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Registro Completo |
Biblioteca(s): |
Embrapa Acre; Embrapa Amazônia Oriental. |
Data corrente: |
31/10/2018 |
Data da última atualização: |
10/01/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
APARECIDO, L. E. de O.; MORAES, J. R. da S. C. de; ROLIM, G. de S.; MARTORANO, L. G.; SOARES, S. dos S.; MENESES, K. C. de; COSTA, C. T. S.; MESQUITA, D. Z.; BARBOSA, A. M. da S.; AMARAL, E. F. do; BARDALES, N. G. |
Afiliação: |
Lucas Eduardo de Oliveira Aparecido, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; José Reinaldo da Silva Cabral de Moraes, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Glauco de Souza Rolim, São Paulo State University; LUCIETA GUERREIRO MARTORANO, CPATU; Sabrina dos Santos Soares, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Kamila Cunha de Meneses, São Paulo State University; Cicero Teixeira Silva Costa, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Daniel Zimmermann Mesquita, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Aline Michelle da Silva Barbosa, São Paulo State University; EUFRAN FERREIRA DO AMARAL, CPAF-AC; Nilson Gomes Bardales, EMBRAPA. |
Título: |
Neural networks in spatialization of meteorological elements and their application in the climatic agricultural zoning of bamboo. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
International Journal of Biometeorology, v. 62, n. 11, p. 1955-1962, Nov. 2018. |
DOI: |
10.1007/s00484-018-1596-1 |
Idioma: |
Inglês |
Conteúdo: |
Bamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piauí, Maranhão, Rondônia, and Acre. The regions that have restrictions due to lowTAIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of TAIR and portions of the northern region that have high levels of P which is favorable for the development of diseases. MenosBamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piau... Mostrar Tudo |
Palavras-Chave: |
Aclimatación; Climate risk; Crop zoning; Modeling; Multilayer perceptron; Redes neuronales; Training algorithm; Zonificación agrícola. |
Thesagro: |
Aclimatação; Bambu; Bambusa Vulgaris; Climatologia; Modelo Matemático; Risco Climático; Zoneamento Agrícola. |
Thesaurus Nal: |
Acclimation; Agricultural zoning; Bamboos; Climatology; Mathematical models; Neural networks. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 03571naa a2200505 a 4500 001 2098629 005 2019-01-10 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1007/s00484-018-1596-1$2DOI 100 1 $aAPARECIDO, L. E. de O. 245 $aNeural networks in spatialization of meteorological elements and their application in the climatic agricultural zoning of bamboo.$h[electronic resource] 260 $c2018 520 $aBamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piauí, Maranhão, Rondônia, and Acre. The regions that have restrictions due to lowTAIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of TAIR and portions of the northern region that have high levels of P which is favorable for the development of diseases. 650 $aAcclimation 650 $aAgricultural zoning 650 $aBamboos 650 $aClimatology 650 $aMathematical models 650 $aNeural networks 650 $aAclimatação 650 $aBambu 650 $aBambusa Vulgaris 650 $aClimatologia 650 $aModelo Matemático 650 $aRisco Climático 650 $aZoneamento Agrícola 653 $aAclimatación 653 $aClimate risk 653 $aCrop zoning 653 $aModeling 653 $aMultilayer perceptron 653 $aRedes neuronales 653 $aTraining algorithm 653 $aZonificación agrícola 700 1 $aMORAES, J. R. da S. C. de 700 1 $aROLIM, G. de S. 700 1 $aMARTORANO, L. G. 700 1 $aSOARES, S. dos S. 700 1 $aMENESES, K. C. de 700 1 $aCOSTA, C. T. S. 700 1 $aMESQUITA, D. Z. 700 1 $aBARBOSA, A. M. da S. 700 1 $aAMARAL, E. F. do 700 1 $aBARDALES, N. G. 773 $tInternational Journal of Biometeorology$gv. 62, n. 11, p. 1955-1962, Nov. 2018.
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Embrapa Amazônia Oriental (CPATU) |
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Biblioteca(s): |
Embrapa Milho e Sorgo; Embrapa Pecuária Sudeste. |
Data corrente: |
28/12/2000 |
Data da última atualização: |
09/06/2018 |
Tipo da produção científica: |
Comunicado Técnico/Recomendações Técnicas |
Autoria: |
ALVES, V. M. C.; VASCONCELLOS, C. A.; FREIRE, F. M.; PITTA, G. V. E.; FRANCA, G. E. |
Afiliação: |
VERA MARIA CARVALHO ALVES, CNPMS. |
Título: |
Recomendacoes para o uso de corretivos e fertilizantes em sorgo no Estado de Minas Gerais. |
Ano de publicação: |
2000 |
Fonte/Imprenta: |
Sete Lagoas: EMBRAPA-CNPMS, 2000. |
Páginas: |
2 p. |
Série: |
(EMBRAPA-CNPMS. Comunicado técnico, 19). |
Idioma: |
Português |
Conteúdo: |
Recomendações para o uso de corretivos e fertilizantes em sorgo no Estado de Minas Gerais. |
Palavras-Chave: |
Brasil; Corretive dressing; Minas Gerais. |
Thesagro: |
Corretivo; Fertilizante; Sorghum Bicolor; Sorgo. |
Thesaurus NAL: |
Brazil; fertilizers. |
Categoria do assunto: |
-- F Plantas e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/30335/1/ct-19.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/46278/1/OK-RecomendacoesCorretivosFertilizantes.pdf
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Marc: |
LEADER 00873nam a2200289 a 4500 001 1484424 005 2018-06-09 008 2000 bl uuuu u0uu1 u #d 100 1 $aALVES, V. M. C. 245 $aRecomendacoes para o uso de corretivos e fertilizantes em sorgo no Estado de Minas Gerais. 260 $aSete Lagoas: EMBRAPA-CNPMS$c2000 300 $a2 p. 490 $a(EMBRAPA-CNPMS. Comunicado técnico, 19). 520 $aRecomendações para o uso de corretivos e fertilizantes em sorgo no Estado de Minas Gerais. 650 $aBrazil 650 $afertilizers 650 $aCorretivo 650 $aFertilizante 650 $aSorghum Bicolor 650 $aSorgo 653 $aBrasil 653 $aCorretive dressing 653 $aMinas Gerais 700 1 $aVASCONCELLOS, C. A. 700 1 $aFREIRE, F. M. 700 1 $aPITTA, G. V. E. 700 1 $aFRANCA, G. E.
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Embrapa Milho e Sorgo (CNPMS) |
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