Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena

Detalhes bibliográficos
Autor(a) principal: LIMA JÚNIOR, Leonardo Mendes de
Data de Publicação: 2006
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFRPE
Texto Completo: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5155
Resumo: The aim of this work was to identify the growth phases of leucena (Leucaena leucocephala (Lam.) of Wit.), as a function of time, by using of the multivariate analysis techniques. The data set was obtained through an experiment performed at the Experimental Station of Caruaru-PE of the Institute of Agricultural Research - IPA. Besides 20 actual measures of height along time, additional 17 values were used, obtained by interpolation of best fit curves to the Weibull Model, as well as by linear type interpolation, for two distinct treatments groups: according to presence or absence of organic compound residue. The factor analysis was used to reduce the dimensionality of measured data to three factors with eigenvalues higher than unity, explaining 94.60% and 94.30% of the total variation for the treatments with and without organic compound, respectively, using the varimax rotation. The resulting factor scores were subjected to k-means cluster analysis, using previously selected, number of groups k from 3 to 10. The discriminant analysis was then employed to verify the efficiency of clustering of the best classification groups, which was found to be 95.2% and 95.1% of correct classification for the two treatments. The study it showed that the leucena trees which has received with treatment with organic on average attained greater height. The graphical analysis allowed the comparison among the data treatment with and without organic compound treatment, according to groups, in growth phase.
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spelling FERREIRA, Rinaldo Luiz CaracioloSILVA, José Antônio Aleixo daSTOSIC, BorkoLIRA JÚNIOR, Mário de Andradehttp://lattes.cnpq.br/4069291662106716LIMA JÚNIOR, Leonardo Mendes de2016-08-02T14:44:31Z2006-05-30LIMA JÚNIOR, Leonardo Mendes de. Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena. 2006. 79 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5155The aim of this work was to identify the growth phases of leucena (Leucaena leucocephala (Lam.) of Wit.), as a function of time, by using of the multivariate analysis techniques. The data set was obtained through an experiment performed at the Experimental Station of Caruaru-PE of the Institute of Agricultural Research - IPA. Besides 20 actual measures of height along time, additional 17 values were used, obtained by interpolation of best fit curves to the Weibull Model, as well as by linear type interpolation, for two distinct treatments groups: according to presence or absence of organic compound residue. The factor analysis was used to reduce the dimensionality of measured data to three factors with eigenvalues higher than unity, explaining 94.60% and 94.30% of the total variation for the treatments with and without organic compound, respectively, using the varimax rotation. The resulting factor scores were subjected to k-means cluster analysis, using previously selected, number of groups k from 3 to 10. The discriminant analysis was then employed to verify the efficiency of clustering of the best classification groups, which was found to be 95.2% and 95.1% of correct classification for the two treatments. The study it showed that the leucena trees which has received with treatment with organic on average attained greater height. The graphical analysis allowed the comparison among the data treatment with and without organic compound treatment, according to groups, in growth phase.O objetivo deste trabalho foi identificar as fases de crescimento da leucena (Leucaena leucocephala (Lam.) de Wit.), ao longo do tempo, por meio da utilização das técnicas multivariadas. Os dados foram obtidos de um experimento, localizado na Estação Experimental de Caruaru-PE, que pertence à Empresa Pernambucana de Pesquisa Agropecuária – IPA. Nesse estudo, consideraram-se além das 20 medições em altura (em m) ao longo do tempo, outras mais 17 medições, interpoladas através do Modelo de Weibull e também por interpolação do tipo linear, dividido em 2 grupos distintos de tratamentos: segundo a presença ou não de composto de resíduo orgânico. A análise fatorial permitiu a redução da dimensionalidade das medições, em função de 3 fatores, com autovalores superiores a uma unidade e percentual do total da variação explicada de 94,60% e 94,30%, nos tratamentos sem e com composto orgânico, respectivamente, usando a rotação varimax. Dos fatores retidos, foram obtidos os escores e submetidos à análise de agrupamento do tipo k-médias, sendo o número de grupos escolhidos previamente, para de k de 3 a 10. Os grupos de melhor classificação foram verificados na análise discriminante, que avaliou a eficiência destes agrupamentos, em 95,2% e 95,1% de percentual de classificação correta. O estudo mostrou que as plantas que receberam o composto orgânico tiveram as maiores alturas, em média. A análise gráfica permitiu a comparação entre os dados que tiveram tratamento com composto orgânico e sem composto orgânico, conforme os grupos, em sua fase de crescimento.Submitted by (ana.araujo@ufrpe.br) on 2016-08-02T14:44:31Z No. of bitstreams: 1 Leonardo Mendes de Lima Junior.pdf: 503116 bytes, checksum: b90ee3eab94955ade9a3cdf620bfdf26 (MD5)Made available in DSpace on 2016-08-02T14:44:31Z (GMT). No. of bitstreams: 1 Leonardo Mendes de Lima Junior.pdf: 503116 bytes, checksum: b90ee3eab94955ade9a3cdf620bfdf26 (MD5) Previous issue date: 2006-05-30application/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Biometria e Estatística AplicadaUFRPEBrasilDepartamento de Estatística e InformáticaLeucenaLeucaena leucocephalaCrescimentoAnálise multivariadaAnálise fatorialAnálise de agrupamentoMultivariate analysisFactor analysisCluster analysisCIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICAUtilização de técnicas multivariadas na classificação de fases de crescimento da leucenaThe use of multivariate analysis on classification in leucena (Leucaena leucocephala (Lam.) de Wit.) growth fasesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis768382242446187918600600600-6774555140396120501-5836407828185143517info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPELICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5155/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51ORIGINALLeonardo Mendes de Lima Junior.pdfLeonardo Mendes de Lima Junior.pdfapplication/pdf503116http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5155/2/Leonardo+Mendes+de+Lima+Junior.pdfb90ee3eab94955ade9a3cdf620bfdf26MD52tede2/51552016-08-04 09:24:08.332oai:tede2:tede2/5155Tk9UQTogQ09MT1FVRSBBUVVJIEEgU1VBIFBSw5NQUklBIExJQ0VOw4dBCkVzdGEgbGljZW7Dp2EgZGUgZXhlbXBsbyDDqSBmb3JuZWNpZGEgYXBlbmFzIHBhcmEgZmlucyBpbmZvcm1hdGl2b3MuCgpMSUNFTsOHQSBERSBESVNUUklCVUnDh8ODTyBOw4NPLUVYQ0xVU0lWQQoKQ29tIGEgYXByZXNlbnRhw6fDo28gZGVzdGEgbGljZW7Dp2EsIHZvY8OqIChvIGF1dG9yIChlcykgb3UgbyB0aXR1bGFyIGRvcyBkaXJlaXRvcyBkZSBhdXRvcikgY29uY2VkZSDDoCBVbml2ZXJzaWRhZGUgClhYWCAoU2lnbGEgZGEgVW5pdmVyc2lkYWRlKSBvIGRpcmVpdG8gbsOjby1leGNsdXNpdm8gZGUgcmVwcm9kdXppciwgIHRyYWR1emlyIChjb25mb3JtZSBkZWZpbmlkbyBhYmFpeG8pLCBlL291IApkaXN0cmlidWlyIGEgc3VhIHRlc2Ugb3UgZGlzc2VydGHDp8OjbyAoaW5jbHVpbmRvIG8gcmVzdW1vKSBwb3IgdG9kbyBvIG11bmRvIG5vIGZvcm1hdG8gaW1wcmVzc28gZSBlbGV0csO0bmljbyBlIAplbSBxdWFscXVlciBtZWlvLCBpbmNsdWluZG8gb3MgZm9ybWF0b3Mgw6F1ZGlvIG91IHbDrWRlby4KClZvY8OqIGNvbmNvcmRhIHF1ZSBhIFNpZ2xhIGRlIFVuaXZlcnNpZGFkZSBwb2RlLCBzZW0gYWx0ZXJhciBvIGNvbnRlw7pkbywgdHJhbnNwb3IgYSBzdWEgdGVzZSBvdSBkaXNzZXJ0YcOnw6NvIApwYXJhIHF1YWxxdWVyIG1laW8gb3UgZm9ybWF0byBwYXJhIGZpbnMgZGUgcHJlc2VydmHDp8Ojby4KClZvY8OqIHRhbWLDqW0gY29uY29yZGEgcXVlIGEgU2lnbGEgZGUgVW5pdmVyc2lkYWRlIHBvZGUgbWFudGVyIG1haXMgZGUgdW1hIGPDs3BpYSBhIHN1YSB0ZXNlIG91IApkaXNzZXJ0YcOnw6NvIHBhcmEgZmlucyBkZSBzZWd1cmFuw6dhLCBiYWNrLXVwIGUgcHJlc2VydmHDp8Ojby4KClZvY8OqIGRlY2xhcmEgcXVlIGEgc3VhIHRlc2Ugb3UgZGlzc2VydGHDp8OjbyDDqSBvcmlnaW5hbCBlIHF1ZSB2b2PDqiB0ZW0gbyBwb2RlciBkZSBjb25jZWRlciBvcyBkaXJlaXRvcyBjb250aWRvcyAKbmVzdGEgbGljZW7Dp2EuIFZvY8OqIHRhbWLDqW0gZGVjbGFyYSBxdWUgbyBkZXDDs3NpdG8gZGEgc3VhIHRlc2Ugb3UgZGlzc2VydGHDp8OjbyBuw6NvLCBxdWUgc2VqYSBkZSBzZXUgCmNvbmhlY2ltZW50bywgaW5mcmluZ2UgZGlyZWl0b3MgYXV0b3JhaXMgZGUgbmluZ3XDqW0uCgpDYXNvIGEgc3VhIHRlc2Ugb3UgZGlzc2VydGHDp8OjbyBjb250ZW5oYSBtYXRlcmlhbCBxdWUgdm9jw6ogbsOjbyBwb3NzdWkgYSB0aXR1bGFyaWRhZGUgZG9zIGRpcmVpdG9zIGF1dG9yYWlzLCB2b2PDqiAKZGVjbGFyYSBxdWUgb2J0ZXZlIGEgcGVybWlzc8OjbyBpcnJlc3RyaXRhIGRvIGRldGVudG9yIGRvcyBkaXJlaXRvcyBhdXRvcmFpcyBwYXJhIGNvbmNlZGVyIMOgIFNpZ2xhIGRlIFVuaXZlcnNpZGFkZSAKb3MgZGlyZWl0b3MgYXByZXNlbnRhZG9zIG5lc3RhIGxpY2Vuw6dhLCBlIHF1ZSBlc3NlIG1hdGVyaWFsIGRlIHByb3ByaWVkYWRlIGRlIHRlcmNlaXJvcyBlc3TDoSBjbGFyYW1lbnRlIAppZGVudGlmaWNhZG8gZSByZWNvbmhlY2lkbyBubyB0ZXh0byBvdSBubyBjb250ZcO6ZG8gZGEgdGVzZSBvdSBkaXNzZXJ0YcOnw6NvIG9yYSBkZXBvc2l0YWRhLgoKQ0FTTyBBIFRFU0UgT1UgRElTU0VSVEHDh8ODTyBPUkEgREVQT1NJVEFEQSBURU5IQSBTSURPIFJFU1VMVEFETyBERSBVTSBQQVRST0PDjU5JTyBPVSAKQVBPSU8gREUgVU1BIEFHw4pOQ0lBIERFIEZPTUVOVE8gT1UgT1VUUk8gT1JHQU5JU01PIFFVRSBOw4NPIFNFSkEgQSBTSUdMQSBERSAKVU5JVkVSU0lEQURFLCBWT0PDiiBERUNMQVJBIFFVRSBSRVNQRUlUT1UgVE9ET1MgRSBRVUFJU1FVRVIgRElSRUlUT1MgREUgUkVWSVPDg08gQ09NTyAKVEFNQsOJTSBBUyBERU1BSVMgT0JSSUdBw4fDlUVTIEVYSUdJREFTIFBPUiBDT05UUkFUTyBPVSBBQ09SRE8uCgpBIFNpZ2xhIGRlIFVuaXZlcnNpZGFkZSBzZSBjb21wcm9tZXRlIGEgaWRlbnRpZmljYXIgY2xhcmFtZW50ZSBvIHNldSBub21lIChzKSBvdSBvKHMpIG5vbWUocykgZG8ocykgCmRldGVudG9yKGVzKSBkb3MgZGlyZWl0b3MgYXV0b3JhaXMgZGEgdGVzZSBvdSBkaXNzZXJ0YcOnw6NvLCBlIG7Do28gZmFyw6EgcXVhbHF1ZXIgYWx0ZXJhw6fDo28sIGFsw6ltIGRhcXVlbGFzIApjb25jZWRpZGFzIHBvciBlc3RhIGxpY2Vuw6dhLgo=Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:32:40.979761Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false
dc.title.por.fl_str_mv Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
dc.title.alternative.eng.fl_str_mv The use of multivariate analysis on classification in leucena (Leucaena leucocephala (Lam.) de Wit.) growth fases
title Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
spellingShingle Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
LIMA JÚNIOR, Leonardo Mendes de
Leucena
Leucaena leucocephala
Crescimento
Análise multivariada
Análise fatorial
Análise de agrupamento
Multivariate analysis
Factor analysis
Cluster analysis
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
title_short Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
title_full Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
title_fullStr Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
title_full_unstemmed Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
title_sort Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena
author LIMA JÚNIOR, Leonardo Mendes de
author_facet LIMA JÚNIOR, Leonardo Mendes de
author_role author
dc.contributor.advisor1.fl_str_mv FERREIRA, Rinaldo Luiz Caraciolo
dc.contributor.advisor-co1.fl_str_mv SILVA, José Antônio Aleixo da
dc.contributor.referee1.fl_str_mv STOSIC, Borko
dc.contributor.referee2.fl_str_mv LIRA JÚNIOR, Mário de Andrade
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/4069291662106716
dc.contributor.author.fl_str_mv LIMA JÚNIOR, Leonardo Mendes de
contributor_str_mv FERREIRA, Rinaldo Luiz Caraciolo
SILVA, José Antônio Aleixo da
STOSIC, Borko
LIRA JÚNIOR, Mário de Andrade
dc.subject.por.fl_str_mv Leucena
Leucaena leucocephala
Crescimento
Análise multivariada
Análise fatorial
Análise de agrupamento
topic Leucena
Leucaena leucocephala
Crescimento
Análise multivariada
Análise fatorial
Análise de agrupamento
Multivariate analysis
Factor analysis
Cluster analysis
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
dc.subject.eng.fl_str_mv Multivariate analysis
Factor analysis
Cluster analysis
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
description The aim of this work was to identify the growth phases of leucena (Leucaena leucocephala (Lam.) of Wit.), as a function of time, by using of the multivariate analysis techniques. The data set was obtained through an experiment performed at the Experimental Station of Caruaru-PE of the Institute of Agricultural Research - IPA. Besides 20 actual measures of height along time, additional 17 values were used, obtained by interpolation of best fit curves to the Weibull Model, as well as by linear type interpolation, for two distinct treatments groups: according to presence or absence of organic compound residue. The factor analysis was used to reduce the dimensionality of measured data to three factors with eigenvalues higher than unity, explaining 94.60% and 94.30% of the total variation for the treatments with and without organic compound, respectively, using the varimax rotation. The resulting factor scores were subjected to k-means cluster analysis, using previously selected, number of groups k from 3 to 10. The discriminant analysis was then employed to verify the efficiency of clustering of the best classification groups, which was found to be 95.2% and 95.1% of correct classification for the two treatments. The study it showed that the leucena trees which has received with treatment with organic on average attained greater height. The graphical analysis allowed the comparison among the data treatment with and without organic compound treatment, according to groups, in growth phase.
publishDate 2006
dc.date.issued.fl_str_mv 2006-05-30
dc.date.accessioned.fl_str_mv 2016-08-02T14:44:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv LIMA JÚNIOR, Leonardo Mendes de. Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena. 2006. 79 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife.
dc.identifier.uri.fl_str_mv http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5155
identifier_str_mv LIMA JÚNIOR, Leonardo Mendes de. Utilização de técnicas multivariadas na classificação de fases de crescimento da leucena. 2006. 79 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife.
url http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5155
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language por
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dc.publisher.none.fl_str_mv Universidade Federal Rural de Pernambuco
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Biometria e Estatística Aplicada
dc.publisher.initials.fl_str_mv UFRPE
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Departamento de Estatística e Informática
publisher.none.fl_str_mv Universidade Federal Rural de Pernambuco
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