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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
14/05/2020 |
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Data da última atualização: |
14/05/2020 |
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Autoria: |
ROSA, J. C.; FARIA, M. V.; ZALUSKI, W. L.; GAVA, E.; ANDREOLI, P. H. W.; SAGAE, V. S. |
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Afiliação: |
Jocimar Costa Rosa, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia; Marcos Ventura Faria, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia; Welton Luiz Zaluski, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia; Emanuel Gava, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia; Pedro Henrique Willemann Andreoli, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia; Vitor Seiti Sagae, Universidade Estadual do Centro-Oeste - Unicentro/Departamento de Agronomia. |
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Título: |
Forage potential of S3 corn progenies in topcrosses and selection of testers of different genetic bases. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, v. 55, e01283, 2020. |
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Idioma: |
Português |
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Notas: |
Título em português: Potencial forrageiro de progênies S3 de milho em topcrosses e seleção de testadores de diferentes bases genéticas. |
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Conteúdo: |
The objective of this work was to identify corn (Zea mays) genotypes with forage potential and to evaluate the efficiency of testers to discriminate forage traits in topcrosses, considering the contribution of additive and nonadditive genes. The experiment was carried out in the 2015/2016 and 2016/2017 crop seasons, in a randomized complete block design with three replicates. Thirty S3 corn progenies were evaluated in topcrosses with the AG8025, P30B39, MLP102, 60.H23.1, and 70.H26.1 testers. The following traits were assessed: forage dry mass yield, neutral detergent fiber, acid detergent fiber, and forage dry mass degradability. Progenies 205.2, 159.6, and 199.2, in this order, presented the best performance for forage potential. Testers 60.H23.1 and 70.H26.1 better expressed the genetic variability between progenies. For all traits in both crop seasons, there is a predominance of the action of genes of nonadditive effects |
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Palavras-Chave: |
Additive effects; Dialelo parcial; Efeito aditivo; Efeito não aditivo; Nonadditive effects; Partial diallel. |
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Thesagro: |
Zea Mays. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/213012/1/Forage-potential-of-S3-corn-progenies.pdf
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Marc: |
LEADER 01874naa a2200277 a 4500
001 2122323
005 2020-05-14
008 2020 bl uuuu u00u1 u #d
100 1 $aROSA, J. C.
245 $aForage potential of S3 corn progenies in topcrosses and selection of testers of different genetic bases.$h[electronic resource]
260 $c2020
500 $aTítulo em português: Potencial forrageiro de progênies S3 de milho em topcrosses e seleção de testadores de diferentes bases genéticas.
520 $aThe objective of this work was to identify corn (Zea mays) genotypes with forage potential and to evaluate the efficiency of testers to discriminate forage traits in topcrosses, considering the contribution of additive and nonadditive genes. The experiment was carried out in the 2015/2016 and 2016/2017 crop seasons, in a randomized complete block design with three replicates. Thirty S3 corn progenies were evaluated in topcrosses with the AG8025, P30B39, MLP102, 60.H23.1, and 70.H26.1 testers. The following traits were assessed: forage dry mass yield, neutral detergent fiber, acid detergent fiber, and forage dry mass degradability. Progenies 205.2, 159.6, and 199.2, in this order, presented the best performance for forage potential. Testers 60.H23.1 and 70.H26.1 better expressed the genetic variability between progenies. For all traits in both crop seasons, there is a predominance of the action of genes of nonadditive effects
650 $aZea Mays
653 $aAdditive effects
653 $aDialelo parcial
653 $aEfeito aditivo
653 $aEfeito não aditivo
653 $aNonadditive effects
653 $aPartial diallel
700 1 $aFARIA, M. V.
700 1 $aZALUSKI, W. L.
700 1 $aGAVA, E.
700 1 $aANDREOLI, P. H. W.
700 1 $aSAGAE, V. S.
773 $tPesquisa Agropecuária Brasileira$gv. 55, e01283, 2020.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
30/10/2020 |
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Data da última atualização: |
04/11/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
YANO, I. H.; CASTRO, A. de; CANÇADO, G. M. de A.; SILVA, F. C. da. |
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Afiliação: |
INACIO HENRIQUE YANO, CNPTIA; ALEXANDRE DE CASTRO, CNPTIA; GERALDO MAGELA DE ALMEIDA CANCADO, CNPTIA; FABIO CESAR DA SILVA, CNPTIA. |
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Título: |
Storing data of sugarcane industry processes using blockchain technology. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
In: ENCONTRO NACIONAL DE ENGENHARIA DE PRODUÇÃO, 40., 2020, Foz do Iguaçu. Contribuições da engenharia de produção para a gestão de operações energéticas sustentáveis: anais. Rio de Janeiro: ABEPRO, 2020. |
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Páginas: |
p. 1-14. |
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ISSN: |
2594-9713 |
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Idioma: |
Inglês |
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Notas: |
ENEGEP 2020. |
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Conteúdo: |
Advances in information and communication technology (ICTs) have reduced physical, political and cultural barriers among nations. Furnished with equipment and sensors, and without connection limit, world population exercises globally its power of choice, creating reality out of Big Data, where high data and information volume on tendencies and demands reflect, among other features, cultural and psycho-social manifestations. Organizations involved with science and technological innovation are increasingly being required to invest heavily in tools and processes that support forecasting technological needs and on future demands on goods and services- which are more and more diffuse and dynamic - is essential for research and innovation organizations. This document describes specifically an agricultural industry context that is marked by the age of Big Data, generating high data volume that needs to be organized, stored and processed for generating knowledge, more specifically, this work deals with storing data of sugarcane processes using blockchain technology for control processes and tracking purposes. This work presents a prototype of the use of blockchain within the scope of a government project developed between the Embrapa - Brazilian Agricultural Research Corporation, and the Coplacana - Sugarcane Planters Cooperative located in the state of São Paulo, Brazil. |
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Palavras-Chave: |
Ethereum platform; Plataforma Ethereum; Produção de açúcar; Produção de álcool; Renovabio; Sistema de rastreamento; Sugar and Alcohol Production; Tecnologia blockchain; Tracking System. |
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Thesagro: |
Cana de Açúcar. |
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Thesaurus NAL: |
Sugar alcohols; Sugarcane. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/217322/1/PC-Storing-data-ENEGEP-2020.pdf
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Marc: |
LEADER 02497nam a2200325 a 4500
001 2126140
005 2020-11-04
008 2020 bl uuuu u00u1 u #d
022 $a2594-9713
100 1 $aYANO, I. H.
245 $aStoring data of sugarcane industry processes using blockchain technology.$h[electronic resource]
260 $aIn: ENCONTRO NACIONAL DE ENGENHARIA DE PRODUÇÃO, 40., 2020, Foz do Iguaçu. Contribuições da engenharia de produção para a gestão de operações energéticas sustentáveis: anais. Rio de Janeiro: ABEPRO$c2020
300 $ap. 1-14.
500 $aENEGEP 2020.
520 $aAdvances in information and communication technology (ICTs) have reduced physical, political and cultural barriers among nations. Furnished with equipment and sensors, and without connection limit, world population exercises globally its power of choice, creating reality out of Big Data, where high data and information volume on tendencies and demands reflect, among other features, cultural and psycho-social manifestations. Organizations involved with science and technological innovation are increasingly being required to invest heavily in tools and processes that support forecasting technological needs and on future demands on goods and services- which are more and more diffuse and dynamic - is essential for research and innovation organizations. This document describes specifically an agricultural industry context that is marked by the age of Big Data, generating high data volume that needs to be organized, stored and processed for generating knowledge, more specifically, this work deals with storing data of sugarcane processes using blockchain technology for control processes and tracking purposes. This work presents a prototype of the use of blockchain within the scope of a government project developed between the Embrapa - Brazilian Agricultural Research Corporation, and the Coplacana - Sugarcane Planters Cooperative located in the state of São Paulo, Brazil.
650 $aSugar alcohols
650 $aSugarcane
650 $aCana de Açúcar
653 $aEthereum platform
653 $aPlataforma Ethereum
653 $aProdução de açúcar
653 $aProdução de álcool
653 $aRenovabio
653 $aSistema de rastreamento
653 $aSugar and Alcohol Production
653 $aTecnologia blockchain
653 $aTracking System
700 1 $aCASTRO, A. de
700 1 $aCANÇADO, G. M. de A.
700 1 $aSILVA, F. C. da
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Embrapa Agricultura Digital (CNPTIA) |
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