Phytophthora species diversity associated with native and non-native forests in South Africa
Loading...
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Phytophthora represents a threat to agricultural crops and commercial forests as well as affecting global native plant diversity. This review brings together updates from different fields of Phytophthora research and also covers the impact of Phytophthora diseases on global tree health, with special emphasis on the situation in South Africa. During the course of the past few decades, techniques to facilitate the isolation and identification of new Phytophthora species have increased rapidly and this has been strongly influenced by advances in molecular tools. In addition to traditional methods for isolation, efforts have been made to detect Phytophthora a priori and to link this to disease incidence using metagenetics as well as other molecular and biochemical assays. Improved isolation techniques have positively impacted on evolutionary studies. Molecular phylogenies have improved the species concepts for Phytophthora, leading to revisions of species and the identification of cryptic taxa. The diversity of Phytophthora species from the African continent is largely unknown. This is in spite of the fact that Africans depend heavily on agriculture and forestry. In South Africa, various Phytophthora diseases have been reported, starting with the first report of the pathogen in 1913, causing crown rot of rhubarb. Phytophthora diseases are common among agricultural and horticultural plants in the country. Important commercially propagated trees such as Eucalyptus, Acacia and Pinus are also affected by Phytophthora species. In South Africa, knowledge regarding the diversity of Phytophthora from natural ecosystems is limited, although Phytophthora cinnamomi is known to be causing serious disease of native plants in the Cape Floristic Region of South Africa.
Description
Thesis (PhD (Forestry and Agricultural Biotechnology))--University of Pretoria, 2017.
Keywords
Eucalyptus, Metabarcoding, Phytophthora, Acacia, Pyrosequencing
