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Revista Brasileira de Sementes

Print version ISSN 0101-3122

Abstract

FUNGUETTO, Claudete Izabel; TILLMANN, Maria Ângela André; VILLELA, Francisco Amaral  and  DODE, Luciana Bicca. Bio assays for detection of soybean seeds tolerant to glyphosate herbicide. Rev. bras. sementes [online]. 2004, vol.26, n.1, pp. 130-138. ISSN 0101-3122.  http://dx.doi.org/10.1590/S0101-31222004000100020.

The objective of this study was to adjust methodology to detect soybean seeds tolerant to glyphosate, to characterize the symptoms, to establish the necessary minimum time capable to allow safe and possible evaluation of being reproduced. Three independent assays were done, based on the germination test. In study 1, seeds were pre-imbibed in a substrate containing herbicide solution for 16 hours. In study 2 the substratum was imbibed with the herbicide. In the study 3, seeds were immersed in solution of the herbicide. The standard germination test, speed of germination, length of seedling root and shoot and percentage of seedling secondary roots were used as evaluation parameters. Evaluations were made in the fourth day, until the final count, on the eighth day. All three methods allowed detection of soybean seeds tolerant to the herbicide glyphosate, in the period of five days. The most recommended methodlogies for routine use in seed analysis laboratory were sowing in substratum moistened with solution of the herbicide, at the concentration of 0,03% (480 g/l active ingredient) and pre-imbibing of the seeds for 16 hours, with solution containing 0,4% and 0,6% of glyphosate (480 g/l active ingredient) because they allow germination and the normal development of the aerial parts and root system of genetically modified seedlings. The following symptoms were observed in non GM seedlings : thickened points, longitudinal grooves and with yellowing of the hypocotyl, inhibition of the development of the primary root and of the emission of secondary roots, and the hypocotyl was proportionally larger than the primary root.

Keywords : Glycine max; detection methodology; GMO; symptoms characterization.

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