Relationship between coffee leaf analysis and soil chemical analysis

Detalhes bibliográficos
Autor(a) principal: Sousa, Jailson Silva
Data de Publicação: 2018
Outros Autores: Neves, Júlio César Lima, Martinez, Herminia Emilia Prieto, Alvarez, Víctor Hugo V.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: http://dx.doi.org/10.1590/18069657rbcs20170109
http://www.locus.ufv.br/handle/123456789/20430
Resumo: Research focused on adequate nutrition of plants is essential in modern coffee production to increase yield and develop more efficient management strategies with greater environmental and economic sustainability. The objectives of this study were to establish critical and optimal levels of soil fertility properties for high yielding Arabica coffee crops using the Boundary Line method and, then, relate the macronutrient contents in the diagnostic leaf of coffee to the macronutrients available in the soil using the Quadrant Diagram of the Plant-Soil Relationship (QDpsR). The study made use of a soil chemical analysis database, leaf macronutrient contents, and Arabica coffee yield from five representative coffee-growing regions in Minas Gerais. An analysis of data consistency was performed, and relative fruit yield (RFY) was related to the soil organic matter (SOM), P, K, Ca, and Mg contents in the soil, establishing the boundary line (BL) in each graph. Equations were adjusted from the BL points, and the equation that best fit was selected. Using the QDpsR method, the response plane was divided into four quadrants, where the total leaf contents of N, P, K, Ca, Mg, and S were plotted as a function of the contents of SOM, P, K, Ca, and Mg in the soil, on the y and x axes of the Cartesian coordinate system. The regression equations were adjusted to the pairs of points (y, x) of quadrants III and I and were used to estimate the macronutrient sufficiency ranges from the critical and optimal levels in the soil. The BL method was used to determine the class of good soil fertility for SOM, P, K, Ca, and Mg. The QDpsR method allows determination of response curves for leaf content as a variable of soil contents, making it possible to estimate the sufficiency ranges in the diagnostic leaf of coffee: 33.4-35.8 g kg-1 of N, 1.4-1.6 g kg-1 of P, 24.4-27.0 g kg-1 of K, 11.9-13.6 g kg-1 of Ca, 3.8-4.5 g kg-1 of Mg, and 1.4-1.8 g kg-1 of S; which were consistent with the sufficiency ranges considered suitable for the crop. This study demonstrated the importance of leaf analysis as a tool for evaluation of the nutritional status of Arabica coffee since the technique is consistent with the theoretical principles underlying it.
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spelling Sousa, Jailson SilvaNeves, Júlio César LimaMartinez, Herminia Emilia PrietoAlvarez, Víctor Hugo V.2018-07-04T14:28:19Z2018-07-04T14:28:19Z2018-06-071806-9657http://dx.doi.org/10.1590/18069657rbcs20170109http://www.locus.ufv.br/handle/123456789/20430Research focused on adequate nutrition of plants is essential in modern coffee production to increase yield and develop more efficient management strategies with greater environmental and economic sustainability. The objectives of this study were to establish critical and optimal levels of soil fertility properties for high yielding Arabica coffee crops using the Boundary Line method and, then, relate the macronutrient contents in the diagnostic leaf of coffee to the macronutrients available in the soil using the Quadrant Diagram of the Plant-Soil Relationship (QDpsR). The study made use of a soil chemical analysis database, leaf macronutrient contents, and Arabica coffee yield from five representative coffee-growing regions in Minas Gerais. An analysis of data consistency was performed, and relative fruit yield (RFY) was related to the soil organic matter (SOM), P, K, Ca, and Mg contents in the soil, establishing the boundary line (BL) in each graph. Equations were adjusted from the BL points, and the equation that best fit was selected. Using the QDpsR method, the response plane was divided into four quadrants, where the total leaf contents of N, P, K, Ca, Mg, and S were plotted as a function of the contents of SOM, P, K, Ca, and Mg in the soil, on the y and x axes of the Cartesian coordinate system. The regression equations were adjusted to the pairs of points (y, x) of quadrants III and I and were used to estimate the macronutrient sufficiency ranges from the critical and optimal levels in the soil. The BL method was used to determine the class of good soil fertility for SOM, P, K, Ca, and Mg. The QDpsR method allows determination of response curves for leaf content as a variable of soil contents, making it possible to estimate the sufficiency ranges in the diagnostic leaf of coffee: 33.4-35.8 g kg-1 of N, 1.4-1.6 g kg-1 of P, 24.4-27.0 g kg-1 of K, 11.9-13.6 g kg-1 of Ca, 3.8-4.5 g kg-1 of Mg, and 1.4-1.8 g kg-1 of S; which were consistent with the sufficiency ranges considered suitable for the crop. This study demonstrated the importance of leaf analysis as a tool for evaluation of the nutritional status of Arabica coffee since the technique is consistent with the theoretical principles underlying it.engRevista Brasileira de Ciência do SoloVolume 42, Article e0170109, Pages 1-13, june 2018Coffea arabica L.Leaf nutrient contentSoil nutrient contentNutritional managementRelationship between coffee leaf analysis and soil chemical analysisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdftexto completoapplication/pdf1140705https://locus.ufv.br//bitstream/123456789/20430/1/artigo.pdf7e9fb5c04b60a16a8d919333293df178MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/20430/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg5815https://locus.ufv.br//bitstream/123456789/20430/3/artigo.pdf.jpg6eb805c907711a178a6797ca6fa76a20MD53123456789/204302018-07-04 23:00:58.664oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-07-05T02:00:58LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Relationship between coffee leaf analysis and soil chemical analysis
title Relationship between coffee leaf analysis and soil chemical analysis
spellingShingle Relationship between coffee leaf analysis and soil chemical analysis
Sousa, Jailson Silva
Coffea arabica L.
Leaf nutrient content
Soil nutrient content
Nutritional management
title_short Relationship between coffee leaf analysis and soil chemical analysis
title_full Relationship between coffee leaf analysis and soil chemical analysis
title_fullStr Relationship between coffee leaf analysis and soil chemical analysis
title_full_unstemmed Relationship between coffee leaf analysis and soil chemical analysis
title_sort Relationship between coffee leaf analysis and soil chemical analysis
author Sousa, Jailson Silva
author_facet Sousa, Jailson Silva
Neves, Júlio César Lima
Martinez, Herminia Emilia Prieto
Alvarez, Víctor Hugo V.
author_role author
author2 Neves, Júlio César Lima
Martinez, Herminia Emilia Prieto
Alvarez, Víctor Hugo V.
author2_role author
author
author
dc.contributor.author.fl_str_mv Sousa, Jailson Silva
Neves, Júlio César Lima
Martinez, Herminia Emilia Prieto
Alvarez, Víctor Hugo V.
dc.subject.pt-BR.fl_str_mv Coffea arabica L.
Leaf nutrient content
Soil nutrient content
Nutritional management
topic Coffea arabica L.
Leaf nutrient content
Soil nutrient content
Nutritional management
description Research focused on adequate nutrition of plants is essential in modern coffee production to increase yield and develop more efficient management strategies with greater environmental and economic sustainability. The objectives of this study were to establish critical and optimal levels of soil fertility properties for high yielding Arabica coffee crops using the Boundary Line method and, then, relate the macronutrient contents in the diagnostic leaf of coffee to the macronutrients available in the soil using the Quadrant Diagram of the Plant-Soil Relationship (QDpsR). The study made use of a soil chemical analysis database, leaf macronutrient contents, and Arabica coffee yield from five representative coffee-growing regions in Minas Gerais. An analysis of data consistency was performed, and relative fruit yield (RFY) was related to the soil organic matter (SOM), P, K, Ca, and Mg contents in the soil, establishing the boundary line (BL) in each graph. Equations were adjusted from the BL points, and the equation that best fit was selected. Using the QDpsR method, the response plane was divided into four quadrants, where the total leaf contents of N, P, K, Ca, Mg, and S were plotted as a function of the contents of SOM, P, K, Ca, and Mg in the soil, on the y and x axes of the Cartesian coordinate system. The regression equations were adjusted to the pairs of points (y, x) of quadrants III and I and were used to estimate the macronutrient sufficiency ranges from the critical and optimal levels in the soil. The BL method was used to determine the class of good soil fertility for SOM, P, K, Ca, and Mg. The QDpsR method allows determination of response curves for leaf content as a variable of soil contents, making it possible to estimate the sufficiency ranges in the diagnostic leaf of coffee: 33.4-35.8 g kg-1 of N, 1.4-1.6 g kg-1 of P, 24.4-27.0 g kg-1 of K, 11.9-13.6 g kg-1 of Ca, 3.8-4.5 g kg-1 of Mg, and 1.4-1.8 g kg-1 of S; which were consistent with the sufficiency ranges considered suitable for the crop. This study demonstrated the importance of leaf analysis as a tool for evaluation of the nutritional status of Arabica coffee since the technique is consistent with the theoretical principles underlying it.
publishDate 2018
dc.date.accessioned.fl_str_mv 2018-07-04T14:28:19Z
dc.date.available.fl_str_mv 2018-07-04T14:28:19Z
dc.date.issued.fl_str_mv 2018-06-07
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.issn.none.fl_str_mv 1806-9657
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http://www.locus.ufv.br/handle/123456789/20430
dc.language.iso.fl_str_mv eng
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dc.relation.ispartofseries.pt-BR.fl_str_mv Volume 42, Article e0170109, Pages 1-13, june 2018
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