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Registro Completo |
Biblioteca(s): |
Embrapa Algodão. |
Data corrente: |
02/07/2014 |
Data da última atualização: |
02/07/2014 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
NASCIMENTO, I. M.; SILVA, J. D.; MEDEIROS, E. P. de. |
Afiliação: |
NASCIMENTO, I. M.; SILVA, J. D.; EVERALDO PAULO DE MEDEIROS, CNPA. |
Título: |
Um fotômetro led-nir para screening análise de torta de mamona detoxificada. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
In: ENCONTRO DE PRODUÇÃO CIENTÍFICA DA EMBRAPA ALGODÃO - EPC 2013, 8., 2013, Campina Grande. [Resumos...]. Campina Grande: Embrapa Algodão, 2013. |
Páginas: |
p. 22 |
Idioma: |
Português |
Thesagro: |
Fotômetro. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00575naa a2200157 a 4500 001 1989557 005 2014-07-02 008 2013 bl uuuu u00u1 u #d 100 1 $aNASCIMENTO, I. M. 245 $aUm fotômetro led-nir para screening análise de torta de mamona detoxificada.$h[electronic resource] 260 $c2013 300 $ap. 22 650 $aFotômetro 700 1 $aSILVA, J. D. 700 1 $aMEDEIROS, E. P. de 773 $tIn: ENCONTRO DE PRODUÇÃO CIENTÍFICA DA EMBRAPA ALGODÃO - EPC 2013, 8., 2013, Campina Grande. [Resumos...]. Campina Grande: Embrapa Algodão, 2013.
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Embrapa Algodão (CNPA) |
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Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
02/08/2017 |
Data da última atualização: |
07/01/2020 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
CAMARGO, L. de; OLIVEIRA, A. L. de; OLIVEIRA, S. R. de M.; COLETI, J. de C. |
Afiliação: |
LARISSA DE CAMARGO, IAC; ANDRÉA LEDA RAMOS DE OLIVEIRA, Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; JAMILE DE CAMPOS COLETI, Unicamp. |
Título: |
Analysis of regional patterns of grain production and storage in Brazil: a clustering application. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
In: CONFERENCE INTERNATIONAL CONSORTIUM ON APPLIED BIOECONOMY RESEARCH, 21., 2017, Berkeley. Bioeconomy in transition: new tools and new actors. Berkeley: University of California, 2017. |
Idioma: |
Inglês |
Conteúdo: |
The aim of this study is to identify patterns in the production and storage of grains in Brazil from 1980 to 2015 and analyze the conditions of similarity of each group. The technique of data mining Clustering was applied through the algorithm k-means to transform the historical series of grain storage and production into a group of similarities. The results show that the application of the mining technique coherently delimited the regions, which had a direct relation with the expansion of the agricultural frontier in Brazil, proving to be efficient for this application. Four clusters were formed. The first is composed by States of the South Region referring to consolidated crops since the 1960s. The second is composed of States of the Midwest and Southeast regions, revealing the second phase of the country's agricultural expansion. The third is made by states that do not have agricultural potential by soil and climate conditions, with an inexpressive agriculture. Finally, the fourth cluster shows the new Brazilian agricultural frontier called MATOPIBA (Maranhão, Tocantins, Piauí and Bahia), which has reached records in the production and export of grains driven by the installation of new transport routes. |
Palavras-Chave: |
Data mining; Logistics. |
Thesagro: |
Agronegócio. |
Thesaurus NAL: |
agribusiness. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 01955nam a2200193 a 4500 001 2073467 005 2020-01-07 008 2017 bl uuuu u00u1 u #d 100 1 $aCAMARGO, L. de 245 $aAnalysis of regional patterns of grain production and storage in Brazil$ba clustering application.$h[electronic resource] 260 $aIn: CONFERENCE INTERNATIONAL CONSORTIUM ON APPLIED BIOECONOMY RESEARCH, 21., 2017, Berkeley. Bioeconomy in transition: new tools and new actors. Berkeley: University of California$c2017 520 $aThe aim of this study is to identify patterns in the production and storage of grains in Brazil from 1980 to 2015 and analyze the conditions of similarity of each group. The technique of data mining Clustering was applied through the algorithm k-means to transform the historical series of grain storage and production into a group of similarities. The results show that the application of the mining technique coherently delimited the regions, which had a direct relation with the expansion of the agricultural frontier in Brazil, proving to be efficient for this application. Four clusters were formed. The first is composed by States of the South Region referring to consolidated crops since the 1960s. The second is composed of States of the Midwest and Southeast regions, revealing the second phase of the country's agricultural expansion. The third is made by states that do not have agricultural potential by soil and climate conditions, with an inexpressive agriculture. Finally, the fourth cluster shows the new Brazilian agricultural frontier called MATOPIBA (Maranhão, Tocantins, Piauí and Bahia), which has reached records in the production and export of grains driven by the installation of new transport routes. 650 $aagribusiness 650 $aAgronegócio 653 $aData mining 653 $aLogistics 700 1 $aOLIVEIRA, A. L. de 700 1 $aOLIVEIRA, S. R. de M. 700 1 $aCOLETI, J. de C.
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