Longitudinal data assessment of global stability index in kale leaves
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2016 |
| Outros Autores: | , , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositório Institucional da UFMG |
| Texto Completo: | http://dx.doi.org/10.1590/0103-9016-2014-0334 http://hdl.handle.net/1843/40660 https://orcid.org/0000-0001-5196-0851 |
Resumo: | CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico |
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2022-03-31T13:11:16Z2022-03-31T13:11:16Z20167317984http://dx.doi.org/10.1590/0103-9016-2014-03341678992Xhttp://hdl.handle.net/1843/40660https://orcid.org/0000-0001-5196-0851CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas GeraisCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorKale plants are usually sold “in natura” in street markets and malls. Kale leaves can have their appearance compromised by dehydration and discoloration due to increased post-harvest time exposure. We aimed to analyze the Global Stability Index (GSI) in kale accessions by means of repeated measurement analysis and curve grouping as a complementary form of superior sample identification with regard to post-harvest preservation. Thirty kale accessions were evaluated using a randomized block design with four blocks and five plants per plot. Two commercial leaves per plant were collected, and kept on workbenches in the shade at a temperature of 18 ± 1 °C. Subsequently, the degrees of discoloration and dehydration, total chlorophyll content, and accumulated fresh mass loss were evaluated over a 15-day period. From these data, the GSI was calculated for each day of evaluation. In addition, using mixed models, thirteen co-variance structures were tested. For graphical analysis, thirteen linear and non-linear models were assessed followed by curve grouping using multivariate analysis. The GSI was efficient for differentiating accessions, which became an important tool in post-harvest studies. GSI values were not equally correlated, therefore the use of mixed models became an important approach. The unstructured matrix was the best fit to model the dependence of error. The Melow I model was the best fit for studying the GSI. The accessions UFVJM-10, UFLA-1, COM-1, UFVJM-32, COM-3, UFVJM-8, UFVJM-36 and UFVJM-24, belonging to 3 and 5 clusters, are recommended for crop cultivation and as parental material in breeding programs.engUniversidade Federal de Minas GeraisUFMGBrasilICA - INSTITUTO DE CIÊNCIAS AGRÁRIASScientia AgricolaCouvePós-colheitaAnalise multivariadaAjuste de curvaLongitudinal data assessment of global stability index in kale leavesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://www.revistas.usp.br/sa/article/view/108537?msclkid=4d4779e9b0f211ec8ef5039af25cdbebAlcinei Mistico AzevedoValter Carvalho de Andrade JúniorCarlos Enrrik PedrosaNermy Ribeiro ValadaresMarcos Aurélio Miranda FerreiraPaulo Roberto Ceconinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/40660/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALLongitudinal data assessment of global stability index in kale leaves.pdfLongitudinal data assessment of global stability index in kale leaves.pdfapplication/pdf388330https://repositorio.ufmg.br/bitstream/1843/40660/2/Longitudinal%20data%20assessment%20of%20global%20stability%20index%20in%20kale%20leaves.pdf3da34f9371d0497137bbddb7579c229fMD521843/406602022-03-31 10:11:16.945oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2022-03-31T13:11:16Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
| dc.title.pt_BR.fl_str_mv |
Longitudinal data assessment of global stability index in kale leaves |
| title |
Longitudinal data assessment of global stability index in kale leaves |
| spellingShingle |
Longitudinal data assessment of global stability index in kale leaves Alcinei Mistico Azevedo Couve Pós-colheita Analise multivariada Ajuste de curva |
| title_short |
Longitudinal data assessment of global stability index in kale leaves |
| title_full |
Longitudinal data assessment of global stability index in kale leaves |
| title_fullStr |
Longitudinal data assessment of global stability index in kale leaves |
| title_full_unstemmed |
Longitudinal data assessment of global stability index in kale leaves |
| title_sort |
Longitudinal data assessment of global stability index in kale leaves |
| author |
Alcinei Mistico Azevedo |
| author_facet |
Alcinei Mistico Azevedo Valter Carvalho de Andrade Júnior Carlos Enrrik Pedrosa Nermy Ribeiro Valadares Marcos Aurélio Miranda Ferreira Paulo Roberto Cecon |
| author_role |
author |
| author2 |
Valter Carvalho de Andrade Júnior Carlos Enrrik Pedrosa Nermy Ribeiro Valadares Marcos Aurélio Miranda Ferreira Paulo Roberto Cecon |
| author2_role |
author author author author author |
| dc.contributor.author.fl_str_mv |
Alcinei Mistico Azevedo Valter Carvalho de Andrade Júnior Carlos Enrrik Pedrosa Nermy Ribeiro Valadares Marcos Aurélio Miranda Ferreira Paulo Roberto Cecon |
| dc.subject.other.pt_BR.fl_str_mv |
Couve Pós-colheita Analise multivariada Ajuste de curva |
| topic |
Couve Pós-colheita Analise multivariada Ajuste de curva |
| description |
CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico |
| publishDate |
2016 |
| dc.date.issued.fl_str_mv |
2016 |
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2022-03-31T13:11:16Z |
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2022-03-31T13:11:16Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/1843/40660 |
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http://dx.doi.org/10.1590/0103-9016-2014-0334 |
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1678992X |
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https://orcid.org/0000-0001-5196-0851 |
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http://dx.doi.org/10.1590/0103-9016-2014-0334 http://hdl.handle.net/1843/40660 https://orcid.org/0000-0001-5196-0851 |
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1678992X |
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eng |
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eng |
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Scientia Agricola |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Universidade Federal de Minas Gerais |
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UFMG |
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Brasil |
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ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS |
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Universidade Federal de Minas Gerais |
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reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
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