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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão; Embrapa Milho e Sorgo. |
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Data corrente: |
22/09/2016 |
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Data da última atualização: |
23/09/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RAMALHO, M. A. P.; ABREU, A. de F. B.; CARNEIRO, J. E. de S.; MELO, L. C.; PAULA JÚNIOR, T. J. de; PEREIRA, H. S.; DEL PELOSO, M. J.; PEREIRA FILHO, I. A.; MARTINS, M.; DEL GIÚDICE, M. P.; VIEIRA, R. F. |
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Afiliação: |
MARCO ANTONIO PATTO RAMALHO, UNIVERSIDADE FEDERAL DE LAVRAS; ANGELA DE FATIMA BARBOSA ABREU, CNPAF; JOSÉ EUSTÁQUIO DE SOUZA CARNEIRO, UNIVERSIDADE FEDERAL DE VIÇOSA; LEONARDO CUNHA MELO, CNPAF; TRAZILDO JOSÉ DE PAULA JÚNIOR, EPAMIG; HELTON SANTOS PEREIRA, CNPAF; MARIA JOSE DEL PELOSO, CNPAF; ISRAEL ALEXANDRE PEREIRA FILHO, CNPMS; MAURÍCIO MARTINS, UNIVERSIDADE FEDERAL DE UBERLÂNDIA; MARCOS PAIVA DEL GIÚDICE, UNIVERSIDADE FEDERAL DE VIÇOSA; ROGERIO FARIA VIEIRA, EPAMIG. |
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Título: |
BRSMG Uai: common bean cultivar with carioca grain type and upright plant architecture. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, Viçosa, MG, v. 16, n. 3, p. 261-264, July/Sept. 2016. |
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DOI: |
10.1590/1984-70332016v16n3c40 |
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Idioma: |
Inglês |
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Conteúdo: |
The common bean cultivar with carioca grain type, BRSMG Uai, is recommended for cultivation in Minas Gerais and stands out for its upright plant architecture, which facilitates cultivation and mechanical harvesting. This cultivar has high yield potential and is resistant to the major races of anthracnose that occur in region. |
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Thesagro: |
Feijão; Melhoramento genético vegetal; Phaseolus vulgaris; Variedade resistente. |
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Thesaurus Nal: |
Breeding; Disease resistance; Grain yield; Varieties. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/147709/1/CNPAF-2016-cbab-BRSMG-Uai.pdf
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Marc: |
LEADER 01405naa a2200349 a 4500
001 2053342
005 2016-09-23
008 2016 bl uuuu u00u1 u #d
024 7 $a10.1590/1984-70332016v16n3c40$2DOI
100 1 $aRAMALHO, M. A. P.
245 $aBRSMG Uai$bcommon bean cultivar with carioca grain type and upright plant architecture.$h[electronic resource]
260 $c2016
520 $aThe common bean cultivar with carioca grain type, BRSMG Uai, is recommended for cultivation in Minas Gerais and stands out for its upright plant architecture, which facilitates cultivation and mechanical harvesting. This cultivar has high yield potential and is resistant to the major races of anthracnose that occur in region.
650 $aBreeding
650 $aDisease resistance
650 $aGrain yield
650 $aVarieties
650 $aFeijão
650 $aMelhoramento genético vegetal
650 $aPhaseolus vulgaris
650 $aVariedade resistente
700 1 $aABREU, A. de F. B.
700 1 $aCARNEIRO, J. E. de S.
700 1 $aMELO, L. C.
700 1 $aPAULA JÚNIOR, T. J. de
700 1 $aPEREIRA, H. S.
700 1 $aDEL PELOSO, M. J.
700 1 $aPEREIRA FILHO, I. A.
700 1 $aMARTINS, M.
700 1 $aDEL GIÚDICE, M. P.
700 1 $aVIEIRA, R. F.
773 $tCrop Breeding and Applied Biotechnology, Viçosa, MG$gv. 16, n. 3, p. 261-264, July/Sept. 2016.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
02/01/2019 |
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Data da última atualização: |
21/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
RODRIGUES, L. S.; REZENDE, S. O.; MOURA, M. F.; MARCACINI, R. M. |
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Afiliação: |
LUCAS S. RODRIGUES, UFMS; SOLANGE O. REZENDE, UFSCar; MARIA FERNANDA MOURA, CNPTIA; RICARDO M. MARCACINI, UFMS. |
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Título: |
Agribusiness time series forecasting using perceptually important events. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: LATIN AMERICAN COMPUTING CONFERENCE, 44., 2018, São Paulo. Anais... São Paulo: Mackenzie, 2018. |
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Páginas: |
10 p. |
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Idioma: |
Inglês |
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Notas: |
CLEI 2018. |
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Conteúdo: |
Resumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluation based on price prediction on ten corn futures contracts (derivatives) provides evidence that the proposed approach is promising. MenosResumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluatio... Mostrar Tudo |
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Palavras-Chave: |
Séries temporais. |
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Thesagro: |
Agronegócio. |
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Thesaurus NAL: |
Agribusiness; Risk management. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/189590/1/agribusiness-time.pdf
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Marc: |
LEADER 02297nam a2200217 a 4500
001 2102768
005 2020-01-21
008 2018 bl uuuu u00u1 u #d
100 1 $aRODRIGUES, L. S.
245 $aAgribusiness time series forecasting using perceptually important events.$h[electronic resource]
260 $aIn: LATIN AMERICAN COMPUTING CONFERENCE, 44., 2018, São Paulo. Anais... São Paulo: Mackenzie$c2018
300 $a10 p.
500 $aCLEI 2018.
520 $aResumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluation based on price prediction on ten corn futures contracts (derivatives) provides evidence that the proposed approach is promising.
650 $aAgribusiness
650 $aRisk management
650 $aAgronegócio
653 $aSéries temporais
700 1 $aREZENDE, S. O.
700 1 $aMOURA, M. F.
700 1 $aMARCACINI, R. M.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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