Phytoextraction efficiency of Pteris vittata grown on a naturally As-rich soil and characterization of As-resistant rhizosphere bacteria.

This study evaluated the phytoextraction capacity of the fern Pteris vittata grown on a natural arsenic-rich soil of volcanic-origin from the Viterbo area in central Italy. This calcareous soil is characterized by an average arsenic concentration of 750 mg kg-1, of which 28% is bioavailable. By means of micro-energy dispersive X-ray fluorescence spectrometry (µ-XRF) we detected As in P. vittata fronds after just 10 days of growth, while a high As concentrations in fronds (5,000 mg kg-1), determined by Inductively coupled plasma-optical emission spectrometry (ICP-OES), was reached after 5.5 months. Sixteen arsenate-tolerant bacterial strains were isolated from the P. vittata rhizosphere, a majority of which belong to the Bacillus genus, and of this majority only two have been previously associated with As. Six bacterial isolates were highly As-resistant (> 100 mM) two of which, homologous to Paenarthrobacter ureafaciens and Beijerinckia fluminensis, produced a high amount of IAA and siderophores and have never been isolated from P. vittata roots. Furthermore, five isolates contained the arsenate reductase gene (arsC). We conclude that P. vittata can efficiently phytoextract As when grown on this natural As-rich soil and a consortium of bacteria, largely different from that usually found in As-polluted soils, has been found in P. vittata rhizosphere.

Rapid assessment of As and other elements in naturally-contaminated calcareous soil through hyperspectral VIS-NIR analysis.

Although arsenic (As) toxicity in soil vary depending on its chemical forms and oxidation states, regulatory limits for this compartment rely on total As content. Conventional methods of total As determination are expensive and time-consuming. The development of predictive techniques might enable a speditive assessment of As contamination in those scenarios, such as thermal spring sites, where exposure to the metalloid poses a threat to human health. The objective of this study was to assess the suitability of Visible Near Infrared spectrophotometry for predicting the total As content in highly calcareous thermal spring soils and the same aim was pursued for those elements (i.e. Al, Fe and Mn) the chemistry of which is tightly connected with that of As. A Partial Least Square approach, including cross-validation and external independent test, was used to relate the concentrations of the target elements to spectral data. The most accurate prediction was found for As with Pearson's coefficient, RMSE, RPD and SEP being equal to 0.94, 69.65, 2.9 and 66.99, respectively. Less accurate predictions were found for Al (r = 0.88; RMSE = 11014; RPD = 1.96; SEP = 11014), Fe (r = 0.93; RMSE = 6921.1; RPD = 2.45; SEP = 6462.4), and Mn (r = 0.92; RMSE = 542.01; RPD = 2.43; SEP = 529.79).