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Revista Caatinga

Print version ISSN 0100-316XOn-line version ISSN 1983-2125

Abstract

GILIO, THIAGO ALEXANDRE SANTANA et al. GENETIC DIVERGENCE AMONG COTTON GENOTYPES GROWN IN THE MAIN SEASON AND OFF SEASON. Rev. Caatinga [online]. 2017, vol.30, n.2, pp.377-390. ISSN 0100-316X.  http://dx.doi.org/10.1590/1983-21252017v30n213rc.

The objective of this work was to evaluate the agronomic performance and estimate the genetic divergence of 18 cotton genotypes grown in the main season (sowed in December, 2012) and off season (sowed in January, 2013), considering their agronomic characteristics and resistance to Ramularia leaf spot. A randomized block experimental design was used, with five replications. The characteristics evaluated were plant height, first branch height, position of first fruiting branch, height of first fruiting branch, length between nodes, number of nodes, average number of bolls per plant, average boll weight, area under the disease progress curve (AUDPC) related to the Ramularia leaf spot severity, weight of 100-seed from the plant middle third, fiber percentage, average production per plant, yield and cotton fiber quality. The results were subjected to individual and joint analysis of variance and the genetic divergence was estimated according to multivariate procedures (Mahalanobis' generalized distance and Tocher's optimization method). The dissimilarity matrices were summed to estimate the genetic divergence, considering both growing periods. Genetic variability was found among the genotypes evaluated, in both the main season and off season. The characteristic that most contributed to the genetic divergence in the main season was the production per plant and, in the off season, was the fiber percentage. According to the results of the present work, the crosses between the genotypes BRS-335 and FMT-707; FM-910 and FMT-707; and IMA-08-12427 and FMT-707 are recommended.

Keywords : Agronomic characteristics; Ramularia leaf spot; Gossypium hirsutum L.; Mahalanobis' generalized distance; Tocher's optimization method..

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