ReviewA review of germination and early growth as a proxy for plant fitness under petrogenic contamination - knowledge gaps and recommendations

- Petrogenic contamination effects on germination and seedling stages are documented.
- The use of root imaging software is proposed for ecotoxicological assessments.
- Key traits are suggested to inform selection criteria of appropriate plant species.
- Recommendations are made to improve germination protocols.

Germination-an important stage in the life cycle of plants-is susceptible to the presence of soil contaminants. Since the early 1990s, the use of germination tests to screen multiple plant species to select candidates for phytoremediation has received much attention. This is due to its inexpensive methodology and fast assessment relative to greenhouse or field growth studies. Surprisingly, no comprehensive synthesis is available of these studies in the scientific literature. As more plant species are added to phytoremediation databases, it is important to encapsulate the knowledge thus far and revise protocols. In this review, we have summarised previously-documented effects of petroleum hydrocarbons on germination and seedling growth. The methods and materials of previous studies are presented in tabulated form. Common practice includes the use of cellulose acetate filter paper, plastic Petri dishes, and low numbers of seeds and replicates. A general bias was observed for the screening of cultivated crops as opposed to native species, even though the latter may be better suited to site conditions. The relevance of germination studies as important ecotoxicological tools is highlighted with the proposed use of root imaging software. Screening of novel plant species, particularly natives, is recommended with selection focussed on (i) species phylogeny, (ii) plant morphological and functional traits, and (iii) tolerance towards harsh environmental stresses. Recommendations for standardised protocols for germination and early growth monitoring are made in order to improve the robustness of statistical modelling and species selection in future phytoremediation evaluations and field programs.

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