Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead

Detalhes bibliográficos
Autor(a) principal: Fontes, Maurício P. F.
Data de Publicação: 2017
Outros Autores: Soares, Liliane C., Alves, Júnia de O., Linhares, Lucília A., Egreja Filho, Fernando B.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: https://doi.org/10.1016/j.microc.2017.03.028
http://www.locus.ufv.br/handle/123456789/22121
Resumo: One of the most important components of the soil vulnerability to heavy metals is related to a situation where the critical load of the soil be exceeded, causing the releasing of retained metals. Soil vulnerability to a metal is a function mainly of the interaction forces between the metal and the soil matrix, which depends on the physical and chemical soil characteristics. This study aims to classify the soils as vulnerable or non-vulnerable for lead as a function of the soil characteristics using Partial Least Squares Discriminant Analysis (PLS-DA). The vulnerability was assessed by the determination of available fraction metal (AF), after a treatment with Pb^2 +. Percent AF, evaluated by extraction with KNO3 solution, was used as reference only to separate the samples into two classes (vulnerable and non-vulnerable) before the model construction. The data about soil characteristics were treated by PLS-DA aiming to discriminate the above-mentioned classes, i.e. vulnerable and non-vulnerable. The employed PLS-DA model was built with 20 and 10 samples for the training and test sets, respectively, and in all cases they were properly separated. The developed methodology shows high sensitivities (rate of true positives) and specificities (rate of true negatives) for the two classes. Finally, it can be envisaged that this approach has potential to be applied in classification of the soil vulnerability to lead, just based on soil characteristics.
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spelling Fontes, Maurício P. F.Soares, Liliane C.Alves, Júnia de O.Linhares, Lucília A.Egreja Filho, Fernando B.2018-10-04T10:47:39Z2018-10-04T10:47:39Z2017-070026265Xhttps://doi.org/10.1016/j.microc.2017.03.028http://www.locus.ufv.br/handle/123456789/22121One of the most important components of the soil vulnerability to heavy metals is related to a situation where the critical load of the soil be exceeded, causing the releasing of retained metals. Soil vulnerability to a metal is a function mainly of the interaction forces between the metal and the soil matrix, which depends on the physical and chemical soil characteristics. This study aims to classify the soils as vulnerable or non-vulnerable for lead as a function of the soil characteristics using Partial Least Squares Discriminant Analysis (PLS-DA). The vulnerability was assessed by the determination of available fraction metal (AF), after a treatment with Pb^2 +. Percent AF, evaluated by extraction with KNO3 solution, was used as reference only to separate the samples into two classes (vulnerable and non-vulnerable) before the model construction. The data about soil characteristics were treated by PLS-DA aiming to discriminate the above-mentioned classes, i.e. vulnerable and non-vulnerable. The employed PLS-DA model was built with 20 and 10 samples for the training and test sets, respectively, and in all cases they were properly separated. The developed methodology shows high sensitivities (rate of true positives) and specificities (rate of true negatives) for the two classes. Finally, it can be envisaged that this approach has potential to be applied in classification of the soil vulnerability to lead, just based on soil characteristics.engMicrochemical Journalv. 133, p. 258- 264, jul. 2017Elsevier B.V.info:eu-repo/semantics/openAccessChemometricsSoil chemistryWeathered soilsPbAvailable metalVulnerability of tropical soils to heavy metals: a PLS-DA classification model for leadinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdftexto completoapplication/pdf645962https://locus.ufv.br//bitstream/123456789/22121/1/artigo.pdf8725f1f03c0401a564c8bea2deb3ededMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/22121/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg6127https://locus.ufv.br//bitstream/123456789/22121/3/artigo.pdf.jpga188782f04f3e8883255377ac8db4883MD53123456789/221212018-10-04 23:00:37.206oai:locus.ufv.br:123456789/22121Tk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-10-05T02:00:37LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
title Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
spellingShingle Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
Fontes, Maurício P. F.
Chemometrics
Soil chemistry
Weathered soils
Pb
Available metal
title_short Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
title_full Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
title_fullStr Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
title_full_unstemmed Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
title_sort Vulnerability of tropical soils to heavy metals: a PLS-DA classification model for lead
author Fontes, Maurício P. F.
author_facet Fontes, Maurício P. F.
Soares, Liliane C.
Alves, Júnia de O.
Linhares, Lucília A.
Egreja Filho, Fernando B.
author_role author
author2 Soares, Liliane C.
Alves, Júnia de O.
Linhares, Lucília A.
Egreja Filho, Fernando B.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Fontes, Maurício P. F.
Soares, Liliane C.
Alves, Júnia de O.
Linhares, Lucília A.
Egreja Filho, Fernando B.
dc.subject.pt-BR.fl_str_mv Chemometrics
Soil chemistry
Weathered soils
Pb
Available metal
topic Chemometrics
Soil chemistry
Weathered soils
Pb
Available metal
description One of the most important components of the soil vulnerability to heavy metals is related to a situation where the critical load of the soil be exceeded, causing the releasing of retained metals. Soil vulnerability to a metal is a function mainly of the interaction forces between the metal and the soil matrix, which depends on the physical and chemical soil characteristics. This study aims to classify the soils as vulnerable or non-vulnerable for lead as a function of the soil characteristics using Partial Least Squares Discriminant Analysis (PLS-DA). The vulnerability was assessed by the determination of available fraction metal (AF), after a treatment with Pb^2 +. Percent AF, evaluated by extraction with KNO3 solution, was used as reference only to separate the samples into two classes (vulnerable and non-vulnerable) before the model construction. The data about soil characteristics were treated by PLS-DA aiming to discriminate the above-mentioned classes, i.e. vulnerable and non-vulnerable. The employed PLS-DA model was built with 20 and 10 samples for the training and test sets, respectively, and in all cases they were properly separated. The developed methodology shows high sensitivities (rate of true positives) and specificities (rate of true negatives) for the two classes. Finally, it can be envisaged that this approach has potential to be applied in classification of the soil vulnerability to lead, just based on soil characteristics.
publishDate 2017
dc.date.issued.fl_str_mv 2017-07
dc.date.accessioned.fl_str_mv 2018-10-04T10:47:39Z
dc.date.available.fl_str_mv 2018-10-04T10:47:39Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv https://doi.org/10.1016/j.microc.2017.03.028
http://www.locus.ufv.br/handle/123456789/22121
dc.identifier.issn.none.fl_str_mv 0026265X
identifier_str_mv 0026265X
url https://doi.org/10.1016/j.microc.2017.03.028
http://www.locus.ufv.br/handle/123456789/22121
dc.language.iso.fl_str_mv eng
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dc.relation.ispartofseries.pt-BR.fl_str_mv v. 133, p. 258- 264, jul. 2017
dc.rights.driver.fl_str_mv Elsevier B.V.
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