Pollutants accumulate in aquatic habitats as a result of mining activities. Lemna gibba and Lemna minor were used in this study to examine the accumulation capacities of Mo+, Pb+, and Cu++ in the acid fluids of the copper mining. Duckweed family includes water plants like L. minor and L. gibba. These are tiny, delicate, free-floating aquatic plants. Two reactors were assigned to L. gibba and L. minor, respectively. Throughout the course of eight days, these plants and reactor water were gathered every day. The acid mine water's pH, temperature, and electric conductivity were also tested every day. The L. gibba and L. minor were cleaned, dehydrated, and burned in a drying oven for a whole day at 300 oC. ICP-MS (Inductively Coupled Plasma Mass Spectroscopy) was used to determine the Mo+, Pb+, and Cu++ content of the plant and water samples. The concentrations of Mo, Pb, and Cu in the acid mine fluids of the copper mining were 30±4, 260±12, and 15535±322 μg L−1, respectively.in that order. When it came to extracting Mo, Pb, and Cu from the acidic fluids of the copper mining, L. gibba and L. minor performed well and efficiently compared to control samples; they did so 29 and 177 times for Mo, 30 and 109 times for Pb, and 495 and 1150 times for Cu. Considering all these findings, it has been shown that L. gibba and L. minor have the ability to efficiently remove Mo, Pb and Cu in acid mine fluids and can be good rehabilitation plants for polluted waters.

Numerous new technologies have been implemented in image analysis methods that help researchers withdraw scientific conclusions from biological phenomena. Plants of the family Lemnaceae (duckweeds) are the smallest flowering plants in the world, and biometric measurements of single plants and their growth rate are highly challenging. Although the use of software for digital image analysis has changed the way scientists extract phenomenological data (also for studies on duckweeds), the procedure is often not wholly automated and sometimes relies on the intervention of a human operator. Such a constraint can limit the objectivity of the measurements and generally slows down the time required to produce scientific data. Here is the need to implement image analysis software with artificial intelligence that can substitute the human operator. In this paper, we present a new method to study the growth rates of the plants of the Lemnaceae family based on the application of machine learning procedures to digital image analysis. The method is compared to existing analogical and computer-operated procedures. Results showed that our method drastically reduces the time consumption of the human operator while retaining a high correlation in the growth rates measured with other procedures As expected, machine learning methods applied to digital image analysis can overtake the constraints of measuring growth rates of very small plants and might help duckweeds gain worldwide attention thanks to their great nutritional qualities and biological plasticity.

A two-fold integrated research study was conducted; firstly, to understand effects of copper (Cu) and zinc (Zn) on the growth and oxidative stress in Nile tilapia, Oreochromis niloticus; secondly, to study the beneficial effects of the duckweed Lemna minor L. as a heavy metal remover from wastewater. Experiments were conducted in mesocosms with and without duckweed. Tilapia fingerlings were exposed to Cu (0.004 and 0.02 mg/L) and Zn (0.5 and 1.5 mg/L) and fish fed for four weeks. We evaluated the fish growth performance, the hepatic DNA structure using comet assay, the expression of antioxidative genes (superoxide dismutase, SOD; catalase, CAT; glutathione peroxidase, GPx and glutathione-S-transferase, GST) and GPx and GST enzymatic activity. The results showed that Zn exhibited more pronounced toxic effects than Cu. Low dose of Cu did not influence the growth whereas higher doses of Cu and Zn significantly reduced the growth rate of tilapia compared to control, but addition of duckweed prevented weight loss. Further, in the presence of a high dose of Cu and Zn, DNA damage decreased, antioxidant gene expressions and enzymatic activities increased. In conclusion, results suggest that duckweed and Nile tilapia can be suitable candidates in metal remediation wastewater assessment programs.