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.

Production of an innovative biowaste-derived fertilizer: Rapid monitoring of physical-chemical parameters by hyperspectral imaging.

In this work the possibility to apply hyperspectral imaging as a fast and non-destructive technique for the monitoring of the production process at pilot plant scale of an innovative biowaste-derived fertilizer was explored. Different mixtures of urban organic waste, farm organic residues, biochar and vegetable active principles were selected and utilized in two different European countries, Italy and Spain, for the production of the innovative fertilizer. The biowaste-derived fertilizer samples were collected from the pilot plant piles at different curing time and acquired by the hyperspectral imaging device. Spectra have been collected in the near infrared wavelength range (1000-1700 nm). Conventional analyses were carried out on the same samples in order to find correlations between the physical-chemical parameters detected at laboratory scale, and the acquired reflectance spectra. The investigated parameters were: pH, electrical conductivity, soluble total organic carbon and soluble total nitrogen. Hyperspectral data were processed adopting chemometric strategies through the application of principal component analysis, for exploratory purposes, and partial least squares analysis to establish correlations between spectral features and measured physical-chemical parameters. Good correlations, with R2 ranging between 0.85 and 0.96, were obtained for all the investigated parameters. Results showed as the proposed approach, based on hyperspectral imaging, is suitable to be adopted for a rapid and non-destructive monitoring of waste-derived fertilizer production.

A new approach for the modelling of chestnut wood photo-degradation monitored by different spectroscopic techniques.

The aim of this work is to study the colour and chemical modifications of the surfaces in chestnut wood samples as a consequence of irradiating in a controlled environment. The changes were investigated by a new analytical approach by combining traditional techniques such as reflectance spectrophotometry in the visible range and Fourier transform infrared spectroscopy with new hyperspectral imaging, in order to obtain forecast models to describe the phenomenon. The statistical elaboration of the experimental data allowed to validate the measurements and to obtain models enabling to relate the investigated parameters; the elaboration of the hyperspectral images by chemometric methods allowed for studying the changes in the reflectance spectra. A result of great importance is the possibility to correlate the oxidation of wood chemical components with the colour change in a totally non-invasive modality. This result is particularly relevant in the field of cultural heritage and in general in the control processes of wooden materials.

Early detection of toxigenic fungi on maize by hyperspectral imaging analysis.

Fungi can grow on many food commodities. Some fungal species, such as Aspergillus flavus, Aspergillus parasiticus, Aspergillus niger and Fusarium spp., can produce, under suitable conditions, mycotoxins, secondary metabolites which are toxic for humans and animals. Toxigenic fungi are a real issue, especially for the cereal industry. The aim of this work is to carry out a non destructive, hyperspectral imaging-based method to detect toxigenic fungi on maize kernels, and to discriminate between healthy and diseased kernels. A desktop spectral scanner equipped with an imaging based spectrometer ImSpector- Specim V10, working in the visible-near infrared spectral range (400-1000 nm) was used. The results show that the hyperspectral imaging is able to rapidly discriminate commercial maize kernels infected with toxigenic fungi from uninfected controls when traditional methods are not yet effective: i.e. from 48 h after inoculation with A. niger or A. flavus.