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Registro Completo |
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
06/09/2019 |
Data da última atualização: |
23/01/2020 |
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.; MENESES, K. C. de; VALERIANO, T. T. B. |
Afiliação: |
Lucas Eduardo de Oliveira Aparecido, IFMS; José Reinaldo da Silva Cabral de Moraes, UNESP; Glauco de Souza Rolim, UNESP; LUCIETA GUERREIRO MARTORANO, CPATU; Kamila Cunha de Meneses, UNESP; Taynara Tuany Borges Valeriano, UNESP. |
Título: |
Neural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Archives of Agronomy and Soil Science, v. 65, n. 11, p. 1477-1492, 2019. |
DOI: |
10.1080/03650340.2019.1566715 |
Idioma: |
Inglês |
Conteúdo: |
Sunflower is a species that is sensitive to local climate conditions. However, studies that use artificial neural networks (ANNs) to evaluate this influence and create tools such as agricultural zoning of climate risk (ZARC) have not been conducted for this species. Due to the importance of sunflower as a human food source and for biodiesel production, and also the necessity of conducting research to evaluate the suitability of this oleaginous species under different climatic conditions. Thus, we seek to construct a ZARC for sunflower in Brazil simulating sowing on different dates and using meteorological elements spatialized by ANNs. Climate data were used: air temperature (T), rainfall (P), relative air humidity (UR), solar radiation (MJ_m−2_d−1) and wind velocity (U2). Climatic regions considered suitable for the cultivation of sunflower had average annual values for T between 20 and 28°C, P between 500 and 1.500 mm per cycle, and soil water deficit (DEF) below 140 mm per cycle. A neural network is an efficient tool that can be used in spatialization of climate variables quickly and accurately. Sunflower sowing in the spring and summer are the ones that provide the largest suitable areas in southeastern Brazil, with 58.13 and 64.36% of suitable areas, respectively |
Thesagro: |
Clima; Girassol; Zoneamento Agrícola. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02087naa a2200229 a 4500 001 2112016 005 2020-01-23 008 2019 bl uuuu u00u1 u #d 024 7 $a10.1080/03650340.2019.1566715$2DOI 100 1 $aAPARECIDO, L. E. de O. 245 $aNeural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates.$h[electronic resource] 260 $c2019 520 $aSunflower is a species that is sensitive to local climate conditions. However, studies that use artificial neural networks (ANNs) to evaluate this influence and create tools such as agricultural zoning of climate risk (ZARC) have not been conducted for this species. Due to the importance of sunflower as a human food source and for biodiesel production, and also the necessity of conducting research to evaluate the suitability of this oleaginous species under different climatic conditions. Thus, we seek to construct a ZARC for sunflower in Brazil simulating sowing on different dates and using meteorological elements spatialized by ANNs. Climate data were used: air temperature (T), rainfall (P), relative air humidity (UR), solar radiation (MJ_m−2_d−1) and wind velocity (U2). Climatic regions considered suitable for the cultivation of sunflower had average annual values for T between 20 and 28°C, P between 500 and 1.500 mm per cycle, and soil water deficit (DEF) below 140 mm per cycle. A neural network is an efficient tool that can be used in spatialization of climate variables quickly and accurately. Sunflower sowing in the spring and summer are the ones that provide the largest suitable areas in southeastern Brazil, with 58.13 and 64.36% of suitable areas, respectively 650 $aClima 650 $aGirassol 650 $aZoneamento Agrícola 700 1 $aMORAES, J. R. da S. C. de 700 1 $aROLIM, G. de S. 700 1 $aMARTORANO, L. G. 700 1 $aMENESES, K. C. de 700 1 $aVALERIANO, T. T. B. 773 $tArchives of Agronomy and Soil Science$gv. 65, n. 11, p. 1477-1492, 2019.
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Embrapa Amazônia Oriental (CPATU) |
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Biblioteca(s): |
Embrapa Agroindústria de Alimentos. |
Data corrente: |
09/11/2020 |
Data da última atualização: |
23/11/2020 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
COMETTANT-RABANAL, R.; CARVALHO, C. W. P. de; ASCHERI, J. L. R.; HIDALGO CHÁVEZ, D. W.; GERMANI, R. |
Afiliação: |
Raúl Comettant-Rabanal, UFRRJ; CARLOS WANDERLEI PILER DE CARVALHO, CTAA; JOSE LUIS RAMIREZ ASCHERI, CTAA; Davy William Hidalgo Chávez, UFRRJ; ROGERIO GERMANI, CTAA. |
Título: |
Extruded whole grain flours as ingredient for gluten-free bread: rheological evaluation. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
In: CONGRESSO ON-LINE BRASILEIRO DE TECNOLOGIA DE CEREAIS E PANIFICAÇÃO, 2020, virtual. Anais... Saudabilidade na Indústria de Cereais e Panificação. Sete Lagoas: Universidade Federal de São João del-Rei, 2020. 4 p. |
ISBN: |
978-65-88243-73-2 |
DOI: |
10.29327/cbcp2020.276130 |
Idioma: |
Inglês |
Notas: |
CBCP; 5 a 9 out. |
Conteúdo: |
Whole grain flours of maize, rice and sorghum were processed by thermoplastic extrusion at 25% of moisture and milled into pre-cooked whole grain fine flours. Their pasting and farinograph properties were determined. The modification caused by extrusion was observed through apparent curve viscosity was observed and compared to their raw profile. The farinograph consistency and water absorption (WA) capacity of the extrusion pre-cooked whole grain flours stood out considerably among the farinographic properties, evidencing the development of outstanding viscoelastic properties. The reduction in the dough development time for all extruded flours, meant low processing cost of energy leading to possible adoption as ingredient by bakery industry of gluten free breads. |
Palavras-Chave: |
Dough rheology; Farinograph; Paste viscosity; Thermomechanical process. |
Thesagro: |
Produto de Origem Vegetal; Tecnologia de Alimento. |
Thesaurus NAL: |
Food technology; Gluten-free foods; Vegetable products. |
Categoria do assunto: |
Q Alimentos e Nutrição Humana |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217629/1/276130.pdf
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Marc: |
LEADER 01889nam a2200301 a 4500 001 2126389 005 2020-11-23 008 2020 bl uuuu u00u1 u #d 020 $a978-65-88243-73-2 024 7 $a10.29327/cbcp2020.276130$2DOI 100 1 $aCOMETTANT-RABANAL, R. 245 $aExtruded whole grain flours as ingredient for gluten-free bread$brheological evaluation.$h[electronic resource] 260 $aIn: CONGRESSO ON-LINE BRASILEIRO DE TECNOLOGIA DE CEREAIS E PANIFICAÇÃO, 2020, virtual. Anais... Saudabilidade na Indústria de Cereais e Panificação. Sete Lagoas: Universidade Federal de São João del-Rei, 2020. 4 p.$c2020 500 $aCBCP; 5 a 9 out. 520 $aWhole grain flours of maize, rice and sorghum were processed by thermoplastic extrusion at 25% of moisture and milled into pre-cooked whole grain fine flours. Their pasting and farinograph properties were determined. The modification caused by extrusion was observed through apparent curve viscosity was observed and compared to their raw profile. The farinograph consistency and water absorption (WA) capacity of the extrusion pre-cooked whole grain flours stood out considerably among the farinographic properties, evidencing the development of outstanding viscoelastic properties. The reduction in the dough development time for all extruded flours, meant low processing cost of energy leading to possible adoption as ingredient by bakery industry of gluten free breads. 650 $aFood technology 650 $aGluten-free foods 650 $aVegetable products 650 $aProduto de Origem Vegetal 650 $aTecnologia de Alimento 653 $aDough rheology 653 $aFarinograph 653 $aPaste viscosity 653 $aThermomechanical process 700 1 $aCARVALHO, C. W. P. de 700 1 $aASCHERI, J. L. R. 700 1 $aHIDALGO CHÁVEZ, D. W. 700 1 $aGERMANI, R.
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