Here is a description of the Trase database on soybeans in Brazil. It is available at: https://www.trase.earth/

This collaborative database seeks to link the main information on soybean value chains in Brazil:

Here are descriptions of the variables you provided:

1. YEAR: The year in which the data is recorded.
2. COUNTRY OF PRODUCTION: The country where soy production took place.
3. BIOME: The specific biome in which soy production occurred.
4. STATE: The particular state within the country where soy production occurred.
5. MUNICIPALITY OF PRODUCTION: The municipality or city where soy production took place.
6. LOGISTICS HUB: The transportation or processing hub where products are handled and distributed.
7. PORT OF EXPORT: The export port from which soy products are shipped to international destinations.
8. EXPORTER: The company or entity responsible for exporting soy products.
9. EXPORTER GROUP: The group to which the exporter belongs.
10. IMPORTER: The company or entity that imports soy products.
11. IMPORTER GROUP: The group to which the importer belongs.
12. COUNTRY OF FIRST IMPORT: The country that first imports soy products.
13. ECONOMIC BLOC: The economic bloc to which the involved countries belong, such as the European Union or Mercosur.
14. TYPE: The type or category of information contained in the record.
15. Soy deforestation exposure: Exposure to deforestation associated with soy production.
16. FOB_USD: The value in US dollars of the Free on Board (FOB) product, indicating the price of the product at the export port.
17. CO2_GROSS_EMISSIONS_SOY_DEFORESTATION_5_YEAR_TOTAL_EXPOSURE: Gross CO2 emissions associated with deforestation caused by soy production over a five-year period.
18. SOY_EQUIVALENT_TONNES: The quantity of soy in metric tonnes used as a unit of measurement.
19. LAND_USE_HA: The amount of land used in hectares for soy production.
20. CO2_NET_EMISSIONS_SOY_DEFORESTATION_5_YEAR_TOTAL_EXPOSURE: Net CO2 emissions associated with deforestation caused by soy production over a five-year period.
21. Soy deforestation risk: The risk of deforestation associated with soy production.
22. ZERO_DEFORESTATION_BRAZIL_SOY: Indicates whether soy was produced without causing deforestation in Brazil.
23. TRASE_GEOCODE: The geographical location code associated with the record.

These variables form part of a Trase dataset tracking soy production, export, and environmental impacts within the context of the soy industry in Brazil and other countries. They are crucial for understanding and monitoring trends and impacts associated with this economic activity.

Brazil Agricultural Production: Soybeans data was reported at 152,144.238 Ton th in 2023. This records an increase from the previous number of 121,290.103 Ton th for 2022. Brazil Agricultural Production: Soybeans data is updated yearly, averaging 31,147.458 Ton th from Dec 1974 (Median) to 2023, with 50 observations. The data reached an all-time high of 152,144.238 Ton th in 2023 and a record low of 7,876.527 Ton th in 1974. Brazil Agricultural Production: Soybeans data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Global Database’s Brazil – Table BR.RIB008: Agricultural Production: Temporary Crops.

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Forecast: Soybean Oil Domestic Industrial Consumption in Brazil 2022 - 2026 Discover more data with ReportLinker!

Forecast: Soybean Oil Production in Brazil 2022 - 2026 Discover more data with ReportLinker!

Forecast: Soybean Oil Production in Brazil 2023 - 2027 Discover more data with ReportLinker!

Brazil Agricultural Production: Volume: Soybean data was reported at 112,546,649.000 Ton in Jun 2019. This records an increase from the previous number of 112,474,505.000 Ton for May 2019. Brazil Agricultural Production: Volume: Soybean data is updated monthly, averaging 58,514,280.500 Ton from Mar 1998 (Median) to Jun 2019, with 256 observations. The data reached an all-time high of 117,927,506.000 Ton in Nov 2018 and a record low of 29,284,927.000 Ton in Jan 1999. Brazil Agricultural Production: Volume: Soybean data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Agriculture Sector – Table BR.RIB001: Agricultural Production.

Supply chain information is invaluable to further regionalize product life cycle assessments (LCAs), but detailed information linking production and consumption centers is not always available. We introduce the commodity supply mix (CSM) defined as the trade-volume-weighted average representing the combined geographic areas for the production of a commodity exported to a given market with the goal of (1) enhancing the relevance of inventory and impact regionalization and (2) allocating these impacts to specific markets. We apply the CSM to the Brazilian soybean supply chain mapped by Trase to obtain the mix of ecoregions and river basins linked to domestic consumption and exports to China, EU, France, and the rest of the world, before quantifying damage to biodiversity, and water scarcity footprints. The EU had the lowest potential biodiversity damage but the largest water scarcity footprint following respective sourcing patterns in 12 ecoregions and 18 river basins. These results differed from the average impact scores obtained from Brazilian soybean production information alone. The CSM can be derived at different scales (subnationally, internationally) using existing supply chain information and constitutes an additional step toward greater regionalization in LCAs, particularly for impacts with greater spatial variability such as biodiversity and water scarcity.

This dataset contains a collection of evaluative assertions extracted from the public communications of four of Brazil's most influential agribusiness associations: Abiove (Brazilian Association of Vegetable Oil Industries), Aprosoja Brasil (Brazilian Association of Soy Producers), CNA (Confederation of Agriculture and Livestock of Brazil), and the Brazil Climate, Forests and Agriculture Coalition. The data was collected as part of a research project analyzing the response strategies of these actors to the environmental and foreign policies during the Jair Bolsonaro administration. The data covers the period from October 2018 to January 2023.

The Round Table on Responsible Soy (RTRS) is a civil society organization that promotes the production, processing and marketing of responsible soy globally. It aims to promote sustainable production to reduce the social and environmental impacts of soybeans. The RTRS Responsible Soy Production Map is created based on RTRS Standards, and is intended to guide responsible expansion of soybean production for RTRS certification. The RTRS committed to create macro-scale maps for Argentina, Brazil, Bolivia, and Paraguay to identify and preserve critical ecosystems and High Conservation Value Areas (HCVAs), as well as identify opportunities for responsible expansion of soy with low levels of environmental impact. The process began in Brazil in 2012, followed by Paraguay in 2013. Additional national level maps (e.g. Argentina) are in development. These national maps are created by RTRS National Technical Groups in each country, with experts representing all levels of the supply chain to interpret the global methodology at the national level. Each group was led by local coordinators and supported by GIS companies and consultative groups, as well as BACP (IFC), IDH, 3Fi, WWF and The Gordon and Betty Moore Foundation, the principal funders of this project.

The guides were developed according to Annex 4: RTRS approach to responsible conversion, page 20, of the RTRS Production Standard. The macro-scale maps show the four different categories described in Guide 4 of the Standard, and the High Conservation Value Areas assessment guides for determination and management of HCVAs.

The categories are as follows:

1. Areas which are critical for biodiversity (hotspots), where stakeholders agree there should not be any conversion of native to responsible soy production.

2. Areas with high importance for biodiversity where expansion of soy is only carried out after an HCVA assessment which identifies areas for conservation and areas where expansion can occur.

3. Areas where existing legislation is adequate to control responsible expansion (usually areas with importance for agriculture and lower conservation).

4. Areas which are already used for agriculture and where there is no remaining native vegetation except legal reserves and so no further expansion is occurring.

5. Areas deforested after 2009.

DescriptionPalm oil mills: The data comes from FoodReg’s Known Sources palm oil mill database and directly from palm oil traders and buyers. The data represents the mills within the supply chain of at least three major palm oil buyers who wish to remain anonymous. The data does not represent the entire universe of mills, and is only representative of the mills within the supply chains of companies submitting mill data to WRI or Known Sources. The location of mills was self-reported by mill owners. All mill locations were manually verified by WRI using Google Earth imagery according to criteria for mill infrastructure including the presence of buildings, settling ponds, and nearby palm oil plantations. Mills may have duplicate names when site-level name data is missing and group name information is included. The data will be updated as new data becomes available to WRI or Known Sources.Oil palm concessions (select countries): refers to an area allocated by a government or other body for industrial-scale oil palm plantations.The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations. Includes:Liberia oil palm concessions: refers to an area allocated by a government or other body for industrial-scale oil palm plantations.The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations. This data set provides the boundaries of known oil palm plantations for Liberia and was compiled by Global Witness from available government maps. Information provided with this data set includes company, ownership group, and land area.Cameroon agro-industrial zones: This data layer shows the boundaries of agro-industrial zones, where oil palm and rubber tree plantations, as well as other crops, may be established. In Cameroon, industrial agriculture falls outside of the National Forest Estate. Agricultural plantations are allocated by the Ministry of Economy and Planning to private entities under long-term, renewable contracts, which are then monitored by the Ministry of Agriculture. The agro-industrial data set was mapped using satellite imagery, with ground-truthing to determine the crop type and operating company. Official documentation was often lacking, so boundaries should be considered approximate and nonexhaustive.Republic of the Congo oil palm concessions: This data set provides the boundaries for oil palm plantations according to the Republic of the Congo Ministry of Agriculture. Indonesia oil palm concessions: Oil palm concession refers to an area allocated by a government or other body for industrial-scale oil palm plantations. The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources. Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations.This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned oil palm plantations in Indonesia. This data set is known to be incomplete, but it is currently the best available. RSPO palm oil mills: this data layer displays plantation management units (PMU) certified under RSPO through May, 2013. These data are arranged by company group holding the majority shareholding in each unit.RSPO oil palm concessions (Brazil, Indonesia, Cambodia, Malaysia, Papua New Guinea and Thailand): The RSPO concession boundaries were produced by member companies and compiled by Aidenvironment.org. Other data is included from Annual Surveillance Assessments provided by the RSPO as well as third-party audit reports screened by Aidenvironment.org. SPOTT featured company concessions: SPOTT-Sustainability Policy Transparency Toolkit is an online platform supporting sustainable commodity production and trade. This database summarizes some assessments of palm oil producers and traders in relation to its operations and commitments related to environmental, social and governance (ESG) issues. RTRS Guides for Responsible Soy Expansion: The Round Table on Responsible Soy (RTRS) is a civil society organization that promotes the production, processing and marketing of responsible soy globally. It aims to promote sustainable production to reduce the social and environmental impacts of soybeans. The RTRS Responsible Soy Production Map is created based on RTRS Standards, and is intended to guide responsible expansion of soybean production for RTRS certification. The RTRS committed to create macro-scale maps for Argentina, Brazil, Bolivia, and Paraguay to identify and preserve critical ecosystems and High Conservation Value Areas (HCVAs), as well as identify opportunities for responsible expansion of soy with low levels of environmental impact. The process began in Brazil in 2012, followed by Paraguay in 2013. Additional national level maps (e.g. Argentina) are in development. These national maps are created by RTRS National Technical Groups in each country, with experts representing all levels of the supply chain to interpret the global methodology at the national level. Each group was led by local coordinators and supported by GIS companies and consultative groups, as well as BACP (IFC), IDH, 3Fi, WWF and The Gordon and Betty Moore Foundation, the principal funders of this project. The guides were developed according to Annex 4: RTRS approach to responsible conversion, page 20, of the RTRS Production Standard. The macro-scale maps show the four different categories described in Guide 4 of the Standard, and the High Conservation Value Areas assessment guides for determination and management of HCVAs. Date of update and consistency on attributes might differ as the layer is a compilation of concession data from various countries and sources. LimitationsDate of update and consistency on attributes might differ as the layers are a compilation of data from various countries and sources. CreditsPalm Oil Mills, RSPO Palm Oil Mills and Oil Palm ConcessionsGlobal Forest Watch - Data may come from government agencies, NGOs or other organizations. Accessed through GFW portal http://data.globalforestwatch.org/datasetsSPOTT featured company concessions Zoological Society of London - using data provided by Global Forest Watch from the World Resources Institute (WRI). Accessed through GFW portal http://data.globalforestwatch.org/datasetsRSTRS Guides for Responsible Soy ExpansionRound Table on Responsible Soy (RTRS). Accessed through GFW portal http://data.globalforestwatch.org/datasetsAttributesPalm Oil Millsobjectid: Assigned by WWF. Unique identifierwri_id: World Resources Institute identifiermill_name_: Name of the assetgroup_name: Name of the company operating the palm oil milliso: ISO-Alpha 3 code for the country where the mill is located. Cross-reference herecertificat: Indicates if the mill has RSPO certificationcompany_na: Name of the company operating the millglobalid: Global Forest Watch identifierx: X location in the original coordinate system of the database (WGS 1984)y: Y location in the original coordinate system of the database (WGS 1984)Oil Palm ConcessionsOBJECTID: Assigned by WWF. Unique identifierCountry: Country where the oil palm concession is locatedName: Local name of the company operating in the concessionCompany: International name of the company operating in the concessionGroup: International name of the companySub Group: Regional name of the company if appliesGroup ID: Assigned by GFW. Identifier for the Group company. Concession Type: Type of permission associated to the concessionGIS Calculated Area (ha): Reported area of the concession in hectaresSource: Original source of the concession dataLast Update: Last update of the information in the original databaseGFW ID: Global Forest Watch identifierRSPO Palm Oil MillsOBJECTID: Assigned by WWF. Unique identifierlongitude: Longitude in the original coordinate system of the database (WGS 1984)audit_stat: State of the certification process (Initial, renewal)legal_radi: Indicates werther the palm oil mill is located within a radius of up to 10 km from the palm oil concessions (Yes: 1, No: 0)illegal_ra: Indicates werther the palm oil mill is located within a radius of up to 10 km from the palm oil concessions (Yes: 0 or 1, Any other number reflects the distance in km*100)radius_umdradius_for: Presumably an indicator of the distance from the mill to the forests in the area of influenceprimary_in: Presumably an indicator of the primary forest in the areaprimary_1: Presumably an indicator of the primary forest in the areacarbon_rad: Presumably an indicator of the amount of carbon storage in the ecosystems in the area of influence (forest, peatlands, etcetera) peat_radiu: Presumably an indicator of the distance from the mill to peat lands in the area of influence peat_area_: Presumably an indicator of the area of the peatlands in the area of influencefires_radi: Presumably an indicator of the distance within the mill and identified fires in the area of influenceillegal_1: Presumably an indicator that classifies qualitatively the attribute fires_radi (low, high, medium)radius_u_1: Presumably an indicator that classifies qualitatively the attribute radius_umd (low, high, medium)radius_f_1: Presumably an indicator that classifies qualitatively the attribute radius_for (low, high, medium)primary_2: Presumably an indicator that classifies qualitatively the attribute primary_in (low, high, medium)primary_3: Presumably

This is the supplementary information of the research on Soybean production systems carried out in Brazil. The research analyzed the conventional and alternative pathways of soybean production in two agroecoregions of Brazil. The file provided present supplementary information complementing the text of the article.

Forecast: Soybeans Production Level in Brazil 2024 - 2028 Discover more data with ReportLinker!

Forecast: Soybeans Production Level in Brazil 2022 - 2026 Discover more data with ReportLinker!

Soil macrofauna communities were evaluated in two areas recently being converted from conventional to organic grain (soybean) crop production systems at the Embrapa Soybean experiment station in Londrina, Paraná, Brazil. Sampling was performed in October 2003 in an area planted with soybean under conventional tillage and an area planted with pigeon-pea (Cajanus cajan) under no-tillage system. Samples were taken using the standard methodology of the Tropical Soil Biology and Fertility Programme (TSBF), where soil (down to 30 cm depth) and litter fauna were hand-sorted from monoliths of 25x25 cm, and the abundance of a total of 42 taxa was assessed.

Forecast: Soybeans Production at Farm Gate in Brazil 2022 - 2026 Discover more data with ReportLinker!

ABSTRACT. This study had two objectives - firstly, to analyze the total static and dynamic capacity of agricultural storage in Paraná State, Brazil and secondly, to verify if the storage followed the growth of grain production. The study was performed by mesoregion for the 2013/2014 and 2014/2015 crop years. The methodology used was descriptive from an agricultural database of the Secretariat of Agriculture and Supply (SEAB), of the National Register System of Storage Units (SICARM), interviews were also made with agroindustrial cooperatives and official agencies. It was identified that in Paraná State there is an insufficiency of 17.75% of total static capacity of warehouses to comply with the total grain production (soybean, 1st and 2nd corn crops, and wheat). The results showed that the total dynamic capacity of warehouses is sufficient in the mesoregions of Eastern Center, Southern Center, Northern Center, and Metropolitan. Therefore, storage units vary uniformly in most municipalities, not following the growth of total grain production in the state of Paraná.

Brazil Agricultural Production: Volume: Temporary Crops: Southeast: Soybean data was reported at 8,579.535 Ton th in 2017. This records an increase from the previous number of 7,540.290 Ton th for 2016. Brazil Agricultural Production: Volume: Temporary Crops: Southeast: Soybean data is updated yearly, averaging 3,837.144 Ton th from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 8,579.535 Ton th in 2017 and a record low of 1,685.994 Ton th in 1990. Brazil Agricultural Production: Volume: Temporary Crops: Southeast: Soybean data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Agriculture Sector – Table BR.RIB010: Agricultural Production: Temporary Crops: Southeast.

Brazil Exports: FOB: Italy: Soybeans, Incl Grinded data was reported at 11.346 USD mn in Jun 2019. This records a decrease from the previous number of 16.039 USD mn for May 2019. Brazil Exports: FOB: Italy: Soybeans, Incl Grinded data is updated monthly, averaging 12.100 USD mn from Dec 1998 (Median) to Jun 2019, with 205 observations. The data reached an all-time high of 126.159 USD mn in May 2008 and a record low of 0.000 USD mn in Jan 2018. Brazil Exports: FOB: Italy: Soybeans, Incl Grinded data remains active status in CEIC and is reported by Ministry of Development, Industry And Trade. The data is categorized under Brazil Premium Database’s Foreign Trade – Table BR.JAC004: Exports: by Principal Commodities: Italy.