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Introduction to Capparales

  • K. Kubitzki
Chapter
Part of the The Families and Genera of Vascular Plants book series (FAMILIES GENERA, volume 5)

Abstract

The concept of the order Capparales as presented here has a complex history. It is true that a close relationship among Capparaceae, Cruciferae and Resedaceae had been assumed by early plant systematists. Originally, these families, together with Papaveraceae, were accommodated in an order named Rhoeadales, and the disymmetric floral structure of Papaveraceae and Cruciferae seemed to provide a convincing link between them. The first to recognise the hybrid nature of this construct was Hallier (1912), who removed Papaveraceae from Rhoeadales and placed them between Ranunculaceae and Nymphaeaceae in his Ranales. Hallier’s realignement passed nearly unnoticed for a long time until, in the 1950s, Takhtajan, following the work of Blagowestschenski (1955), became aware of the profound difference in secondary metabolites between Papaveraceae and Cruciferae/Capparaceae. By then the time had become ripe to accept this type of evidence as systematically meaningful, and the taxonomic consequences drawn by Takhtajan became more widely known through a book published in a western language (Takhtajan 1959). Actually, Papaveraceae share a group of biosynthetically related, yet taxonomically relatively restricted alkaloids with the families of Ranunculales (see Gottlieb et al.1993 in Vol. II of this series). The remaining families of the Rhoeadales (from then onwards called Capparales by most systematists), i.e., Cruciferae, Capparaceae, Resedaceae and Tovariaceae (which meanwhile had been added to the order), contain very specific sulfur-containing glucosides, the glucosinolates, and the enzyme myrosinase which, upon injury of the plant tissue, interact to produce volatile mustard oils (isothiocyanates).

Keywords

Seed Coat Ellagic Acid Defence Theory Enzyme Myrosinase Taxonomic Consequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2003

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  • K. Kubitzki

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