The plant ionome revisited by the nutrient balance concept
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3389/fpls.2013.00039 http://hdl.handle.net/11449/112006 |
Resumo: | Tissue analysis is commonly used in ecology and agronomy to portray plant nutrient signatures. Nutrient concentration data, or ionomes, belong to the compositional data class, i.e., multivariate data that are proportions of some whole, hence carrying important numerical properties. Statistics computed across raw or ordinary log-transformed nutrient data are intrinsically biased, hence possibly leading to wrong inferences. Our objective was to present a sound and robust approach based on a novel nutrient balance concept to classify plant ionomes. We analyzed leaf N, R K, Ca, and Mg of two wild and six domesticated fruit species from Canada, Brazil, and New Zealand sampled during reproductive stages. Nutrient concentrations were (1) analyzed without transformation, (2) ordinary log-transformed as commonly but incorrectly applied in practice, (3) additive log-ratio (air) transformed as surrogate to stoichiometric rules, and (4) converted to isometric log-ratios OH arranged as sound nutrient balance variables. Raw concentration and ordinary log transformation both led to biased multivariate analysis due to redundancy between interacting nutrients. The air- and ilr-transformed data provided unbiased discriminant analyses of plant ionomes, where wild and domesticated species formed distinct groups and the ionomes of species and cultivars were differentiated without numerical bias. The ilr nutrient balance concept is preferable to air, because the ilr technique projects the most important interactions between nutrients into a convenient Euclidean space.This novel numerical approach allows rectifying historical biases and supervising phenotypic plasticity in plant nutrition studies. |
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The plant ionome revisited by the nutrient balance conceptcompositional data analysisionome classificationnutrient interactionsnumerical biasesisometric log-ratioPlant nutritionTissue analysis is commonly used in ecology and agronomy to portray plant nutrient signatures. Nutrient concentration data, or ionomes, belong to the compositional data class, i.e., multivariate data that are proportions of some whole, hence carrying important numerical properties. Statistics computed across raw or ordinary log-transformed nutrient data are intrinsically biased, hence possibly leading to wrong inferences. Our objective was to present a sound and robust approach based on a novel nutrient balance concept to classify plant ionomes. We analyzed leaf N, R K, Ca, and Mg of two wild and six domesticated fruit species from Canada, Brazil, and New Zealand sampled during reproductive stages. Nutrient concentrations were (1) analyzed without transformation, (2) ordinary log-transformed as commonly but incorrectly applied in practice, (3) additive log-ratio (air) transformed as surrogate to stoichiometric rules, and (4) converted to isometric log-ratios OH arranged as sound nutrient balance variables. Raw concentration and ordinary log transformation both led to biased multivariate analysis due to redundancy between interacting nutrients. The air- and ilr-transformed data provided unbiased discriminant analyses of plant ionomes, where wild and domesticated species formed distinct groups and the ionomes of species and cultivars were differentiated without numerical bias. The ilr nutrient balance concept is preferable to air, because the ilr technique projects the most important interactions between nutrients into a convenient Euclidean space.This novel numerical approach allows rectifying historical biases and supervising phenotypic plasticity in plant nutrition studies.Natural Sciences and Engineering Council of CanadaFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Spanish Ministry of Education and ScienceAgencia de Gestio d'Ajuts Universitaris i de Recerca of the Generalitat de CatalunyaUniv Laval, Dept Soils & Agrifood Engn, Equipe Rech Sols Agr & Miniers, Quebec City, PQ G1V 0A6, CanadaUniv Politecn Cataluna, Dept Appl Math 3, Barcelona, SpainUniv Estadual Paulista, Dept Agron, Sao Paulo, BrazilUniv Estadual Paulista, Dept Solos & Adubos, Sao Paulo, BrazilUniv Laval, Dept Biol, Ctr Etude Foret, Quebec City, PQ G1V 0A6, CanadaCtr Rech Les Buissons, Pointe Aux Outardes, PQ, CanadaAgr & Agri Food Canada, Normandin, PQ, CanadaCtr Citricultura Sylvio Moreira IAC, Sao Paulo, BrazilBio Soil & Crop Ltd, Tauranga, New ZealandUniv Estadual Paulista, Dept Agron, Sao Paulo, BrazilUniv Estadual Paulista, Dept Solos & Adubos, Sao Paulo, BrazilNatural Sciences and Engineering Council of CanadaCG-2254Natural Sciences and Engineering Council of CanadaCRDPJ 385199-09Spanish Ministry of Education and ScienceMTM2009-13272Spanish Ministry of Education and ScienceC5D2006-00032Agencia de Gestio d'Ajuts Universitaris i de Recerca of the Generalitat de Catalunya20095GR424Frontiers Research FoundationUniv LavalUniv Politecn CatalunaUniversidade Estadual Paulista (Unesp)Ctr Rech Les BuissonsAgr & Agri Food CanadaCtr Citricultura Sylvio Moreira IACBio Soil & Crop LtdParent, Serge-EtienneParent, Leon EtienneJose Egozcue, JuanRozane, Danilo-Eduardo [UNESP]Hernandes, Amanda [UNESP]Lapointe, LineHebert-Gentile, ValerieNaess, KristineMarchand, SebastienLafond, JeanMattos, DirceuBarlow, PhilipNatale, William [UNESP]2014-12-03T13:09:10Z2014-12-03T13:09:10Z2013-03-22info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article10application/pdfhttp://dx.doi.org/10.3389/fpls.2013.00039Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 10 p., 2013.1664-462Xhttp://hdl.handle.net/11449/11200610.3389/fpls.2013.00039WOS:000329582300001WOS000329582300001.pdf0618605154638494Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFrontiers In Plant Science3.678info:eu-repo/semantics/openAccess2024-06-07T14:23:54Zoai:repositorio.unesp.br:11449/112006Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:55:11.540254Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
The plant ionome revisited by the nutrient balance concept |
title |
The plant ionome revisited by the nutrient balance concept |
spellingShingle |
The plant ionome revisited by the nutrient balance concept Parent, Serge-Etienne compositional data analysis ionome classification nutrient interactions numerical biases isometric log-ratio Plant nutrition |
title_short |
The plant ionome revisited by the nutrient balance concept |
title_full |
The plant ionome revisited by the nutrient balance concept |
title_fullStr |
The plant ionome revisited by the nutrient balance concept |
title_full_unstemmed |
The plant ionome revisited by the nutrient balance concept |
title_sort |
The plant ionome revisited by the nutrient balance concept |
author |
Parent, Serge-Etienne |
author_facet |
Parent, Serge-Etienne Parent, Leon Etienne Jose Egozcue, Juan Rozane, Danilo-Eduardo [UNESP] Hernandes, Amanda [UNESP] Lapointe, Line Hebert-Gentile, Valerie Naess, Kristine Marchand, Sebastien Lafond, Jean Mattos, Dirceu Barlow, Philip Natale, William [UNESP] |
author_role |
author |
author2 |
Parent, Leon Etienne Jose Egozcue, Juan Rozane, Danilo-Eduardo [UNESP] Hernandes, Amanda [UNESP] Lapointe, Line Hebert-Gentile, Valerie Naess, Kristine Marchand, Sebastien Lafond, Jean Mattos, Dirceu Barlow, Philip Natale, William [UNESP] |
author2_role |
author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Univ Laval Univ Politecn Cataluna Universidade Estadual Paulista (Unesp) Ctr Rech Les Buissons Agr & Agri Food Canada Ctr Citricultura Sylvio Moreira IAC Bio Soil & Crop Ltd |
dc.contributor.author.fl_str_mv |
Parent, Serge-Etienne Parent, Leon Etienne Jose Egozcue, Juan Rozane, Danilo-Eduardo [UNESP] Hernandes, Amanda [UNESP] Lapointe, Line Hebert-Gentile, Valerie Naess, Kristine Marchand, Sebastien Lafond, Jean Mattos, Dirceu Barlow, Philip Natale, William [UNESP] |
dc.subject.por.fl_str_mv |
compositional data analysis ionome classification nutrient interactions numerical biases isometric log-ratio Plant nutrition |
topic |
compositional data analysis ionome classification nutrient interactions numerical biases isometric log-ratio Plant nutrition |
description |
Tissue analysis is commonly used in ecology and agronomy to portray plant nutrient signatures. Nutrient concentration data, or ionomes, belong to the compositional data class, i.e., multivariate data that are proportions of some whole, hence carrying important numerical properties. Statistics computed across raw or ordinary log-transformed nutrient data are intrinsically biased, hence possibly leading to wrong inferences. Our objective was to present a sound and robust approach based on a novel nutrient balance concept to classify plant ionomes. We analyzed leaf N, R K, Ca, and Mg of two wild and six domesticated fruit species from Canada, Brazil, and New Zealand sampled during reproductive stages. Nutrient concentrations were (1) analyzed without transformation, (2) ordinary log-transformed as commonly but incorrectly applied in practice, (3) additive log-ratio (air) transformed as surrogate to stoichiometric rules, and (4) converted to isometric log-ratios OH arranged as sound nutrient balance variables. Raw concentration and ordinary log transformation both led to biased multivariate analysis due to redundancy between interacting nutrients. The air- and ilr-transformed data provided unbiased discriminant analyses of plant ionomes, where wild and domesticated species formed distinct groups and the ionomes of species and cultivars were differentiated without numerical bias. The ilr nutrient balance concept is preferable to air, because the ilr technique projects the most important interactions between nutrients into a convenient Euclidean space.This novel numerical approach allows rectifying historical biases and supervising phenotypic plasticity in plant nutrition studies. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-03-22 2014-12-03T13:09:10Z 2014-12-03T13:09:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3389/fpls.2013.00039 Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 10 p., 2013. 1664-462X http://hdl.handle.net/11449/112006 10.3389/fpls.2013.00039 WOS:000329582300001 WOS000329582300001.pdf 0618605154638494 |
url |
http://dx.doi.org/10.3389/fpls.2013.00039 http://hdl.handle.net/11449/112006 |
identifier_str_mv |
Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 10 p., 2013. 1664-462X 10.3389/fpls.2013.00039 WOS:000329582300001 WOS000329582300001.pdf 0618605154638494 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Frontiers In Plant Science 3.678 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
10 application/pdf |
dc.publisher.none.fl_str_mv |
Frontiers Research Foundation |
publisher.none.fl_str_mv |
Frontiers Research Foundation |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129264239771648 |