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Registro Completo |
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Biblioteca(s): |
Embrapa Meio-Norte. |
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Data corrente: |
26/01/2012 |
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Data da última atualização: |
26/01/2012 |
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Autoria: |
WITHAM, F. H.; BLAYDES, D. F.; DEVLIN, R. M. |
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Título: |
Experiments in plant physiology. |
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Ano de publicação: |
1971 |
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Fonte/Imprenta: |
New York: Van Nostrand, 1971. |
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Páginas: |
245 p. |
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Idioma: |
Inglês |
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Conteúdo: |
Plant nutrition and mineral deficiencies. Macroelements in plant ash. The expansion of bean disks by cobaltous and nickelous ions. The estimation of total soluble carbohydrate in cauliflower tissue. Simple tests for carbohydrates. The separation of sugars by paper chromatography. Isolation and properties of starch. Paper chromatography of nucleic acids and the ultraviolet. Absorption spectrum of ribonucleic acid or deoxyribonucleic acid. |
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Thesagro: |
Crescimento; Fisiologia Vegetal; Fotossíntese; Germinação; Semente; Tecido. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00957nam a2200217 a 4500
001 1913555
005 2012-01-26
008 1971 bl uuuu 00u1 u #d
100 1 $aWITHAM, F. H.
245 $aExperiments in plant physiology.
260 $aNew York: Van Nostrand$c1971
300 $a245 p.
520 $aPlant nutrition and mineral deficiencies. Macroelements in plant ash. The expansion of bean disks by cobaltous and nickelous ions. The estimation of total soluble carbohydrate in cauliflower tissue. Simple tests for carbohydrates. The separation of sugars by paper chromatography. Isolation and properties of starch. Paper chromatography of nucleic acids and the ultraviolet. Absorption spectrum of ribonucleic acid or deoxyribonucleic acid.
650 $aCrescimento
650 $aFisiologia Vegetal
650 $aFotossíntese
650 $aGerminação
650 $aSemente
650 $aTecido
700 1 $aBLAYDES, D. F.
700 1 $aDEVLIN, R. M.
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Registro original: |
Embrapa Meio-Norte (CPAMN) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/10/2010 |
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Data da última atualização: |
23/05/2011 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
ROMANI, L. A. S.; ÁVILA, A. M. H.; ZULLO JÚNIOR, J.; TRAINA JÚNIOR, C.; TRAINA, A. J. M. |
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Afiliação: |
LUCIANA ALVIM SANTOS ROMANI, CNPTIA; ANA MARIA H. ÁVILA, CEPAGRI/UNICAMP; JURANDIR ZULLO JÚNIOR, CEPAGRI/UNICAMP; CAETANO TRAINA JÚNIOR, ICMC/USP; AGMA J. M. TRAINA, ICMC/USP. |
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Título: |
Mining relevant and extreme patterns on climate time series with CLIPSMiner. |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
Journal of Information and Data Management, Belo Horizonte, v. 1, n. 2, p. 245-260. June 2010. |
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Idioma: |
Inglês |
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Conteúdo: |
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of natural hazards. Another problem of changes in the Earth's climate is its impact in the agriculture production. In this scenario, application of statistical models as well as development of new methods become very important to aid in the analyses of climate from ground-based stations and outputs of forecasting models. Additionally, remote sensing images have been used to improve the monitoring of crop yields. In this context we propose a new technique to identify extreme values in climate time series and to correlate climate and remote sensing data in order to improve agricultural monitoring. Accordingly, this paper presents a new unsupervised algorithm, called CLIPSMiner (CLImate PatternS Miner) that works on multiple time series of continuous data, identifying relevant patterns or extreme ones according to a relevance factor, which can be tuned by the user. Results show that CLIPSMiner detects, as expected, patterns that are known in climatology, indicating the correctness and feasibility of the proposed algorithm. Moreover, patterns detected using the highest relevance factor is coincident with extreme phenomena. Furthermore, series correlations detected by the algorithm show a relation between agroclimatic and vegetation indices, which confirms the agrometeorologists' expectations. |
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Palavras-Chave: |
Algoritmo CLIPSMiner; Data mining; Mineração de dados. |
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Thesagro: |
Sensoriamento Remoto. |
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Thesaurus NAL: |
Climate change; Remote sensing. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/23218/1/39-220-2-PB.pdf
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Marc: |
LEADER 02239naa a2200241 a 4500
001 1863850
005 2011-05-23
008 2010 bl uuuu u00u1 u #d
100 1 $aROMANI, L. A. S.
245 $aMining relevant and extreme patterns on climate time series with CLIPSMiner.$h[electronic resource]
260 $c2010
520 $aOne of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of natural hazards. Another problem of changes in the Earth's climate is its impact in the agriculture production. In this scenario, application of statistical models as well as development of new methods become very important to aid in the analyses of climate from ground-based stations and outputs of forecasting models. Additionally, remote sensing images have been used to improve the monitoring of crop yields. In this context we propose a new technique to identify extreme values in climate time series and to correlate climate and remote sensing data in order to improve agricultural monitoring. Accordingly, this paper presents a new unsupervised algorithm, called CLIPSMiner (CLImate PatternS Miner) that works on multiple time series of continuous data, identifying relevant patterns or extreme ones according to a relevance factor, which can be tuned by the user. Results show that CLIPSMiner detects, as expected, patterns that are known in climatology, indicating the correctness and feasibility of the proposed algorithm. Moreover, patterns detected using the highest relevance factor is coincident with extreme phenomena. Furthermore, series correlations detected by the algorithm show a relation between agroclimatic and vegetation indices, which confirms the agrometeorologists' expectations.
650 $aClimate change
650 $aRemote sensing
650 $aSensoriamento Remoto
653 $aAlgoritmo CLIPSMiner
653 $aData mining
653 $aMineração de dados
700 1 $aÁVILA, A. M. H.
700 1 $aZULLO JÚNIOR, J.
700 1 $aTRAINA JÚNIOR, C.
700 1 $aTRAINA, A. J. M.
773 $tJournal of Information and Data Management, Belo Horizonte$gv. 1, n. 2, p. 245-260. June 2010.
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Embrapa Agricultura Digital (CNPTIA) |
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