Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica)
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.2013.00449 http://hdl.handle.net/11449/113418 |
Resumo: | Plant ionomes and soil nutrients are commonly diagnosed in agronomy using concentration and nutrient ratio ranges. However, both diagnoses are biased by redundancy of information, subcompositional incoherence and non-normal distribution inherent to compositional data, potentially leading to conflicting results and wrong inferences. Our objective was to present an unbiased statistical approach of plant nutrient diagnosis using a balance concept and mango (Mangifera indica) as test crop. We collected foliar samples at flowering stage in 175 mango orchards. The ionomes comprised 11 nutrients (S, N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe). Traditional multivariate methods were found to be biased. lonomes were thus represented by unbiased balances computed as isometric log ratios (ilr). Soil fertility attributes (pH and bioavailable nutrients) were transformed into balances to conduct discriminant analysis. The orchards differed more from genotype than soil nutrient signatures. A customized receiver operating characteristic (ROC) iterative procedure was developed to classify tissue ionomes between balanced/misbalanced and high/low-yielders. The ROC partitioning procedure showed that the critical Mahalanobis distance of 4.08 separating balanced from imbalanced specimens about yield cut-off of 128.5 kg fruit tree(-1) proved to be a fairly informative test (area under curve = 0.84-0.92). The [P vertical bar N,S] and [Mn vertical bar Cu,Zn] balances were found to be potential sources of misbalance in the less productive orchards, and should thus be further investigated in field experiments. We propose using a coherent pan balance diagnostic method with median ilr values of top yielders centered at fulcrums of a mobile and the critical Mahalanobis distance as a guide for global nutrient balance. Nutrient concentrations in weighing pans assisted appreciating nutrients as relative shortage, adequacy or excess in balances. |
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Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica)Plant nutritionionomicscrop managementmangocompositional data analysisPlant ionomes and soil nutrients are commonly diagnosed in agronomy using concentration and nutrient ratio ranges. However, both diagnoses are biased by redundancy of information, subcompositional incoherence and non-normal distribution inherent to compositional data, potentially leading to conflicting results and wrong inferences. Our objective was to present an unbiased statistical approach of plant nutrient diagnosis using a balance concept and mango (Mangifera indica) as test crop. We collected foliar samples at flowering stage in 175 mango orchards. The ionomes comprised 11 nutrients (S, N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe). Traditional multivariate methods were found to be biased. lonomes were thus represented by unbiased balances computed as isometric log ratios (ilr). Soil fertility attributes (pH and bioavailable nutrients) were transformed into balances to conduct discriminant analysis. The orchards differed more from genotype than soil nutrient signatures. A customized receiver operating characteristic (ROC) iterative procedure was developed to classify tissue ionomes between balanced/misbalanced and high/low-yielders. The ROC partitioning procedure showed that the critical Mahalanobis distance of 4.08 separating balanced from imbalanced specimens about yield cut-off of 128.5 kg fruit tree(-1) proved to be a fairly informative test (area under curve = 0.84-0.92). The [P vertical bar N,S] and [Mn vertical bar Cu,Zn] balances were found to be potential sources of misbalance in the less productive orchards, and should thus be further investigated in field experiments. We propose using a coherent pan balance diagnostic method with median ilr values of top yielders centered at fulcrums of a mobile and the critical Mahalanobis distance as a guide for global nutrient balance. Nutrient concentrations in weighing pans assisted appreciating nutrients as relative shortage, adequacy or excess in balances.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Natural Sciences and Engineering Council of CanadaUniv Laval, ERSAM, Dept Soils & Agrifood Engn, Quebec City, PQ G1V 0A6, CanadaUniv Estadual Paulista, Dept Agron, Registro, BrazilUniv Estadual Paulista, Dept Solos & Adubos, Jaboticabal, BrazilUniv Estadual Paulista, Dept Agron, Registro, BrazilUniv Estadual Paulista, Dept Solos & Adubos, Jaboticabal, BrazilNatural Sciences and Engineering Council of CanadaDG-2254Natural Sciences and Engineering Council of CanadaCRDPJ 385199-09Frontiers Research FoundationUniv LavalUniversidade Estadual Paulista (Unesp)Parent, Serge-EtienneParent, Leon E.Rozane, Danilo Eduardo [UNESP]Natale, William [UNESP]2014-12-03T13:11:41Z2014-12-03T13:11:41Z2013-11-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article12application/pdfhttp://dx.doi.org/10.3389/fpls.2013.00449Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 12 p., 2013.1664-462Xhttp://hdl.handle.net/11449/11341810.3389/fpls.2013.00449WOS:000331445300001WOS000331445300001.pdf0618605154638494Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengFrontiers In Plant Science3.678info:eu-repo/semantics/openAccess2024-05-03T13:20:21Zoai:repositorio.unesp.br:11449/113418Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-05-03T13:20:21Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
title |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
spellingShingle |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) Parent, Serge-Etienne Plant nutrition ionomics crop management mango compositional data analysis |
title_short |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
title_full |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
title_fullStr |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
title_full_unstemmed |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
title_sort |
Plant iononne diagnosis using sound balances: case study with mango (Mangifera Indica) |
author |
Parent, Serge-Etienne |
author_facet |
Parent, Serge-Etienne Parent, Leon E. Rozane, Danilo Eduardo [UNESP] Natale, William [UNESP] |
author_role |
author |
author2 |
Parent, Leon E. Rozane, Danilo Eduardo [UNESP] Natale, William [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Univ Laval Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Parent, Serge-Etienne Parent, Leon E. Rozane, Danilo Eduardo [UNESP] Natale, William [UNESP] |
dc.subject.por.fl_str_mv |
Plant nutrition ionomics crop management mango compositional data analysis |
topic |
Plant nutrition ionomics crop management mango compositional data analysis |
description |
Plant ionomes and soil nutrients are commonly diagnosed in agronomy using concentration and nutrient ratio ranges. However, both diagnoses are biased by redundancy of information, subcompositional incoherence and non-normal distribution inherent to compositional data, potentially leading to conflicting results and wrong inferences. Our objective was to present an unbiased statistical approach of plant nutrient diagnosis using a balance concept and mango (Mangifera indica) as test crop. We collected foliar samples at flowering stage in 175 mango orchards. The ionomes comprised 11 nutrients (S, N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe). Traditional multivariate methods were found to be biased. lonomes were thus represented by unbiased balances computed as isometric log ratios (ilr). Soil fertility attributes (pH and bioavailable nutrients) were transformed into balances to conduct discriminant analysis. The orchards differed more from genotype than soil nutrient signatures. A customized receiver operating characteristic (ROC) iterative procedure was developed to classify tissue ionomes between balanced/misbalanced and high/low-yielders. The ROC partitioning procedure showed that the critical Mahalanobis distance of 4.08 separating balanced from imbalanced specimens about yield cut-off of 128.5 kg fruit tree(-1) proved to be a fairly informative test (area under curve = 0.84-0.92). The [P vertical bar N,S] and [Mn vertical bar Cu,Zn] balances were found to be potential sources of misbalance in the less productive orchards, and should thus be further investigated in field experiments. We propose using a coherent pan balance diagnostic method with median ilr values of top yielders centered at fulcrums of a mobile and the critical Mahalanobis distance as a guide for global nutrient balance. Nutrient concentrations in weighing pans assisted appreciating nutrients as relative shortage, adequacy or excess in balances. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-11-12 2014-12-03T13:11:41Z 2014-12-03T13:11:41Z |
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.2013.00449 Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 12 p., 2013. 1664-462X http://hdl.handle.net/11449/113418 10.3389/fpls.2013.00449 WOS:000331445300001 WOS000331445300001.pdf 0618605154638494 |
url |
http://dx.doi.org/10.3389/fpls.2013.00449 http://hdl.handle.net/11449/113418 |
identifier_str_mv |
Frontiers In Plant Science. Lausanne: Frontiers Research Foundation, v. 4, 12 p., 2013. 1664-462X 10.3389/fpls.2013.00449 WOS:000331445300001 WOS000331445300001.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 |
12 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 |
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1799965441641152512 |