Development Indicators and Soybean Production in Brazil

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 soy...

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Autores principales: Marley Nunes Vituri Toloi, Silvia Helena Bonilla, Rodrigo Carlo Toloi, Helton Raimundo Oliveira Silva, Irenilza de Alencar Nääs
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Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/a1a5fad20d384b8a96a050ef6d722cc2
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spelling oai:doaj.org-article:a1a5fad20d384b8a96a050ef6d722cc22021-11-25T16:01:34ZDevelopment Indicators and Soybean Production in Brazil10.3390/agriculture111111642077-0472https://doaj.org/article/a1a5fad20d384b8a96a050ef6d722cc22021-11-01T00:00:00Zhttps://www.mdpi.com/2077-0472/11/11/1164https://doaj.org/toc/2077-0472Due 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.Marley Nunes Vituri ToloiSilvia Helena BonillaRodrigo Carlo ToloiHelton Raimundo Oliveira SilvaIrenilza de Alencar NääsMDPI AGarticlesoybeanfactor analysis methodbehaviorframework DPSRIAgriculture (General)S1-972ENAgriculture, Vol 11, Iss 1164, p 1164 (2021)
institution DOAJ
collection DOAJ
language EN
topic soybean
factor analysis method
behavior
framework DPSRI
Agriculture (General)
S1-972
spellingShingle soybean
factor analysis method
behavior
framework DPSRI
Agriculture (General)
S1-972
Marley Nunes Vituri Toloi
Silvia Helena Bonilla
Rodrigo Carlo Toloi
Helton Raimundo Oliveira Silva
Irenilza de Alencar Nääs
Development Indicators and Soybean Production in Brazil
description 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.
format article
author Marley Nunes Vituri Toloi
Silvia Helena Bonilla
Rodrigo Carlo Toloi
Helton Raimundo Oliveira Silva
Irenilza de Alencar Nääs
author_facet Marley Nunes Vituri Toloi
Silvia Helena Bonilla
Rodrigo Carlo Toloi
Helton Raimundo Oliveira Silva
Irenilza de Alencar Nääs
author_sort Marley Nunes Vituri Toloi
title Development Indicators and Soybean Production in Brazil
title_short Development Indicators and Soybean Production in Brazil
title_full Development Indicators and Soybean Production in Brazil
title_fullStr Development Indicators and Soybean Production in Brazil
title_full_unstemmed Development Indicators and Soybean Production in Brazil
title_sort development indicators and soybean production in brazil
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/a1a5fad20d384b8a96a050ef6d722cc2
work_keys_str_mv AT marleynunesvituritoloi developmentindicatorsandsoybeanproductioninbrazil
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AT rodrigocarlotoloi developmentindicatorsandsoybeanproductioninbrazil
AT heltonraimundooliveirasilva developmentindicatorsandsoybeanproductioninbrazil
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