An innovative approach, based on hyperspectral imaging (HSI) coupled with chemometrics, allowing the detection of arsenic (As) in the hyper-accumulator fern Pteris Vittata L., is presented in this study. The aim of this work was to investigate the possibility of monitoring by HSI the As sequestration capacity of plants grown on As-contaminated soils, in order to perform soil remediation. The proposed approach is based on the acquisition by HSI in the SWIR range (1000-2500 nm) of fern leaves, followed by the implementation of a classification model based on Partial Least Square Discriminant Analysis (PLS-DA). Following this procedure, false color maps, representative of the chemical elements distribution on the leaves were obtained, where As is clearly detected without performing any chemical analysis. The proposed approach is not invasive and not destructive. Comparative evaluations were carried out analyzing Pteris Vittata L. leaves collected from plants grown on natural soils containing different As concentrations. To evaluate reliability, robustness and analytical correctness of the proposed HSI approach, micro X-ray fluorescence (μXRF) analyses were carried out on the same samples in order to quantitatively and topologically assess As presence in the leaves of the plants. The achieved results are very promising for monitoring the phytoremediation process by detecting and controlling the uptake of As plants growing on contaminated soils.

An innovative approach based on hyperspectral imaging (HSI) combined with chemometrics for soil phytoremediation monitoring / Bonifazi, G.; Capobianco, G.; Serranti, S.; Antenozio, M. L.; Brunetti, P.; Cardarelli, M.. - 11287:(2020), pp. 1-10. ((Intervento presentato al convegno Photonic Instrumentation Engineering VII 2020 tenutosi a San Francisco; USA [10.1117/12.2543539].

An innovative approach based on hyperspectral imaging (HSI) combined with chemometrics for soil phytoremediation monitoring

Bonifazi G.;Capobianco G.;Serranti S.
;
Antenozio M. L.;Brunetti P.;Cardarelli M.
2020

Abstract

An innovative approach, based on hyperspectral imaging (HSI) coupled with chemometrics, allowing the detection of arsenic (As) in the hyper-accumulator fern Pteris Vittata L., is presented in this study. The aim of this work was to investigate the possibility of monitoring by HSI the As sequestration capacity of plants grown on As-contaminated soils, in order to perform soil remediation. The proposed approach is based on the acquisition by HSI in the SWIR range (1000-2500 nm) of fern leaves, followed by the implementation of a classification model based on Partial Least Square Discriminant Analysis (PLS-DA). Following this procedure, false color maps, representative of the chemical elements distribution on the leaves were obtained, where As is clearly detected without performing any chemical analysis. The proposed approach is not invasive and not destructive. Comparative evaluations were carried out analyzing Pteris Vittata L. leaves collected from plants grown on natural soils containing different As concentrations. To evaluate reliability, robustness and analytical correctness of the proposed HSI approach, micro X-ray fluorescence (μXRF) analyses were carried out on the same samples in order to quantitatively and topologically assess As presence in the leaves of the plants. The achieved results are very promising for monitoring the phytoremediation process by detecting and controlling the uptake of As plants growing on contaminated soils.
Photonic Instrumentation Engineering VII 2020
arsenic; HyperSpectral Imaging; phytoremediation; PLS-DA; Pteris Vittata L.
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
An innovative approach based on hyperspectral imaging (HSI) combined with chemometrics for soil phytoremediation monitoring / Bonifazi, G.; Capobianco, G.; Serranti, S.; Antenozio, M. L.; Brunetti, P.; Cardarelli, M.. - 11287:(2020), pp. 1-10. ((Intervento presentato al convegno Photonic Instrumentation Engineering VII 2020 tenutosi a San Francisco; USA [10.1117/12.2543539].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1390958
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