Authors
Claudia Savarese, Massimiliano Gargiulo, Francesco Tufano, Sara Parrilli, Lina Fusaro, Francesca Lanni, Fausto Manes, Mirco Boschetti, Gabriele Candiani, Cinzia Panigada, Roberto Colombo, Maria Vittoria Verrillo, Vincenza Cozzolino, Alessandro Piccolo, Marco De Mizio
Published in
Environmental research. Pages 125597. Sep 12, 2026. Epub Sep 12, 2026.
Abstract
Soil contamination represents a growing environmental concern, particularly in areas such as the "Land of Fires" (Campania region, Italy). This study evaluates the potential of Zea mays L. as a bioindicator of soil contamination through a multiscale approach. In bin-like containers under natural conditions, maize plants were grown on untreated (C) and artificially contaminated (T) soil with a mixture of heavy metals (Pb, Zn, Cr) and benzo[a]pyrene. Analyses were conducted at leaf, canopy, and field scales, integrating eco-physiological, spectral, and UAV measurements. At the leaf level, contamination induced functional alterations in photochemical and spectral traits that were strongly dependent on the growth stage, being most pronounced early in the season and progressively attenuating thereafter. At the canopy level, contaminated plants developed less height and leaf area, together with lower chlorophyll- and canopy-density-sensitive spectral indices, consistent with reduced vegetative vigor under contamination stress. Solar Induced Fluorescence (SIF) showed no residual difference between treatments once normalized for biomass production at the end of the growing season, in agreement with leaf-level active fluorescence measurements taken on the same date. At the field scale, UAV-based classification achieved superior performance with hyperspectral relative to multispectral data in distinguishing contaminated areas. Taken together, these results show that, under the experimental exposure conditions adopted here, the detectability of soil pollution by maize progressively shifts from early, transient physiological signals to persistent structural differences, while UAV hyperspectral data provided the highest discrimination between treatments. By tracking how leaf-level functional alterations translate into canopy- and field-scale structural separability, this study provides a scale-explicit assessment of maize as a promising bioindicator of soil contamination.
PMID:
42731588
Bibliographic data and abstract were imported from PubMed on 13 Sep 2026.
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