIBA. The projections of these regions were also made to some municipalities in these localities, selected according to their importance in the production of grains. Regional projections were only for production and planted area because there aren`t more detailed information such as for the national projections.

81 80 Table 23 Regional Projections /2014 to 2023/2024 Selected States Production (Thousand tons) RICE - Thousand Tons Planted Area (Thousand ha) Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % RS 8, ,114 1, Sugar cane - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % GO 69,307 96, , MG 76, , , MT 19, PR 49,227 65, SP 404, , ,046 6, Corn - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % MG 6,957 9, ,325 1, MT 16,839 27, , PR 15,295 19, ,575 2, Soybean - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % BA 3,229 4, ,313 1, MT 27,002 38, ,616 12, PR 14,741 19, ,019 6, RS 12,734 16, , 5, Wheat - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % PR 3,825 5, ,323 1, RS 2,979 3, ,103 1, Grapes - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % RS Grains - Thousand Tons Thousand hectares 2013/ /24 Var. % 2013/ /24 Var. % MATOPIBA* 18,623 22, , Source: AGE/Mapa and SGE/Embrapa * Located in the Center Northeast of Brazil and formed by the states of Maranhão, Tocantins, Piauí, Bahia.

82 Regional projections show that Rio Grande do Sul should continue leading the production and expansion of rice in Brazil in the coming years. The production of the state that is in 2013/2014, 65.8% of the national rice production must increase production in the coming years in 25.0% and 5.8% in area. The production of sugar cane must present expansion in all states considered. The greatest expansion of production must occur in Minas Gerais, Goiás and Paraná. In these states sugar cane should expand by reducing area of other crops and also in pastures. Sao Paulo, the leader of national production, should have a production increase of approximately 24.6% over the next decade. To meet this growing area in the state should increase by 26.7% at the end of the period of projections. Projections indicate that only in Minas Gerais production the increase will occur by gains in productivity. In the other the expected growth in production will be done mainly by the increase in area. Mato Grosso should lead in the coming years the growth of corn production. The projected increase for the next decade is 62.2%, while the area is expected to increase 49.2%. The available information indicates that increased corn production should occur primarily through the second corn crop that has achieved amazing results Corn must suffer in the coming years 6.9% decrease in the area in Minas Gerais. It is possible that this should occur due to the expansion of sugar cane in the state and also the soybean. Mato Grosso and Bahia should lead the increase in soybean production in the coming years, increasing by 40.9% and 35.9%, respectively, soybean should increase production, without any reduction of area in any of the analyzed states. The projections show that the wheat production increases should be similar in Paraná and Rio Grande do Sul, about 30.0% over the next 10 years and 26.1% for Paraná and Rio Grande do Sul, respectively. No reduction in wheat area is expected to occur, and the largest increase should occur in Rio Grande do Sul The region formed by the states of Maranhão, Tocantins, Piauí and Bahia, known as MATOPIBA has a different growth dynamics. Hence the interest in presenting the results of the main projections. Its growth has been extraordinary. The latest survey of IBGE (2011) on the municipal GDP shows that these municipalities have pulled the growth of the states where they are located. Its growth has been much higher than the growth of the state 81

83 82 and national average. These four states must reach a grain production of 22.6 million tons over the next 10 years in a planted area of 8.4 million hectares in 2023/2024 but which could reach 10.9 million hectares at its upper bound to the end of the next decade. Fig. 35 Grains Projections - MaToPiBa 30,000 25,000 22,607 20,000 15,000 18,623 16,647 Produc0on (thousand tonnes) 10,000 7,259 7,245 8,440 5,000 0 Planted Area (thousand hectares) 2013/ / / / / / / / / / /24 Source: AGE/Mapa and SGE/Embrapa The areas that have been settled in these states have some essential features for modern agriculture. Are flat and extensive, potentially productive soils, water availability, and climate conducive to long days and high intensity of sunshine. The major limitation, however are precarious logistics, especially inland transport, port, communication, and some areas lack of financial services.

84 83 Table 24 Projections of MATOPIBA (*) 2013/2014 to 2023/2024 Production (thousand tons) Planted Area (thousand hectares) Grains 2013/ /24 Var. % 2013/ /24 Var. % 18,623 22, ,259 8, Soybean Selected Municipalities- Thousand tons thousand hectares Balsas - MA Campos Lindos - TO Uruçuí - PI Barreiras - BA Formosa do Rio Preto - BA 1,532 3, São Desidério - BA 829 1, Source: AGE/Mapa and SGE/Embrapa * Located in the Center Northeast of Brazil and formed by the states of Maranhão, Tocantins, Piauí, Bahia. Balsas Urucuí Bom Jesus MA PI Formosa do Rio Preto Campos Lindos TO BA Luiz Eduardo Magalhães Barreiras Pedro Afonso Brazilian Cerrado Savannah

85 84 6. SUMMARY OF MAIN RESULTS The most dynamic products in agribusiness should be cotton lint, chicken, cellulose, sugar, soybean, pork, wheat and sugarcane. These products are those that indicate greater potential for production growth in the coming years.

86 85 Table 25 Brazil - Production Results 2013/14 to 2023/24 Products Unit Estimates to 2013/14 Projection 2023/24 Variation % Rice thousand tons 12,251 13,637 to 21, to 78.0 Bean thousand tons 3,714 3,173 to 4, to 15.6 Corn thousand tons 77, ,121 to 138, to 78.0 Soybean thousand tons 86, ,811 to 139, to 61.6 Soybean Meal thousand tons 28,105 35,168 to 40, to 45.6 Soybean Oil thousand tons 7,118 8,961 to 10, to 53.1 Wheat thousand tons 7,373 9,991 to 19, to Chicken thousand tons 12,691 17,216 to 19, to 57.4 Beef thousand tons 9,753 11,975 to 14, to 50.8 Pork thousand tons 3,553 4,680 to 5, to 67.4 Coffee million sc to to 74.5 Milk Million liters 34,408 44,657 to 49, to 45.1 Manioc Thousand tons 22,655 21,770 to 32, to 43.2 Potatoes Thousand tons 3,711 4,406 to 4, to 30.2 Cotton lint Thousand tons 1,672 2,350 to 2, to 78.3 Sugar Cane Thousand tons 658, ,777 to 1,053, to 60.0 Tobacco Thousand tons 865 1,060 to 1, to 71.5 Sugar Thousand tons 37,878 52,913 to 62, to 63.9 Orange Thousand tons 16,333 17,521 to 25, to 57.6 Paper Thousand tons 10,759 13,320 to 13, to 28.5 Pulp Thousand tons 15,736 20,599 to 23, to 48.7 Cocoa Thousand tons to to 52.9 Grape Thousand tons 1,361 1,650 to 2, to 55.6 Apple Thousand tons 1,271 1,642 to 2, to 63.5 Banana Thousand tons to to 34.7 Source: AGE/Mapa and SGE/Embrapa Note: Sugar Cane refers to the sugar cane intended to alcohol and sugar production

87 86 Grain production should increase from million tonnes in 2013/2014 to million tons in This indicates an increase of 58.9 million tons to the current production in Brazil, and relative values 30.4%. This, however, will require an effort of growth that should consist of infrastructure, investment in research and funding. These estimates are compatible with the expansion of grain production in the last ten years where production grew 69.0 % (Conab, 2014). This result indicates that there is growth potential to achieve the designed values. The production of meat (beef, pork and chicken) will increase by 7.9 million tons. Represents an increase of 30.3% in relation to meat production for 2013/2014. The chicken is the one to present the highest growth, 35.7% over 2014 production. Then pork, which is expected to grow 31.7% and then the beef, 22.8%. Table 26 Brazil Production Projections of Grains and Meat 2013/14 to 2023/24 Grains Unit 2013/14 Projection 2014/15 UP Limit. 2023/24 variation% 2013/14 to 2023/24 Production Thousand tons 193, ,656 to 217, , Planted Area Thousand hectares 56,861 58,553 to 61,469 67, Increase of 58.9 million tons of grains and 10.1 million hectares Meat Unit 2013/14 Projection 2014/15 Lsup. 2023/24 variation% 2013/14 to 2023/24 Chicken Thousand tons 12,691 13,081 to 14,122 17, Beef Thousand tons 9,753 9,762 to 10,799 11, Pork Thousand tons 3,553 3,666 to 4,067 4, Total Thousand tons 25,997 26,509 to 28,987 33, Increase of 7.9 million tons of meat Source: AGE/Mapa and SGE/Embrapa *Grains: refers to crops raised by Conab in their surveys of crops (cotton, peanuts, rice, oats, canola, rye, barley, beans, sunflower, castor, corn, soybean, sorghum, wheat and triticale).

88 The growth of agricultural production in Brazil should continue happening based on productivity. Strong growth of total factor productivity should be maintained, as recent studies have shown, (Fuglie, K., Wang, Sun, Ball, V., 2012 and Gasques, et.al. 2014). These studies show that total factor productivity has grown over 4.0% per year over the past few years. The global average of the last years was 1.84%. The results show a greater increase in agricultural production that increases in area. Between 2014 and 2024 grain production can grow between 30.4% and 52.3%, while the area should expand by between 17,8 and 45.3%. This projection shows a typical example of growth based on productivity. We do not believe that the grain area expands the upper limit of the projection, because the potential productivity is high, especially in products such as soybeans and corn. Estimates made until 2023/2024 are that the total planted area with crops must pass the 70,2 million hectares in 2014 to 82.0 million in An increase of 11.8 million hectares. This area expansion is concentrated in soybean, more than 10.3 million hectares, and cane sugar, more than 2.3 million. The expansion of soybean area and sugarcane should occur by the incorporation of new areas, areas of natural pastures and also for replacing other crops that will give area. Corn must have an expansion area around 1.0 million hectares (15.7 to 16.7 million hectares between 2014 and 2024) and other crops analyzed mostly tend to lose area. The domestic market with exports and productivity gains, should be the main factors for growth in the next decade. In 2023/2024, 42.8% of soybean production should be aimed at the domestic market, and corn, 62.2% of production should be consumed internally. Thus there will be a double pressure on increasing domestic production, due to the growth of the domestic market and exports. Currently, 46.6% of the soybean produced is for domestic consumption, and corn, 69.0%. In meat, there will be strong pressure of the internal market. The expected increase in the production of chicken, 67.2% of output in 2023/2024 will be for the domestic market; of beef produced, 74.8% will go to the internal market, and pork, 83.7% will be for the domestic market. Thus, although Brazil is generally a major exporter of many of these products, domestic consumption is prevalent in the destination of production. 87

89 88 Table 27- Brazil: Exports Projections 2013/14 to 2023/24 Products Unit 2013/14 Projection 2023/24 Variation % Cotton lint Thousand t to 1, to Corn Thousand t 21,000 33,698 to 52, to Soybean Thousand t 45,297 65,244 to 82, to 82.3 Soybean meal Thousand t 13,579 15,701 to 22, to 65.1 Soybean oil Thousand t 1,374 1,626 to 4, to Chicken Thousand t 4,002 5,784 to 7, to 86.9 Beef Thousand t 2,068 2,889 to 4, to Pork Thousand t to 1, to Coffee Million sacs to to 63.7 Sugar Thousand t 27,154 38,801 to 50, to 85.5 Orange juice Thousand t 2,094 2,626 to 3, to 52.2 Milk Million litters to 1, to 912 Paper Thousand t 1,937 2,332 to 3, to 66.7 Pulp Thousand t 9,853 13,735 to 16, to 66.2 Source: AGE/Mapa and SGE/Embrapa

90 89 Table 28 Leadind Exporters of Agricultural Products in 2023/24 Million Tons Share in the World Market (%) Corn United States Brazil Argentina Former Soviet Union Total Exports Soybean Brazil United States Argentina Other South Americans Total Exports Beef Brazil Índia United States Austrália Others New Zeland Total Exports Chicken Brazill United States Sovietic Union Thailand China Total Exports Pork United States Union European Canada Brazil China Total Exports Source: USDA,2014 and AGE/Mapa and SGE/Embrapa

91 90 The five complexes shown in the table represent the main food consumed in the world and considered essential by almost all the world s population. Should continue expressive and with a tendency to increase the participation of Brazil in world trade in soybeans, beef and chicken. As noted, the Brazilian soybean should have in 2023/2024 a share in world exports of 43.0%, beef 28.9%, and chicken, 48.9%. Besides its importance in relation to those goods Brazil will maintain leadership in world trade in coffee, and sugar. Finally, the regional projections are indicating that the largest increases in production and area of cane sugar, must occur in the state of Goiás, although this is still a state of small production. But São Paulo as major national producer, also projected high growth of production and area of the product. Mato Grosso should continue to lead the expansion of maize production in the country with higher expected increases in production to 62.2%. The region called MATOPIBA, to be situated in the Brazilian states of Maranhão, Tocantins, Piauí and Bahia, should present sharp increase in grain production as well as its area must also present significant increase. Projections indicate this region is expected to produce around 22.6 million tons of grain in 2024 (up 21.4%) and an area planted with grains between 8.4 and 10.9 million hectares at the end of the period of the projections.

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94 93 Fuglie Keith O., Wang S. Ling and Ball V. Eldon. Productivity growth in agriculture: an international perspective. USA, 2012 Keith, F. Productivity Growth in the Global Agricultural Economy.Pittsburg, 2011 Mapa- Ministério da Agricultura, Pecuária e Abastecimento. Diretoria de Agroenergia. Informações obtidas por solicitação, Mapa- Ministério da Agricultura, Pecuária e Abastecimento. Departamento do Café DECAF MORETTIN, Pedro A.; TOLOI, Clelia M. C. Análise de Séries Temporais. ABE - Projeto Fisher e Ed. Blucher, OIC Organização Internacional do Café. Disponível em: < coffee/statistics>. Acesso em maio e junho de Santiago, C. M. Embrapa - Centro Nacional de Pesquisa de Arroz e Feijão, 2013 SAS Institute Inc., SAS / ETS User's Guide, Version 8, Cary, NC: SAS Institute Inc., SAS, Institute Inc., Manuais do software versão 9.2, Cary, NC: SAS Institute Inc., SOUZA, G. S.; GAZOLLA, R.; COELHO, C. H. M.; MARRA, R.; OLIVEIRA, A. J. DE. Mercado de Carnes: Aspectos Descritivos e Experiências com o uso de Modelos de Equilíbrio Parcial e de Espaço de Estados. Embrapa - SGE, Revista de Política Agrícola, ano XV n. 1, 2006, Brasília. UNICA - União da Indústria de Cana-de-açúcar - Sugarcane Industry in Brazil, Ethanol, Sugar, Bioelectricity, 2010 (folheto). USDA. USDA Agricultural Projections. Disponível em: < ers.usda.gov/publications/oce081>. Acesso em: fevereiro 2008, 2009, 2010, 2011, 2012 e 2013, 2014.

95 94 Ministério da Agricultura Pecuária e Abastecimento - Assessoria de Gestão Estratégica Annex 1 - Methodological Note ATTACHMENT 1 Methodological Note 1. Introduction The study of the national agribusiness projections consists on the analysis of historical series with the use of statistical techniques for analysis of time series classified as Exponential Smoothing, Box and Jenkins (ARIMA) and State-Space. Below, there is a brief description of the models, methods and some concepts which were used in this study. As general reference it is suggested Morettin and Toloi, 2004). Other specific references are given throughout the text. 1.1 Stationary Process: A process is stationary (weakly) when its mean and its variance are constant through the time and when the value of the co-variance between two periods of time depends only on the difference between the two periods of time, and not on the time itself where the covariance is calculated. We have: Mean: E(Z t ) = µ ; Variance: VAR (Z t ) = E(Z t µ) 2 = σ 2 Covariance: ψκ = E[(Z t µ)(z t+κ µ) ] Where ψκ, is the covariance between the values of Z t and Z t+κ that is, between two values of the time series separated by κ periods. 1.2 Purely Random Process or White Noise: A process (e t ) is purely random when its mean is zero, its variance is σ 2 and the variables e t are not correlated. 1.3 Integrated Process: If a time series (non-stationary) has to be differenced d times to become stationary, it is said that this series is integrated of order d. An integrated time series Z t of order d is denoted as: Z t ~ I(d). 2. Exponential Smoothing Models The Double Exponential Smoothing or Linear Smoothing is adequate to time series Z t which evolve showing linear trend for which the linear and angular coefficients can also vary in time. It is possible to demonstrate that optimal representations of the exponential smoothing models are obtained from the ARIMA models and of State-Space models described below. In the double exponential smoothing approach (the only one we are dealing here) the linear coefficient µ t (level) of the series in period t and its growth rate β t Projections of Agribusiness Brazil 2013/2014 a 2023/

96 95 Ministério da Agricultura Pecuária e Abastecimento - Assessoria de Gestão Estratégica in the same period are given by the smoothing equations (see Bowerman, O Connel and Koehler, 2005) µ = αz + (1 α )( µ + β ) t t t t 1 ( ) β = γ µ µ + (1 γ) β t t t 1 t 1 where α and γ are constants in the interval (0,1) and t=1,2,...,n. The predictor of the series in period N + τ based on period N is given by ZˆN = τ µ + + N τβ. N The exponential smoothing, simple, double (discussed here) or even triple can be obtained from PROC FORECAST (SAS, 2010), but the standard errors of the predictors may also be computed from state-space methods. 3. ARIMA Models The Autoregressive Integrated Moving Average (ARIMA) model fits data generated by a univariate time series, transformed to stationarity through calculations of differences, using a class of models known as autoregressive processes, moving average processes or mixed autoregressive-moving average processes 3.1. Autoregressive Process (AR) Let Z t be a stationary time series. If we model Z t as (Z t - µ) = α1(z t -1 - µ) + e t, where µ is the mean of Z t and e t is a white noise, we say that Z t follows an autoregressive process of first order, or AR(1). In this case, the value of Z t in period t depends on its value in the previous period and on a random term; the values of Z t are expressed as deviations of its mean value. So, this model says that the forecasted value of Z t in period t is simply a proportion (= α 1) of its value in the period (t-1) plus a random shock in period t. Stationarity is achieved imposing α 1 < 1. In general, it is possible to have: (Z t - µ) = α1(z t -1 - µ) + α2(z t -2 - µ) α p (Z t -p - µ) + e t In this case Z t follows an autoregressive process of order p, or AR(p) if the coefficients satisfy appropriate conditions Moving Average Process (MA) α i Projections of Agribusiness Brazil 2013/2014 a 2023/

97 96 Ministério da Agricultura Pecuária e Abastecimento - Assessoria de Gestão Estratégica Let Z t be a stationary time series. If we model Z t as Z = µ + e βe t t t 1 Where µ and β are constants with β < 1, and the error term e t is a white noise, it is said that the time series defines the MA(1) - moving average process of order 1. In general, if the time series satisfies Z = µ + e β e β e L β e t t 1 t 1 2 t 2 q t q where the coefficients βi satisfy additional conditions of invertibility, it is said that Z t follows a moving average process of order q, or MA(q). In summary a moving average process is a linear combination of terms of a white noise process Autoregressive Moving Average Process (ARMA) If a stationary time series (Z t ) has characteristics of AR with errors following a process MA, it will be an ARMA process. The series Z t will follow an ARMA process (1,1), for example, if it can be represented by Z = µ + αz + e βe t t 1 t t 1 In general, for an ARMA process (p,q) there will be p autoregressive terms and q moving average terms Autoregressive Integrated Moving Average Process (ARIMA) If a time series is not stationary, but when differenced d times it becomes stationary, and it is an AR with errors MA, we say that the time series is an ARIMA (p, d, q), that is, an integrated autoregressive-moving averages time series, where p denotes the number of autoregressive terms, d is the number of times that we must difference the series to make it stationary, and q, is the number of moving average terms. It is important to emphasize ARMA models can be fit only to stationary and invertible time series. These properties are achieved through differencing. This approach was proposed by Box and Jenkins (1976). The fit and computation of forecasts of a given time series with the use of Box and Jenkins techniques were performed here using PROC ARIMA (SAS, 2010) Deterministic Trends with ARMA Errors In one instance (consumption of cellulose) a satisfactory model was not possible with the use of integrated models. In this case it was used the regression model Zt=F(t)+Ut Projections of Agribusiness Brazil 2013/2014 a 2023/

98 97 Ministério da Agricultura Pecuária e Abastecimento - Assessoria de Gestão Estratégica where Ut is an ARMA error and F(t) a linear function in time. The PROC ARIMA (SAS, 2010) produces statistics for these models using generalized least squares. 4. State-Space Models The state-space model is a statistical model for a multivariate time series. It represents the multivariate time series through auxiliary variables, some of which are not observable directly. These auxiliary variables are denominated state-space variables. The state-space vector summarizes all the information of values from the present and from the past on the relevant time series for the prediction of future values for the series. The observed time series are expressed as linear combination of the state variables. The statespace model is called a Markovian representation or canonical representation of a multivariate time series. Let Z t be a q dimensional time series. Its representation in state-space, relate the observations vector Z t to the state vector X t, of dimension k, through the linear system Zt = AX t t + dt + Sε (observation equation), t t X = GX + c + Rη (state or system equation) t t t 1 t t t where t=1,..., N ; Α t is the matrix of the system of order (q x k); ε t is the noise vector of the observation of order (q x 1), not correlated in time, with mean vector zero and matrix of variance W of order (q x q), ; G t t is the transition matrix of order (k x k) ; η t is a noise vector not correlated in time, of order (k x 1), with mean vector zero and matrix of variance order (k x k); d t has order (q x 1) ; c t has order (k x 1); R t has order (k x k). Q t of In the state-space models it is supposed additionally that the initial state X 0 has mean µ 0 and matrix of variance Σ 0; the noise vectors ε t and η t are not correlated with each other and not correlated with the initial state, that is, E(ε t η s ) = 0, every t, s= 1,...,N; and E(ε t X 0 ) = 0 and E(η t X 0 ) = 0, t= 1,...,N; It is said that the state-space model is Gaussian when the noise vectors are normally distributed. The matrixes Α t and G t are non-stochastic; in this way if there is any variation in time it will be pre-determined. Projections of Agribusiness Brazil 2013/2014 a 2023/

99 98 Ministério da Agricultura Pecuária e Abastecimento - Assessoria de Gestão Estratégica In this work it was used a particular form of the general representation described above, which is the stationary representation described in SOUZA, et al, 2006 and Brocklebank and Dickey, It is important to notice here that every ARMA process has a state-space representation. The parameters of the state-space representation are estimated by maximum likelihood supposing that the residual shocks vector are normally (multivariate) distributed. The fit and forecasts of time series performed via state-space models were performed using PROC STATESPACE (SAS, 2010). 5. AIC and SBC Information Criterion The information criteria are very useful to assist in choosing the best model among those which are potentially adequate. These criteria consider not only the quality of the fit but also penalize the inclusion of extra parameters. Therefore, a model with more parameters can have a better fit, however not necessarily it will be preferable in terms of the information criterion. It is considered the best model by the information criteria the one which presents the lowest values of AIC or SBC. The information criterions known as Akaike Information Criterion (AIC) and the Schwartz Bayesian Criterion (SBC) can be described as follows: AIC = T ln (estimator of maximum verisimilitude) + 2n, SBC = T ln (estimator of maximum verisimilitude) + n ln(t) Where, T is the number of observations used in the computations and n the number of parameters estimated. It is interesting to highlight that these information criteria analyzed individually do not have any meaning considering only one model. Comparison of alternative models (or competing) is to be done in the same sampling period, in other words, with the same quantity of information. In this work the use of the information criteria was used in the choice of the order of some ARMA models and restricted to the Akaike criterion in the context of the use of the state-space modeling. Projections of Agribusiness Brazil 2013/2014 a 2023/

100 ANNEX 2 Results Brazil National Projection of Grains* - Brazil 2013/2014 to 2023/2024 Product Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Grains* production 193, , , , , , , , , , , thousand Up limit 181, , , , , , , , , ,096 9 tons lower limit 217, , , , , , , , , , Grains* Area 56,861 58,553 59,741 60,729 61,654 62,555 63,448 64,338 65,227 66,115 67, thousand Up limit 55,637 54,309 53,389 52,688 52,193 51,845 51,613 51,469 51,397 51, hectares lower limit 61,469 65,172 68,068 70,621 72,917 75,051 77,063 78,985 80,834 82, Source: AGE/Mapa and SGE/Embrapa * raw cotton,peanuts, rice, oats, canola, rye, barley, beans, sumflower, castor, corn, soybean, sorghum, wheat and triticale

101 Projected Prodution - Brazil 2013/2014 to 2023/2024 Production Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Cotton 1,672 2,143 1,900 1,719 2,099 2,271 2,072 2,135 2,411 2,426 2, tons 1,770 1,477 1,290 1,641 1,730 1,522 1,582 1,819 1,800 1,719 3 lower limit 2,517 2,322 2,148 2,558 2,813 2,622 2,689 3,004 3,051 2, Rice 12,251 12,703 12,807 12,910 13,014 13,118 13,222 13,326 13,429 13,533 13, tons 10,120 9,155 8,438 7,849 7,344 6,896 6,493 6,125 5,786 5, lower limit 15,285 16,459 17,383 18,179 18,892 19,547 20,158 20,734 21,280 21, Beans 3,714 3,179 2,928 3,268 3,227 3,036 3,164 3,205 3,099 3,129 3, tons 2,524 2,212 2,547 2,388 2,124 2,232 2,217 2,049 2,049 2, lower limit 3,835 3,644 3,990 4,066 3,949 4,096 4,193 4,149 4,209 4, Corn 77,887 80,717 83,462 86,773 88,118 91,516 93,193 96,528 98, , , tons 67,538 66,113 65,962 65,296 65,544 65,438 66,209 66,297 67,377 67, lower limit 93, , , , , , , , , , Soybeans 86,052 89,831 93,254 96,377 99, , , , , , , tons 81,446 82,683 84,205 85,582 87,188 88,903 90,696 92,577 94,523 96, lower limit 98, , , , , , , , , , Soybeans meal thousand tons 28,105 28,676 30,079 30,534 31,041 31,910 32,562 33,135 33,856 34,539 35, Up limit 26,275 26,986 27,134 27,165 27,601 27,967 28,227 28,630 29,047 29,417 5 lower limit 31,078 33,173 33,935 34,918 36,218 37,158 38,043 39,082 40,031 40, Soybeans oil 7,118 7,353 7,510 7,706 7,886 8,066 8,247 8,425 8,604 8,783 8, tons 6,581 6,539 6,584 6,608 6,660 6,720 6,787 6,862 6,941 7,026-1 lower limit 8,125 8,481 8,827 9,164 9,472 9,773 10,064 10,347 10,624 10, Wheat 7,373 7,635 7,897 8,158 8,420 8,682 8,944 9,205 9,467 9,729 9, tons 4,751 3,818 3,163 2,652 2,233 1,879 1,574 1,309 1, lower limit 10,519 11,975 13,154 14,188 15,131 16,008 16,836 17,625 18,381 19, Chicken 12,691 13,081 13,519 13,972 14,432 14,894 15,358 15,822 16,286 16,751 17, tons 12,041 12,417 12,372 12,774 12,857 13,270 13,419 13,839 14,029 14, lower limit 14,122 14,620 15,571 16,090 16,931 17,445 18,225 18,734 19,474 19, Beef 9,753 9,762 10,309 10,632 10,451 10,589 11,027 11,105 11,159 11,615 11, tons 8,725 8,696 8,691 8,242 8,086 8,454 8,510 8,520 8,916 9,243-5 lower limit 10,799 11,921 12,573 12,661 13,091 13,600 13,699 13,799 14,314 14, Pork 3,553 3,666 3,778 3,891 4,004 4,116 4,229 4,342 4,454 4,567 4, tons 3,264 3,211 3,196 3,201 3,219 3,246 3,280 3,319 3,363 3,411-4 lower limit 4,067 4,346 4,586 4,806 5,013 5,212 5,403 5,589 5,771 5,948 67

102 Coffee Up limit millions bags lower limit Sugar 37,878 40,330 41,265 42,937 44,264 45,749 47,163 48,608 50,040 51,478 52, tons 36,585 36,755 37,570 38,223 39,083 39,932 40,852 41,791 42,765 43, lower limit 44,074 45,774 48,304 50,305 52,415 54,394 56,365 58,288 60,190 62, Manioc 22,655 22,902 22,292 22,473 22,307 22,213 22,140 22,039 21,952 21,861 21,770-4 tons 18,695 16,920 16,289 15,253 14,455 13,720 13,005 12,346 11,714 11, lower limit 27,108 27,665 28,658 29,362 29,971 30,559 31,073 31,558 32,008 32, Potato 3,711 3,948 3,950 3,928 4,028 4,127 4,165 4,209 4,284 4,352 4, tons 3,642 3,622 3,599 3,686 3,754 3,781 3,820 3,882 3,936 3,980 7 lower limit 4,254 4,279 4,257 4,370 4,501 4,549 4,599 4,686 4,768 4, Orange 16,333 16,452 16,571 16,689 16,808 16,927 17,046 17,165 17,283 17,402 17,521 7 tons 13,853 12,895 12,187 11,610 11,115 10,679 10,288 9,932 9,604 9, lower limit 19,051 20,247 21,191 22,007 22,739 23,413 24,042 24,635 25,200 25, Milk 34,408 36,322 36,473 38,377 38,523 40,425 40,569 42,470 42,613 44,514 44, Up limit million liters 34,746 34,060 35,739 35,220 36,923 36,516 38,244 37,912 39,660 39, lower limit 37,897 38,885 41,016 41,826 43,927 44,623 46,696 47,315 49,368 49, Tobacco ,007 1,021 1,046 1, tons lower limit 1,079 1,093 1,197 1,211 1,296 1,310 1,385 1,399 1,469 1, Sugar Cane 658, , , , , , , , , , , tons 671, , , , , , , , , ,569 4 lower limit 671, , , , , , , ,930 1,020,836 1,053, cocoa tons lower limit Grape 1,361 1,413 1,424 1,459 1,483 1,513 1,539 1,567 1,595 1,622 1, tons 1,221 1,201 1,186 1,177 1,173 1,171 1,172 1,174 1,178 1, lower limit 1,605 1,647 1,733 1,788 1,852 1,907 1,963 2,015 2,067 2, Apple 1,271 1,306 1,344 1,381 1,418 1,456 1,493 1,530 1,568 1,605 1, tons 1,124 1,128 1,124 1,130 1,137 1,148 1,160 1,174 1,190 1,206-5 lower limit 1,488 1,560 1,638 1,707 1,774 1,838 1,900 1,961 2,020 2, Banana bunche lower limit Paper 10,759 10,992 11,267 11,516 11,776 12,035 12,289 12,553 12,805 13,070 13, tons 10,746 10,969 11,184 11,415 11,641 11,874 12,106 12,340 12,576 12, lower limit 11,237 11,565 11,848 12,136 12,429 12,704 13,000 13,269 13,564 13, Pulp 15,736 16,173 16,675 17,183 17,651 18,156 18,640 19,128 19,622 20,108 20, tons 15,240 15,397 15,686 15,892 16,196 16,492 16,798 17,131 17,461 17, lower limit 17,106 17,952 18,681 19,410 20,116 20,789 21,459 22,113 22,755 23, Source: AGE/Mapa and SGE/Embrapa Note: Sugar Cane refers to the sugar cane intended to alcohol and sugar production * seed cotton, full peanuts, rice, oats, canola, rye, barley, full beans, sunflower, castor, full corn, soybeans, sorghum, wheat and triticale

103 Projections of Planted Area - Brazil 2013/2014 to 2023/2024 Planted Area Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Cotton 1,095 1,420 1,222 1,030 1,258 1,356 1,171 1,163 1,324 1,301 1, hectares 1, lower limit 1,747 1,594 1,442 1,706 1,867 1,704 1,719 1,915 1,924 1, Rice 2,417 2,318 2,220 2,121 2,022 1,924 1,825 1,726 1,627 1,529 1, hectares 1,677 1,312 1, lower limit 2,960 3,127 3,232 3,305 3,358 3,396 3,423 3,442 3,453 3, Beans 3,359 3,245 3,131 3,016 2,902 2,788 2,674 2,559 2,445 2,331 2, hectares 2,473 2,039 1,680 1,359 1, lower limit 4,016 4,222 4,353 4,445 4,513 4,563 4,601 4,627 4,645 4, Corn 15,726 15,659 15,874 15,993 16,080 16,188 16,303 16,412 16,520 16,630 16,739 6 hectares 13,799 13,326 12,931 12,606 12,320 12,079 11,863 11,668 11,491 11, lower limit 17,518 18,422 19,055 19,553 20,056 20,527 20,960 21,372 21,768 22, Soybeans 30,105 31,598 32,764 33,785 34,751 35,697 36,633 37,565 38,496 39,427 40, hectares 29,309 28,792 28,395 28,166 28,070 28,078 28,171 28,330 28,543 28,799-4 lower limit 33,887 36,736 39,176 41,336 43,324 45,187 46,959 48,662 50,311 51, Wheat 2,617 2,676 2,734 2,793 2,851 2,910 2,968 3,027 3,085 3,144 3, hectares 1,975 1,743 1,579 1,450 1,343 1,252 1,173 1,103 1, lower limit 3,376 3,725 4,006 4,253 4,477 4,685 4,881 5,068 5,246 5, Coffee 2,016 1,955 1,966 1,958 1,944 1,938 1,925 1,918 1,906 1,898 1,887-6 hectares 1,955 1,507 1,423 1,333 1,263 1,190 1,129 1,065 1, lower limit 1,955 2,425 2,494 2,555 2,613 2,661 2,707 2,747 2,787 2, Manioc ( * ) 1,525 1,566 1,509 1,508 1,490 1,472 1,457 1,440 1,424 1,408 1,391-9 hectares 1,335 1,200 1,153 1,083 1, lower limit 1,797 1,818 1,863 1,897 1,920 1,944 1,963 1,980 1,996 2,010 32

104 Potato ( * ) hectares lower limit Orange ( * ) hectares lower limit Tobacco ( * ) hectares lower limit Sugar Cane ( * ) 8,811 9,130 9,258 9,537 9,748 9,990 10,209 10,440 10,666 10,895 11, hectares 9,130 8,566 8,441 8,222 8,204 8,201 8,241 8,282 8,341 8,408-5 lower limit 9,130 9,949 10,634 11,274 11,776 12,218 12,640 13,050 13,450 13, cocoa ( * ) hectares lower limit Grape ( * ) hectares lower limit Apple ( * ) hectares lower limit Banana ( * ) hectares lower limit Source: AGE/Mapa and SGE/Embrapa Note: Area of Sugar Cane, refers to area destinated to production of alcohol and sugar. * harvested area

105 Projections of Consumption - Brazil 2013/2014 to 2023/2024 Consumption Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Cotton tons lower limit 1,000 1,044 1,078 1,108 1,134 1,159 1,182 1,203 1,223 1, Rice 12,000 12,023 12,047 12,070 12,094 12,117 12,141 12,164 12,188 12,211 12,235 2 tons 11,490 11,293 11,146 11,027 10,925 10,834 10,753 10,679 10,611 10, lower limit 12,557 12,801 12,994 13,161 13,310 13,447 13,575 13,696 13,811 13, Beans 3,450 3,463 3,475 3,488 3,500 3,513 3,525 3,538 3,550 3,563 3,575 4 tons 3,028 2,860 2,735 2,631 2,541 2,461 2,388 2,321 2,259 2, lower limit 3,897 4,090 4,240 4,369 4,484 4,589 4,687 4,779 4,866 4, Corn 53,818 54,876 55,868 56,868 57,899 58,936 59,967 61,000 62,034 63,068 64, tons 53,100 52,844 52,810 52,938 53,196 53,538 53,945 54,404 54,902 55,434 3 lower limit 56,652 58,892 60,927 62,859 64,675 66,396 68,055 69,665 71,234 72, Soybeans 40,080 41,233 42,358 43,391 44,401 45,414 46,417 47,420 48,423 49,425 50, tons 36,767 36,729 37,044 37,191 37,499 37,865 38,256 38,694 39,161 39,654-1 lower limit 45,698 47,988 49,739 51,612 53,329 54,969 56,583 58,152 59,688 61, Soybeans meal 14,100 14,529 15,046 15,548 16,019 16,538 17,049 17,543 18,050 18,559 19, tons 13,824 14,006 14,303 14,575 14,895 15,247 15,595 15,958 16,336 16, lower limit 15,234 16,085 16,793 17,463 18,181 18,851 19,492 20,143 20,783 21, Soybeans oil 5,500 5,566 5,642 5,755 5,880 6,016 6,161 6,309 6,461 6,616 6, tons 5,222 5,058 4,946 4,847 4,775 4,724 4,690 4,673 4,668 4, lower limit 5,911 6,225 6,564 6,913 7,258 7,597 7,928 8,250 8,563 8, Wheat 12,192 12,405 12,617 12,830 13,042 13,255 13,468 13,680 13,893 14,105 14, tons 11,366 11,149 11,031 10,966 10,933 10,924 10,933 10,956 10,990 11,034-9 lower limit 13,443 14,086 14,628 15,119 15,577 16,011 16,428 16,830 17,221 17,602 44

106 Chicken 8,689 8,976 9,263 9,551 9,838 10,125 10,412 10,699 10,987 11,274 11, tons 8,338 8,360 8,445 8,561 8,697 8,848 9,010 9,181 9,358 9, lower limit 9,615 10,166 10,656 11,115 11,553 11,976 12,389 12,792 13,189 13, Beef 7,744 7,615 7,866 8,089 7,992 8,082 8,421 8,501 8,502 8,759 8, tons 6,898 6,852 6,980 6,795 6,765 7,090 7,161 7,098 7,289 7,456-4 lower limit 8,332 8,880 9,198 9,189 9,399 9,752 9,841 9,906 10,230 10, Pork 3,032 3,120 3,209 3,297 3,385 3,474 3,562 3,650 3,738 3,827 3, tons 1, lower limit 4,750 5,513 6,119 6,644 7,117 7,553 7,961 8,347 8,715 9, Sugar 12,233 12,261 12,694 12,963 13,299 13,607 13,927 14,242 14,559 14,875 15, tons 10,882 11,087 11,046 11,155 11,245 11,369 11,501 11,647 11,802 11,965-2 lower limit 13,640 14,300 14,881 15,442 15,970 16,485 16,983 17,471 17,949 18, Coffee Up limit millions bags lower limit Milk 36,298 37,310 38,302 39,290 40,278 41,265 42,253 43,240 44,228 45,215 46, Up limit million liters 34,551 34,794 35,161 35,608 36,112 36,657 37,234 37,838 38,464 39,108 8 lower limit 40,069 41,810 43,420 44,948 46,419 47,849 49,246 50,617 51,967 53, Paper 10,125 10,333 10,598 10,863 11,102 11,377 11,601 11,881 12,102 12,385 12, tons 9,846 9,953 10,131 10,280 10,487 10,639 10,858 11,015 11,242 11, lower limit 10,820 11,243 11,595 11,923 12,267 12,562 12,905 13,188 13,529 13, Pulp 6,327 6,392 6,531 6,654 6,759 6,889 7,001 7,120 7,241 7,356 7, tons 5,923 6,029 6,085 6,161 6,248 6,324 6,412 6,498 6,584 6,674 5 lower limit 6,862 7,034 7,224 7,356 7,531 7,678 7,829 7,984 8,129 8, Source: AGE/Mapa and SGE/Embrapa

107 Projections of Export - Brazil 2013/2014 to 2023/2024 Export Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Cotton tons lower limit 923 1,085 1,218 1,334 1,440 1,540 1,634 1,723 1,809 1, Corn 21,000 22,806 25,001 25,910 26,790 28,018 29,192 30,298 31,425 32,565 33, tons 15,348 14,885 14,676 14,317 14,287 14,368 14,476 14,648 14,883 15, lower limit 30,264 35,117 37,144 39,264 41,748 44,016 46,121 48,201 50,247 52, Soybeans 45,297 47,292 49,286 51,281 53,276 55,270 57,265 59,260 61,254 63,249 65, tons 41,815 41,541 41,795 42,322 43,024 43,849 44,769 45,763 46,818 47, lower limit 52,768 57,032 60,767 64,229 67,517 70,680 73,750 76,745 79,679 82, Soybeans meal 13,579 14,166 14,389 14,715 14,783 14,939 15,128 15,257 15,394 15,557 15, tons 12,406 11,675 11,277 10,746 10,333 10,027 9,713 9,430 9,201 8, lower limit 15,926 17,103 18,154 18,821 19,545 20,230 20,801 21,358 21,912 22, Soybeans oil 1,374 1,530 1,562 1,598 1,622 1,631 1,637 1,637 1,635 1,631 1, tons lower limit 2,119 2,422 2,686 2,945 3,164 3,369 3,556 3,727 3,887 4, Chicken 4,002 4,181 4,323 4,527 4,680 4,890 5,046 5,258 5,415 5,627 5, tons 3,689 3,758 3,670 3,747 3,727 3,816 3,837 3,936 3,984 4, lower limit 4,674 4,887 5,384 5,613 6,054 6,276 6,679 6,893 7,271 7, Beef 2,068 2,143 2,223 2,305 2,388 2,471 2,555 2,638 2,722 2,805 2, tons 1,770 1,584 1,445 1,341 1,261 1,199 1,151 1,113 1,084 1, lower limit 2,515 2,861 3,165 3,435 3,682 3,910 4,125 4,330 4,526 4,

108 Pork tons lower limit ,029 1,082 1,133 1,182 1, Coffee Up limit millions bags lower limit Sugar 27,154 27,824 29,207 30,352 31,577 32,775 33,982 35,186 36,391 37,596 38, tons 23,096 23,519 23,577 23,947 24,352 24,843 25,380 25,962 26,578 27, lower limit 32,552 34,896 37,128 39,208 41,198 43,122 44,993 46,821 48,614 50, Suco de Orange 2,094 2,179 2,215 2,272 2,320 2,372 2,423 2,474 2,525 2,575 2, tons 1,910 1,893 1,914 1,926 1,946 1,966 1,989 2,013 2,038 2, lower limit 2,448 2,537 2,631 2,715 2,799 2,880 2,959 3,036 3,112 3, Milk Up limit millions liters lower limit ,052 1,128 1,200 1,267 1,330 1, Paper 1,937 1,995 2,055 2,079 2,122 2,142 2,190 2,213 2,261 2,284 2, tons 1,734 1,640 1,581 1,532 1,502 1,483 1,464 1,454 1,440 1, lower limit 2,257 2,470 2,576 2,712 2,782 2,897 2,961 3,068 3,128 3, Pulp 9,853 10,240 10,621 11,022 11,403 11,794 12,183 12,569 12,959 13,347 13, tons 9,247 9,326 9,517 9,688 9,894 10,118 10,345 10,590 10,839 11, lower limit 11,233 11,916 12,527 13,117 13,694 14,248 14,794 15,329 15,855 16, Source: AGE/Mapa and SGE/Embrapa

109 Projections of Import - Brazil 2013/2014 to 2023/2024 Import Unit 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Rice 1, tons lower limit 1,769 2,069 2,291 2,473 2,629 2,768 2,892 3,006 3,111 3, Beans tons lower limit Wheat 5,500 5,478 5,456 5,433 5,411 5,389 5,367 5,345 5,322 5,300 5, tons 3,754 3,018 2,448 1,964 1,535 1, lower limit 7,201 7,893 8,418 8,858 9,243 9,588 9,904 10,197 10,470 10, Milk 1,057 1,047 1,037 1,028 1,018 1, Up limit millions liters lower limit 2,820 3,209 3,535 3,821 4,079 4,316 4,535 4,740 4,934 5, Source: AGE/Mapa and SGE/Embrapa

110 Brazil MATOPIBA Production Projections and Planted Área /2014 to 2023/2024 Production 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Grains 20,368 16,966 16,647 20,626 22,029 19,847 19,813 22,773 23,939 22, Up limit 18,623 17,693 13,183 12,839 16,792 17,555 14,813 14,724 17,629 18,402 16, lower limit 23,043 20,748 20,456 24,460 26,503 24,880 24,902 27,917 29,476 28, Planted Area 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Grains 6,998 7,570 7,245 7,795 7,463 8,011 7,678 8,226 7,892 8, Up limit 7,259 6,036 6,554 5,768 6,274 5,594 6,106 5,485 6,002 5,417 5, lower limit 7,959 8,585 8,722 9,316 9,331 9,916 9,871 10,449 10,367 10, Source: AGE/Mapa and SGE/Embrapa * It is a region located at the Centre Northeast of Brazil and formed by municipalities of Maranhão, Tocantins, Piauí and Bahia.

111 Brazil MATOPIBA Production Projections /2014 to 2023/2024 Production 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Soybeans - Selected Municipalities - thousand tons Balsas - MA Up limit lower limit Campos Lindos - TO Up limit lower limit Uruçuí - PI Up limit Fonte: lower AGE/Mapa limit e SGE/Embrapa * Barreiras Região localizada - BA no Brasil central formada pelos 355 estados de 358 MA, TO, PI, 359 BA Up limit lower limit Formosa do Rio Preto - BA 1,784 1,979 2,231 2,426 2,678 2,873 3,124 3,320 3,571 3, Up limit 1,532 1,334 1,398 1,430 1,454 1,459 1,450 1,431 1,394 1,352 1, lower limit 2,234 2,560 3,031 3,398 3,896 4,295 4,818 5,246 5,790 6, São Desidério - BA ,015 1,052 1,089 1,126 1,163 1, Up limit lower limit 1,250 1,346 1,435 1,520 1,600 1,678 1,753 1,826 1,897 1, Source: AGE/Mapa and SGE/Embrapa * It is a region located at the Centre Northeast of Brazil and formed by municipalities of Maranhão, Tocantins, Piauí and Bahia.

112 Brazil MATOPIBA Projections f Planted Area /2014 to 2023/2024 Planted Area 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Soybeans - Selected Municipalities - thousand Hectares Balsas - MA Up limit lower limit Campos Lindos - TO Up limit lower limit Uruçuí - PI Up limit lower limit Barreiras - BA Up limit lower limit Formosa do Rio Preto - BA Up limit lower limit São Desidério - BA Up limit lower limit ,006 1,077 1,143 1,205 1,262 1,317 1,369 1, Source: AGE/Mapa and SGE/Embrapa * It is a region located at the Centre Northeast of Brazil and formed by municipalities of Maranhão, Tocantins, Piauí and Bahia.

113 Brazil Regions Production Projections Selected Regions /2014 to 2023/2024 Production 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Rice - thousand tons RS 8,691 8,952 9,035 9,256 9,462 9,720 9,914 10,125 10,320 10, Up limit 8,434 7,610 7,614 7,602 7,789 7,917 8,109 8,221 8,374 8,515 8,686 3 lower limit 9,772 10,289 10,467 10,722 11,006 11,330 11,608 11,875 12,125 12, Sugar Cane - thousand tons GO 71,060 73,367 75,997 78,813 81,738 84,726 87,750 90,795 93,853 96, Up limit 69,307 64,324 62,244 60,883 60,082 59,729 59,733 60,022 60,539 61,244 62, lower limit 77,795 84,490 91,110 97, , , , , , , MG 80,679 84,201 87,504 90,686 93,799 96,873 99, , , , Up limit 76,741 74,730 73,803 73,032 72,539 72,344 72,424 72,743 73,266 73,961 74,803-3 lower limit 86,628 94, , , , , , , , , MT 18,577 18,317 20,164 21,650 22,272 21,865 22,110 23,139 24,459 25, Up limit 19,153 16,247 15,234 16,833 18,317 18,872 18,166 17,968 18,833 20,104 20,666 8 lower limit 20,908 21,400 23,496 24,982 25,672 25,564 26,252 27,444 28,815 29, PR 50,790 52,433 54,094 55,758 57,422 59,086 60,750 62,414 64,078 65, Up limit 49,227 43,866 40,872 39,130 38,012 37,273 36,791 36,498 36,352 36,324 36, lower limit 57,714 63,993 69,059 73,504 77,571 81,381 85,002 88,476 91,833 95, SP 429, , , , , , , , , , Up limit 404, , , , , , , , , , ,172-3 lower limit 469, , , , , , , , , , Corn - thousand tons MG 7,590 7,967 7,858 8,016 8,339 8,481 8,594 8,804 9,001 9, Up limit 6,957 6,581 6,728 6,583 6,621 6,779 6,835 6,870 6,979 7,086 7,163 3 lower limit 8,600 9,206 9,132 9,411 9,898 10,127 10,317 10,629 10,917 11,145 60

114 MT 21,187 21,077 22,646 21,815 25,560 23,756 26,553 25,999 28,655 27, Up limit 16,839 16,355 15,549 14,726 13,271 15,056 12,781 14,018 13,022 14,317 12, lower limit 26,018 26,605 30,566 30,360 36,065 34,731 39,089 38,976 42,992 42, PR 16,652 15,652 18,617 17,663 19,265 17,607 19,692 18,743 20,976 19, Up limit 15,295 12,714 11,213 13,717 12,077 13,182 11,359 12,817 11,522 13,422 11, lower limit 20,589 20,090 23,517 23,249 25,348 23,854 26,567 25,965 28,531 27, Soybeans - thousand tons BA 3,600 3,356 3,443 3,814 3,865 3,846 4,061 4,239 4,276 4, Up limit 3,229 4,187 4,053 4,144 4,583 4,746 4,755 4,998 5,242 5,326 5, lower limit 3,012 2,658 2,742 3,045 2,984 2,936 3,125 3,235 3,225 3,311 3 MT 28,315 29,181 30,317 31,430 32,526 33,628 34,730 35,831 36,933 38, Up limit 27,002 25,812 25,598 26,032 26,524 27,065 27,666 28,305 28,975 29,671 30, lower limit 30,818 32,764 34,601 36,336 37,987 39,590 41,155 42,687 44,195 45, PR 16,155 14,855 17,442 16,534 17,982 17,538 19,166 18,653 20,045 19, Up limit 14,741 13,767 12,113 14,540 13,588 14,926 14,454 15,997 15,441 16,790 16, lower limit 18,543 17,597 20,345 19,480 21,039 20,622 22,334 21,865 23,299 23, RS 13,086 13,439 13,791 14,143 14,495 14,847 15,199 15,551 15,904 16, Up limit 12,734 7,447 5,463 4,023 2,864 1,885 1, lower limit 18,726 21,414 23,559 25,422 27,105 28,661 30,120 31,502 32,822 34, Wheat - thousand tons PR 3,899 3,967 4,155 4,270 4,430 4,562 4,712 4,851 4,996 5, Up limit 3,825 1,863 1,494 1,374 1,178 1, lower limit 5,935 6,440 6,936 7,363 7,786 8,173 8,554 8,915 9,269 9, RS 2,082 3,053 2,217 3,259 2,409 3,415 2,564 3,586 2,740 3, Up limit 2,979 1,010 1, , , , , lower limit 3,155 4,270 3,656 4,721 4,115 5,170 4,513 5,565 4,894 5, Grape - thousand tons RS Up limit lower limit ,036 1,065 1,105 1,137 1,170 1,201 1,232 1, Source: AGE/Mapa and SGE/Embrapa

115 Projections of Planted Area Selected Regions /2014 to 2023/2024 Planted Area 2013/ / / / / / / / / / /24 variation % 2013/14 to 2023/24 Rice - thousand hectares RS 1,131 1,132 1,124 1,132 1,143 1,154 1,159 1,164 1,170 1,178 6 Up limit 1,114 1, lower limit 1,218 1,283 1,292 1,312 1,327 1,350 1,366 1,383 1,397 1, Sugar Cane - thousand hectares GO ,009 1,045 1,082 1,120 1,157 1, Up limit lower limit 957 1,040 1,124 1,205 1,283 1,358 1,431 1,501 1,569 1, MG 998 1,039 1,077 1,113 1,148 1,184 1,218 1,253 1,288 1, Up limit lower limit 1,062 1,155 1,240 1,320 1,394 1,465 1,532 1,596 1,658 1, MT Up limit lower limit PR Up limit lower limit ,013 1,047 1, SP 5,343 5,137 5,546 5,486 5,910 5,812 6,213 6,105 6,501 6, Up limit 5,046 5,010 4,702 4,756 4,608 4,894 4,773 5,084 4,955 5,260 5,129 2 lower limit 5,676 5,573 6,336 6,364 6,925 6,851 7,343 7,256 7,743 7, Corn - thousand hectares MG 1,316 1,307 1,298 1,289 1,280 1,271 1,261 1,252 1,243 1,234-7 Up limit 1,325 1,187 1,125 1,075 1, lower limit 1,445 1,489 1,521 1,546 1,568 1,586 1,602 1,617 1,630 1,641 24

116 MT 3,650 3,694 4,034 3,905 4,367 4,267 4,620 4,566 4,964 4, Up limit 3,250 3,022 2,975 2,957 2,756 2,948 2,787 2,918 2,811 3,016 2, lower limit 4,278 4,412 5,111 5,053 5,786 5,747 6,321 6,320 6,912 6, PR 2,454 2,389 2,712 2,789 2,615 2,511 2,537 2,617 2,661 2,631 2 Up limit 2,575 2,144 2,069 2,377 2,362 2,177 2,030 2,046 2,120 2,156 2, lower limit 2,763 2,709 3,048 3,216 3,053 2,993 3,027 3,114 3,166 3, Soybeans - thousand hectares BA 1,423 1,426 1,523 1,520 1,615 1,610 1,704 1,700 1,793 1, Up limit 1,313 1,298 1,288 1,318 1,303 1,346 1,332 1,383 1,370 1,427 1,415 8 lower limit 1,548 1,564 1,728 1,737 1,883 1,889 2,025 2,029 2,159 2, MT 9,345 9,552 9,878 10,220 10,549 10,879 11,211 11,542 11,873 12, Up limit 8,616 8,510 8,193 8,220 8,307 8,407 8,531 8,673 8,828 8,994 9,168 6 lower limit 10,179 10,911 11,536 12,133 12,691 13,228 13,748 14,255 14,751 15, PR 5,124 5,285 5,465 5,619 5,753 5,915 6,071 6,221 6,370 6, Up limit 5,019 4,783 4,752 4,799 4,824 4,838 4,900 4,966 5,029 5,098 5,180 3 lower limit 5,464 5,817 6,131 6,413 6,668 6,930 7,177 7,413 7,643 7, RS 5,024 4,989 4,986 5,067 5,190 5,303 5,387 5,455 5,527 5, Up limit 4,940 4,717 4,380 4,179 4,155 4,215 4,270 4,286 4,281 4,284 4, lower limit 5,330 5,598 5,794 5,978 6,165 6,336 6,488 6,629 6,770 6, Wheat - thousand hectares PR 1,312 1,345 1,356 1,381 1,397 1,419 1,437 1,458 1,477 1, Up limit 1, lower limit 1,958 2,119 2,246 2,370 2,478 2,583 2,680 2,774 2,863 2, RS 1,053 1,119 1,088 1,186 1,152 1,235 1,199 1,288 1,255 1, Up limit 1, lower limit 1,352 1,525 1,547 1,665 1,681 1,800 1,810 1,923 1,928 2, Grape - thousand hectares RS Up limit lower limit Source: AGE/Mapa and SGE/Embrapa

117 Note

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