Longitudinal data assessment of global stability index in kale leaves

ABSTRACT Kale 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...

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Main Authors: Alcinei Mistico Azevedo, Valter Carvalho de Andrade Júnior, Carlos Enrrik Pedrosa, Nermy Ribeiro Valadares, Marcos Aurélio Miranda Ferreira, Paulo Roberto Cecon
Format: Article
Language:English
Published: Universidade de São Paulo 2016-02-01
Series:Scientia Agricola
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000100079&lng=en&tlng=en
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author Alcinei Mistico Azevedo
Valter Carvalho de Andrade Júnior
Carlos Enrrik Pedrosa
Nermy Ribeiro Valadares
Marcos Aurélio Miranda Ferreira
Paulo Roberto Cecon
author_facet Alcinei Mistico Azevedo
Valter Carvalho de Andrade Júnior
Carlos Enrrik Pedrosa
Nermy Ribeiro Valadares
Marcos Aurélio Miranda Ferreira
Paulo Roberto Cecon
author_sort Alcinei Mistico Azevedo
collection DOAJ
description ABSTRACT Kale 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.
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spelling doaj.art-c44c01eb7ce14ac0bdf7b971dd1d44712022-12-21T18:01:53ZengUniversidade de São PauloScientia Agricola1678-992X2016-02-01731798410.1590/0103-9016-2014-0334S0103-90162016000100079Longitudinal data assessment of global stability index in kale leavesAlcinei Mistico AzevedoValter Carvalho de Andrade JúniorCarlos Enrrik PedrosaNermy Ribeiro ValadaresMarcos Aurélio Miranda FerreiraPaulo Roberto CeconABSTRACT Kale 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000100079&lng=en&tlng=enBrassica oleracea var. acephala DCpost-harvest preservationrepeated measurementsmultivariate statisticscurve grouping
spellingShingle Alcinei Mistico Azevedo
Valter Carvalho de Andrade Júnior
Carlos Enrrik Pedrosa
Nermy Ribeiro Valadares
Marcos Aurélio Miranda Ferreira
Paulo Roberto Cecon
Longitudinal data assessment of global stability index in kale leaves
Scientia Agricola
Brassica oleracea var. acephala DC
post-harvest preservation
repeated measurements
multivariate statistics
curve grouping
title 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_short Longitudinal data assessment of global stability index in kale leaves
title_sort longitudinal data assessment of global stability index in kale leaves
topic Brassica oleracea var. acephala DC
post-harvest preservation
repeated measurements
multivariate statistics
curve grouping
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000100079&lng=en&tlng=en
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AT nermyribeirovaladares longitudinaldataassessmentofglobalstabilityindexinkaleleaves
AT marcosaureliomirandaferreira longitudinaldataassessmentofglobalstabilityindexinkaleleaves
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