Abstract

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.

Highlights

  • Another method adopted to predict the similarity of genotypes is graphical dispersion by principal component analysis, which presents the clustering of genotypes through dispersion in a two- or three-dimensional plane, facilitating the identification of the most divergent types (Resende, 2007; Cruz et al, 2012)

  • Significant differences were found among cultivars for all traits; the differences were found only for plant height (PH) between treatments (ECw) (Table 2)

  • The plant disturbances of stressed plants were demonstrated through deformations and thickening of leaves, and growth reduction in some cultivars, reflected in plant height, as seen in FM 966, CNPA 7MH, CNPA 5M, and CNPA ITA 90, as well as a reduction in diameter of the main stem, which was more visible in CNPA 5M and FMT 705 (Figure 1)

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Summary

Introduction

Salinity is a serious environmental problem affecting several crops worldwide. According to the literature, there are more than 1 billion hectares of salinized soil, mainly in arid and semiarid regions where the leaching of salt is poor due to limited and erratic rainfall (Jesus et al, 2015). Groups are established based on their internal homogeneity and heterogeneity (Cruz et al, 2012) Among these techniques, the hierarchical unweighted pair group method with arithmetic mean (UPGMA) is one of the most commonly used by breeders of various commercial crops (Härdle & Simar, 2003; Ramos et al, 2015). The hierarchical unweighted pair group method with arithmetic mean (UPGMA) is one of the most commonly used by breeders of various commercial crops (Härdle & Simar, 2003; Ramos et al, 2015) Another method adopted to predict the similarity of genotypes is graphical dispersion by principal component analysis, which presents the clustering of genotypes through dispersion in a two- or three-dimensional plane, facilitating the identification of the most divergent types (Resende, 2007; Cruz et al, 2012). The UPGMA and principal component methods were used to classify divergent cotton cultivars by salt tolerance level, by subjecting nine commercial cultivars to moderate salt stress and evaluating their growth and physiological traits

Material and Methods
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Literature Cited

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