Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index

Detalhes bibliográficos
Autor(a) principal: Parent, Léon Etienne
Data de Publicação: 2009
Outros Autores: Natale, William [UNESP], Ziadi, Noura
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.4141/cjss08050
http://hdl.handle.net/11449/231886
Resumo: Compositional nutrient diagnosis (CND) provides a plant nutrient imbalance index (CND - r2) with assumed χ2 distribution. The Mahalanobis distance D2, which detects outliers in compositional data sets, also has a χ2 distribution. The objective of this paper was to compare D2 and CND - r2 nutrient imbalance indexes in corn (Zea mays L.). We measured grain yield as well as N, P, K, Ca, Mg, Cu, Fe, Mn, and Zn concentrations in the ear leaf at silk stage for 210 calibration sites in the St. Lawrence Lowlands [2300-2700 corn thermal units (CTU)] as well as 30 phosphorus (2300-2700 CTU; 10 sites) and 10 nitrogen (1900-2100 CTU; one site) replicated fertilizer treatments for validation. We derived CND norms as mean, standard deviation, and the inverse covariance matrix of centred log ratios (clr) for high yielding specimens (≥9.0 Mg grain ha-1 at 150 g H2O kg-1 moisture content) in the 2300-2700 CTU zone. Using χ2 = 17 (P <0.05) with nine degrees of freedom (i.e., nine nutrients) as a rejection criterion for outliers and a yield threshold of 8.6 Mg ha-1 after Cate-Nelson partitioning between low- and high-yielders in the P validation data set, D2 misclassified two specimens compared with nine for CND -r2. The D2 classification was not significantly different from a χ2 classification (P >0.05), but the CND - r2 classification differed significantly from χ2 or D2(P <0.001). A threshold value for nutrient imbalance could thus be derived probabilistically for conducting D2 diagnosis, while the CND - r2 nutrient imbalance threshold must be calibrated using fertilizer trials. In the proposed CND -D2 procedure, D2 is first computed to classify the specimen as possible outlier. Thereafter, nutrient indices are ranked in their order of limitation. The D2 norms appeared less effective in the 1900-2100 CTU zone.
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spelling Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance indexχ2 distributionGrain cornNitrogen and phosphorus fertilizationNutrient balanceSimplex closureVariance-covariance matrixCompositional nutrient diagnosis (CND) provides a plant nutrient imbalance index (CND - r2) with assumed χ2 distribution. The Mahalanobis distance D2, which detects outliers in compositional data sets, also has a χ2 distribution. The objective of this paper was to compare D2 and CND - r2 nutrient imbalance indexes in corn (Zea mays L.). We measured grain yield as well as N, P, K, Ca, Mg, Cu, Fe, Mn, and Zn concentrations in the ear leaf at silk stage for 210 calibration sites in the St. Lawrence Lowlands [2300-2700 corn thermal units (CTU)] as well as 30 phosphorus (2300-2700 CTU; 10 sites) and 10 nitrogen (1900-2100 CTU; one site) replicated fertilizer treatments for validation. We derived CND norms as mean, standard deviation, and the inverse covariance matrix of centred log ratios (clr) for high yielding specimens (≥9.0 Mg grain ha-1 at 150 g H2O kg-1 moisture content) in the 2300-2700 CTU zone. Using χ2 = 17 (P <0.05) with nine degrees of freedom (i.e., nine nutrients) as a rejection criterion for outliers and a yield threshold of 8.6 Mg ha-1 after Cate-Nelson partitioning between low- and high-yielders in the P validation data set, D2 misclassified two specimens compared with nine for CND -r2. The D2 classification was not significantly different from a χ2 classification (P >0.05), but the CND - r2 classification differed significantly from χ2 or D2(P <0.001). A threshold value for nutrient imbalance could thus be derived probabilistically for conducting D2 diagnosis, while the CND - r2 nutrient imbalance threshold must be calibrated using fertilizer trials. In the proposed CND -D2 procedure, D2 is first computed to classify the specimen as possible outlier. Thereafter, nutrient indices are ranked in their order of limitation. The D2 norms appeared less effective in the 1900-2100 CTU zone.Department of Soils and Agrifood Engineering Paul Comtois Bldg. Université Laval, QC G1K 7P4Department of Soils and Fertilizers Unesp São Paulo State UniversityAgriculture and Agri-Food Canada Soils and Crops Research and Development Centre 2560 Hochelaga Blvd., Quebec, QC G1V 2J3Department of Soils and Fertilizers Unesp São Paulo State UniversityUniversité LavalUniversidade Estadual Paulista (UNESP)2560 Hochelaga Blvd.Parent, Léon EtienneNatale, William [UNESP]Ziadi, Noura2022-04-29T08:47:55Z2022-04-29T08:47:55Z2009-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article383-390http://dx.doi.org/10.4141/cjss08050Canadian Journal of Soil Science, v. 89, n. 4, p. 383-390, 2009.0008-4271http://hdl.handle.net/11449/23188610.4141/cjss080502-s2.0-68949156321Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCanadian Journal of Soil Scienceinfo:eu-repo/semantics/openAccess2022-04-29T08:47:55Zoai:repositorio.unesp.br:11449/231886Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-29T08:47:55Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
title Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
spellingShingle Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
Parent, Léon Etienne
χ2 distribution
Grain corn
Nitrogen and phosphorus fertilization
Nutrient balance
Simplex closure
Variance-covariance matrix
title_short Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
title_full Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
title_fullStr Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
title_full_unstemmed Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
title_sort Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
author Parent, Léon Etienne
author_facet Parent, Léon Etienne
Natale, William [UNESP]
Ziadi, Noura
author_role author
author2 Natale, William [UNESP]
Ziadi, Noura
author2_role author
author
dc.contributor.none.fl_str_mv Université Laval
Universidade Estadual Paulista (UNESP)
2560 Hochelaga Blvd.
dc.contributor.author.fl_str_mv Parent, Léon Etienne
Natale, William [UNESP]
Ziadi, Noura
dc.subject.por.fl_str_mv χ2 distribution
Grain corn
Nitrogen and phosphorus fertilization
Nutrient balance
Simplex closure
Variance-covariance matrix
topic χ2 distribution
Grain corn
Nitrogen and phosphorus fertilization
Nutrient balance
Simplex closure
Variance-covariance matrix
description Compositional nutrient diagnosis (CND) provides a plant nutrient imbalance index (CND - r2) with assumed χ2 distribution. The Mahalanobis distance D2, which detects outliers in compositional data sets, also has a χ2 distribution. The objective of this paper was to compare D2 and CND - r2 nutrient imbalance indexes in corn (Zea mays L.). We measured grain yield as well as N, P, K, Ca, Mg, Cu, Fe, Mn, and Zn concentrations in the ear leaf at silk stage for 210 calibration sites in the St. Lawrence Lowlands [2300-2700 corn thermal units (CTU)] as well as 30 phosphorus (2300-2700 CTU; 10 sites) and 10 nitrogen (1900-2100 CTU; one site) replicated fertilizer treatments for validation. We derived CND norms as mean, standard deviation, and the inverse covariance matrix of centred log ratios (clr) for high yielding specimens (≥9.0 Mg grain ha-1 at 150 g H2O kg-1 moisture content) in the 2300-2700 CTU zone. Using χ2 = 17 (P <0.05) with nine degrees of freedom (i.e., nine nutrients) as a rejection criterion for outliers and a yield threshold of 8.6 Mg ha-1 after Cate-Nelson partitioning between low- and high-yielders in the P validation data set, D2 misclassified two specimens compared with nine for CND -r2. The D2 classification was not significantly different from a χ2 classification (P >0.05), but the CND - r2 classification differed significantly from χ2 or D2(P <0.001). A threshold value for nutrient imbalance could thus be derived probabilistically for conducting D2 diagnosis, while the CND - r2 nutrient imbalance threshold must be calibrated using fertilizer trials. In the proposed CND -D2 procedure, D2 is first computed to classify the specimen as possible outlier. Thereafter, nutrient indices are ranked in their order of limitation. The D2 norms appeared less effective in the 1900-2100 CTU zone.
publishDate 2009
dc.date.none.fl_str_mv 2009-08-01
2022-04-29T08:47:55Z
2022-04-29T08:47:55Z
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/10.4141/cjss08050
Canadian Journal of Soil Science, v. 89, n. 4, p. 383-390, 2009.
0008-4271
http://hdl.handle.net/11449/231886
10.4141/cjss08050
2-s2.0-68949156321
url http://dx.doi.org/10.4141/cjss08050
http://hdl.handle.net/11449/231886
identifier_str_mv Canadian Journal of Soil Science, v. 89, n. 4, p. 383-390, 2009.
0008-4271
10.4141/cjss08050
2-s2.0-68949156321
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Canadian Journal of Soil Science
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 383-390
dc.source.none.fl_str_mv Scopus
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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