Multivariate classification of cotton cultivars tolerant to salt stress

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 Serido, 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.