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Biblioteca(s): |
Embrapa Florestas; Embrapa Uva e Vinho. |
Data corrente: |
05/01/2015 |
Data da última atualização: |
11/03/2019 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
WELKE, J. E.; BARBARÁ, J. A.; ZANUS, M. C.; LAZZAROTTO, M.; ZINI, C. A. |
Afiliação: |
MAURO CELSO ZANUS, CNPUV; MARCELO LAZZAROTTO, CNPF. |
Título: |
Determination of the possible contribution to aroma using odor activity values of volatile compounds of wines analyzed by comprehensive two dimensional gas chromatography. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
In: CONGRESSO LATINOAMERICANO DE CROMATOGRAFIA Y TÉCNICAS AFINES, 15.; CONGRESSO COLOMBIANO DE CROMATOGRAFIA, 7., 2014, Cartagena de Indias, Colombia. Presentaciones en poster: alimientos y bebidas. Bogotá: Sociedad Colombiana de Ciencias Químicas, 2014. |
Páginas: |
p. 205 |
Idioma: |
Inglês |
Conteúdo: |
The aim of this study was to use the HS-SPME-GC × GC/TOFMS to quantify volatile compounds of wines produced with Chardonnay grapes in Serra Gaúcha region, Brazil and determine their possible contribution to aroma through the determination of OAV for each tentatively identified compound. |
Palavras-Chave: |
Chardonnay; Compostos voláteis; Serra Gaúcha; Two-dimensional gas chromatography. |
Thesagro: |
Análise química; Aroma; Cromatografia gasosa; Vinho. |
Thesaurus Nal: |
volatile compounds. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/114762/1/ZANUS-Colacro2014-p205.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/116375/1/2014-RAC-MarceloL-COLACRO-Determination.pdf
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Marc: |
LEADER 01378nam a2200277 a 4500 001 2004245 005 2019-03-11 008 2014 bl uuuu u00u1 u #d 100 1 $aWELKE, J. E. 245 $aDetermination of the possible contribution to aroma using odor activity values of volatile compounds of wines analyzed by comprehensive two dimensional gas chromatography.$h[electronic resource] 260 $aIn: CONGRESSO LATINOAMERICANO DE CROMATOGRAFIA Y TÉCNICAS AFINES, 15.; CONGRESSO COLOMBIANO DE CROMATOGRAFIA, 7., 2014, Cartagena de Indias, Colombia. Presentaciones en poster: alimientos y bebidas. Bogotá: Sociedad Colombiana de Ciencias Químicas$c2014 300 $ap. 205 520 $aThe aim of this study was to use the HS-SPME-GC × GC/TOFMS to quantify volatile compounds of wines produced with Chardonnay grapes in Serra Gaúcha region, Brazil and determine their possible contribution to aroma through the determination of OAV for each tentatively identified compound. 650 $avolatile compounds 650 $aAnálise química 650 $aAroma 650 $aCromatografia gasosa 650 $aVinho 653 $aChardonnay 653 $aCompostos voláteis 653 $aSerra Gaúcha 653 $aTwo-dimensional gas chromatography 700 1 $aBARBARÁ, J. A. 700 1 $aZANUS, M. C. 700 1 $aLAZZAROTTO, M. 700 1 $aZINI, C. A.
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Registro original: |
Embrapa Uva e Vinho (CNPUV) |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
Data corrente: |
18/09/2014 |
Data da última atualização: |
02/06/2017 |
Autoria: |
FERRAZ, P. F. P.; YANAGI JUNIOR, T.; HERNÁNDEZ JULIO, Y. F.; CASTRO, J. de O.; GATES, R. S.; REIS, G. M.; CAMPOS, A. T. |
Afiliação: |
PATRICIA FERREIRA PONCIANO FERRAZ, UFLA; TADAYUKI YANAGI JUNIOR, UFLA; FABIÁN HERNÁNDEZ JULIO, UFLA; JAQUELINE DE OLIVEIRA CASTRO, UFLA; RICHARD STEPHEN GATES, University of Illinois; GREGORY MURAD REIS, UFLA; ALESSANDRO TORRES CAMPOS, UFLA. |
Título: |
Predicting chick body mass by artificial intelligence-based models. |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 7, p. 559-568, jul. 2014. |
Idioma: |
Inglês |
Notas: |
Título em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial. |
Conteúdo: |
The objective of this work was to develop, validate, and compare 190 artificial intelligence‑based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside our climate‑controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21‑day‑old hicks) ? with the variables dry‑bulb air temperature, duration of thermal stress (days), chick ageb (days), and the daily body mass of chicks ? was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro‑fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The NNs enable the simulation of different scenarios, which can assist in managerial decision‑making, and they can be embedded in the heating control system. |
Palavras-Chave: |
Artificial neural networks; Modeling; Neuro-fuzzy network; Thermal comfort. |
Thesaurus NAL: |
Animal welfare. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/108680/1/Predicting-chick-body.pdf
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Marc: |
LEADER 01954naa a2200265 a 4500 001 1995322 005 2017-06-02 008 2014 bl uuuu u00u1 u #d 100 1 $aFERRAZ, P. F. P. 245 $aPredicting chick body mass by artificial intelligence-based models. 260 $c2014 500 $aTítulo em português: Predição da massa corporal de pintinhos por meio de modelos baseados em inteligência artificial. 520 $aThe objective of this work was to develop, validate, and compare 190 artificial intelligence‑based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside our climate‑controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21‑day‑old hicks) ? with the variables dry‑bulb air temperature, duration of thermal stress (days), chick ageb (days), and the daily body mass of chicks ? was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro‑fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The NNs enable the simulation of different scenarios, which can assist in managerial decision‑making, and they can be embedded in the heating control system. 650 $aAnimal welfare 653 $aArtificial neural networks 653 $aModeling 653 $aNeuro-fuzzy network 653 $aThermal comfort 700 1 $aYANAGI JUNIOR, T. 700 1 $aHERNÁNDEZ JULIO, Y. F. 700 1 $aCASTRO, J. de O. 700 1 $aGATES, R. S. 700 1 $aREIS, G. M. 700 1 $aCAMPOS, A. T. 773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 49, n. 7, p. 559-568, jul. 2014.
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