Abstract
The so-called hyperaccumulator plants are capable of storing hundred or thousand times bigger quantities of heavy metals than normal plants, which makes hyperaccumulators very useful in fields such as phytoremediation and phytomining. Among these plants there are many serpentinophytes, i.e., plants that grow exclusively on ultramafic rocks which produce soils with a great proportion of heavy metals. Even though there are multiple classifications, the lack of consensus regarding which parameters to use to determine whether a plant is a hyperaccumulator, as well as the arbitrariness of stablished thresholds, bring about the need to propose more objective criteria. To this end, plant mineral composition data from different vegetal species were analysed using machine learning techniques. Three complementary case studies were established. Firstly, plants were classified in three types of soils: dolomite, gypsum and serpentine. Secondly, data about normal and hyperaccumulator plant Ni composition were analysed with machine learning to find differentiated subgroups. Lastly, association studies were carried out using data about mineral composition and soil type. Results in the classification task reach a success rate over 75%. Clustering of plants by Ni concentration in parts per million (ppm) resulted in four groups with cut-off points in 2.25, 100 (accumulators) and 3000 ppm (hyperaccumulators). Associations with a confidence level above 90% were found between high Ni levels and serpentine soils, as well as between high Ni and Zn levels and the same type of soil. Overall, this work demonstrates the potential of machine learning to analyse data about plant mineral composition. Finally, after consulting the red list of the IUCN and those of countries with high richness in hyperaccumulator species, it is evident that a greater effort should be made to establish the conservation status of this type of flora.
Highlights
Nowadays, research on the use of certain organisms to eliminate heavy metals and other pollutants is of great interest
The element for which there was more information, taking into account that the bibliography focused on serpentine plants, was Ni, both in specialized literature and in the GHD. This is logical because serpentine soils are characterised by their high Ni content (Rajakaruna et al, 2009)
Even though economics is becoming increasingly important, different approaches that focus on concrete aspects while disregarding others prevail
Summary
Research on the use of certain organisms to eliminate heavy metals and other pollutants is of great interest. Most of the toxic metal cases in Africa and other developing nations are a result of industrialization coupled with poor effluent disposal and management. Due to widespread mining activities in South Africa, pollution is a common site with devastating consequences on the health of animals and humans likewise. Talks on toxic metal pollution had taken center stage in most scientific symposiums as a serious health concern. Very high levels of toxic metals have been reported in most parts of South African soils, plants, animals and water bodies due to pollution.
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