Multivariate classification of cotton cultivars tolerant to salt stress

ABSTRACT Two multivariate methods were adopted to classify salt-tolerant cotton genotypes based on their growth and physiological traits. The genotypes were cultivated in a greenhouse and subjected to 45 days of irrigation with saline water from the V4 phase onwards. Irrigation was performed with saline water with electrical conductivity (ECw) of 6.0 dS m-1. A factorial-randomized block design was adopted with nine cultivars, two treatments of ECw (0.6 as the control, and 6.0 dS m-1), and four replicates. Plants were evaluated for growth, gas exchange, and photosynthesis. The data were statistically analyzed using univariate and multivariate methods. For the latter, non-hierarchical (principal component, PC) and hierarchical (UPGMA) models were used for the classification of cultivars. Significant differences were found between cultivars based on univariate analyses, and the traits that differed statistically were used for multivariate analyses. Four groups were identified with the same composition in both the PC and UPGMA methods. Among them, one contained the cultivars BRS Seridó, BRS 286, FMT 705, and BRS Rubi, which were tolerant to salt stress imposed on the plants. Photosynthesis, transpiration, and stomatal conductance data were the main contributors to the classification of cultivars using the principal component method.

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Main Authors: Marcelino,Aline D. A. de L., Fernandes,Pedro D., Ramos,Jean P. C., Dutra,Wellison F., Cavalcanti,José J. V., Santos,Roseane C. dos
Format: Digital revista
Language:English
Published: Departamento de Engenharia Agrícola - UFCG 2022
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662022000400266
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spelling oai:scielo:S1415-436620220004002662022-01-12Multivariate classification of cotton cultivars tolerant to salt stressMarcelino,Aline D. A. de L.Fernandes,Pedro D.Ramos,Jean P. C.Dutra,Wellison F.Cavalcanti,José J. V.Santos,Roseane C. dos Gossypium hirsutum osmotic stress gas exchange clustering ABSTRACT Two multivariate methods were adopted to classify salt-tolerant cotton genotypes based on their growth and physiological traits. The genotypes were cultivated in a greenhouse and subjected to 45 days of irrigation with saline water from the V4 phase onwards. Irrigation was performed with saline water with electrical conductivity (ECw) of 6.0 dS m-1. A factorial-randomized block design was adopted with nine cultivars, two treatments of ECw (0.6 as the control, and 6.0 dS m-1), and four replicates. Plants were evaluated for growth, gas exchange, and photosynthesis. The data were statistically analyzed using univariate and multivariate methods. For the latter, non-hierarchical (principal component, PC) and hierarchical (UPGMA) models were used for the classification of cultivars. Significant differences were found between cultivars based on univariate analyses, and the traits that differed statistically were used for multivariate analyses. Four groups were identified with the same composition in both the PC and UPGMA methods. Among them, one contained the cultivars BRS Seridó, BRS 286, FMT 705, and BRS Rubi, which were tolerant to salt stress imposed on the plants. Photosynthesis, transpiration, and stomatal conductance data were the main contributors to the classification of cultivars using the principal component method.info:eu-repo/semantics/openAccessDepartamento de Engenharia Agrícola - UFCGRevista Brasileira de Engenharia Agrícola e Ambiental v.26 n.4 20222022-04-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662022000400266en10.1590/1807-1929/agriambi.v26n4p266-273
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libraryname SciELO
language English
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author Marcelino,Aline D. A. de L.
Fernandes,Pedro D.
Ramos,Jean P. C.
Dutra,Wellison F.
Cavalcanti,José J. V.
Santos,Roseane C. dos
spellingShingle Marcelino,Aline D. A. de L.
Fernandes,Pedro D.
Ramos,Jean P. C.
Dutra,Wellison F.
Cavalcanti,José J. V.
Santos,Roseane C. dos
Multivariate classification of cotton cultivars tolerant to salt stress
author_facet Marcelino,Aline D. A. de L.
Fernandes,Pedro D.
Ramos,Jean P. C.
Dutra,Wellison F.
Cavalcanti,José J. V.
Santos,Roseane C. dos
author_sort Marcelino,Aline D. A. de L.
title Multivariate classification of cotton cultivars tolerant to salt stress
title_short Multivariate classification of cotton cultivars tolerant to salt stress
title_full Multivariate classification of cotton cultivars tolerant to salt stress
title_fullStr Multivariate classification of cotton cultivars tolerant to salt stress
title_full_unstemmed Multivariate classification of cotton cultivars tolerant to salt stress
title_sort multivariate classification of cotton cultivars tolerant to salt stress
description ABSTRACT Two multivariate methods were adopted to classify salt-tolerant cotton genotypes based on their growth and physiological traits. The genotypes were cultivated in a greenhouse and subjected to 45 days of irrigation with saline water from the V4 phase onwards. Irrigation was performed with saline water with electrical conductivity (ECw) of 6.0 dS m-1. A factorial-randomized block design was adopted with nine cultivars, two treatments of ECw (0.6 as the control, and 6.0 dS m-1), and four replicates. Plants were evaluated for growth, gas exchange, and photosynthesis. The data were statistically analyzed using univariate and multivariate methods. For the latter, non-hierarchical (principal component, PC) and hierarchical (UPGMA) models were used for the classification of cultivars. Significant differences were found between cultivars based on univariate analyses, and the traits that differed statistically were used for multivariate analyses. Four groups were identified with the same composition in both the PC and UPGMA methods. Among them, one contained the cultivars BRS Seridó, BRS 286, FMT 705, and BRS Rubi, which were tolerant to salt stress imposed on the plants. Photosynthesis, transpiration, and stomatal conductance data were the main contributors to the classification of cultivars using the principal component method.
publisher Departamento de Engenharia Agrícola - UFCG
publishDate 2022
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662022000400266
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