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Development Indicators and Soybean Production in Brazil

Author

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  • Marley Nunes Vituri Toloi

    (Postgraduate Program in Production Engineering, Paulista University—UNIP, Dr. Bacelar Street 1212, São Paulo 04026-002, Brazil
    Federal Institute of the Mato Grosso, Rondonópolis 78721-520, Brazil)

  • Silvia Helena Bonilla

    (Postgraduate Program in Production Engineering, Paulista University—UNIP, Dr. Bacelar Street 1212, São Paulo 04026-002, Brazil)

  • Rodrigo Carlo Toloi

    (Federal Institute of the Mato Grosso, Rondonópolis 78721-520, Brazil)

  • Helton Raimundo Oliveira Silva

    (Postgraduate Program in Production Engineering, Paulista University—UNIP, Dr. Bacelar Street 1212, São Paulo 04026-002, Brazil)

  • Irenilza de Alencar Nääs

    (Postgraduate Program in Production Engineering, Paulista University—UNIP, Dr. Bacelar Street 1212, São Paulo 04026-002, Brazil)

Abstract

Due to its agricultural potential, land extensions, and favorable climate, Brazil is one of the largest producers and exporters of various agricultural products. A significant part of this production is placed in Mato Grosso, the primary national producer of several agricultural commodities. The soybean complex alone produced more than 33 million tons of soybean for the 2019/2020 harvest, representing 27% of national production. The economic potential that the soybean commodity represents is linked to the increase in demand for inputs, planted area, production, and productivity. Given these factors, the present study aims to analyze how the largest municipalities of soybean production behave, and the degree of interaction and positive associations between the economic potential promoted by soybean production and the economic/social development and environmental impacts in the Mato Grosso State, Brazil. The methodology was to categorize the thirty largest soybean producing municipalities, using the factor analysis method for selected indicators. The interpretation is made through the adoption of the Driver-Pressure-State-Impact-Response (DPSIR) framework. The results indicated that the groups formed are not homogeneous in terms of socio-economic and environmental development. The three factors that formed, were interpreted using the DPSIR are characterized by the significant influence of the population, reflect on its development, how economic activities are other and not just agriculture. The second also belongs to the driver in the DPSRI framework group. It is associated with the soybean production indicator, implying larger planting areas, generating jobs focused on agricultural activities. The interpretation is made through the adoption of the Driver-Pressure-State-Impact-Response (DPSIR) framework. The results indicated that the groups formed are not homogeneous in terms of socio-economic and environmental development. The significant influence of the population characterizes the three found factors. The first reflects on the region’s development and how other economic activities (not just agriculture) are carried on. The second also belongs to the driver in the DPSRI framework group, and it is associated with the soybean production indicator, generating jobs focused on agricultural activities. The third group, formed by municipalities in the Amazon region, with environmental factors associated with large geographical areas, extensive native forests, and more significant carbon sequestration, considers the DPSRI framework’s impacts. Showing that there are behavior patterns and taking this into account is the optimal way to use the predictors appropriately. Municipalities are expected to be more reactive to some changes than to others to achieve a good level of development.

Suggested Citation

  • Marley Nunes Vituri Toloi & Silvia Helena Bonilla & Rodrigo Carlo Toloi & Helton Raimundo Oliveira Silva & Irenilza de Alencar Nääs, 2021. "Development Indicators and Soybean Production in Brazil," Agriculture, MDPI, vol. 11(11), pages 1-15, November.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:11:p:1164-:d:682373
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    References listed on IDEAS

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    1. Emerson Rodolfo Abraham & João Gilberto Mendes dos Reis & Oduvaldo Vendrametto & Pedro Luiz de Oliveira Costa Neto & Rodrigo Carlo Toloi & Aguinaldo Eduardo de Souza & Marcos de Oliveira Morais, 2020. "Time Series Prediction with Artificial Neural Networks: An Analysis Using Brazilian Soybean Production," Agriculture, MDPI, vol. 10(10), pages 1-18, October.
    2. Russo Lopes, Gabriela & Bastos Lima, Mairon G. & Reis, Tiago N.P. dos, 2021. "Maldevelopment revisited: Inclusiveness and social impacts of soy expansion over Brazil’s Cerrado in Matopiba," World Development, Elsevier, vol. 139(C).
    3. Peter Richards & Heitor Pellegrina & Leah VanWey & Stephanie Spera, 2015. "Soybean Development: The Impact of a Decade of Agricultural Change on Urban and Economic Growth in Mato Grosso, Brazil," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-18, April.
    4. João Gilberto Mendes dos Reis & Pedro Sanches Amorim & José António Sarsfield Pereira Cabral & Rodrigo Carlo Toloi, 2020. "The Impact of Logistics Performance on Argentina, Brazil, and the US Soybean Exports from 2012 to 2018: A Gravity Model Approach," Agriculture, MDPI, vol. 10(8), pages 1-21, August.
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    2. Md Mahbubar Rahman & Arup Dey & Nita Yodo & Chiwon W. Lee & David Grewell, 2023. "Soybean By-Products Bioplastic (Polylactic Acid)-Based Plant Containers: Sustainable Development and Performance Study," Sustainability, MDPI, vol. 15(6), pages 1-18, March.

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