Study on the detection of heavy metal lead (Pb) in mussels based on near-infrared spectroscopy technology and a REELM classifier

Hazardous Elements in the Edible Portion of Perna perna Mussels: Relation with the COVID-19 Pandemic Period and Assessment of the Risk to Human Health

In this work, the concentrations of hazardous elements (As, Cd and Pb) in the edible portion of the Perna perna mussel from Southeast Brazil were analyzed to understand the effects of the COVID-19 pandemic on the coastal environment and to evaluate the quality of this fishery resource. Decreases in anthropogenic chemical outputs to the environment were expected to occur during the COVID-19 pandemic, with decreases in element concentrations in mussels. The ranges of median concentrations (µg g-1 dw) in the pre- and pandemic periods were 5.4-16.1 and 2.2-10.6 for As; 0.2-0.6 and 0.1-0.5 for Cd; and 1.2-3.2 and 0.7-1.8 for Pb, respectively. Temporal variations (prepandemic x pandemic) were more significant than spatial variations (five sampling sites). The relationships between the concentrations of hazardous elements and isotopic ratios (δ15N and δ13C) suggested that food sources were more diverse across the sampling sites during the pandemic period, when individuals exhibited less efficient trophic transfer. The concentrations of Cd and Pb were below the tolerable maximum limit, whereas for As, they were above the limit; however, these concentrations are not a risk to human health, as most As was present in the least toxic organic form. The intake estimates were below the tolerable intake limits, and only Pb concentrations are at risk of causing concern if the intake of mussels increases. This is the first study in Brazil that presents a spatial-temporal comparison of hazardous elements in marine fauna considering COVID-19 as a temporal landmark. The results are of interest for both public health and environmental health management in a post-COVID-19 scenario.

Identification of Perna viridis contaminated with diarrhetic shellfish poisoning toxins in vitro using NIRS and a discriminative non-negative representation-based classifier

Diarrhetic shellfish poisoning (DSP) toxins are one of the most widespread marine biotoxins that affect aquaculture and human health, and their detection has become crucial. In this study, near-infrared reflectance spectroscopy (NIRS) with non-destructive characteristics was used to identify DSP toxins in Perna viridis. The spectral data of the DSP toxin-contaminated and non-contaminated Perna viridis samples were acquired in the 950-1700 nm range. To solve the discrimination of spectra with crossover and overlapping, a discriminative non-negative representation-based classifier (DNRC) has been proposed. Compared with collaborative and non-negative representation-based classifiers, the DNRC model exhibited better performance in detecting DSP toxins, with a classification accuracy of 99.44 %. For a relatively small-scale sample dataset in practical applications, the performance of the DNRC model was compared with those of classical models. The DNRC model achieved the best results for both identification accuracy and F-measure, and its detection performance did not significantly decrease with decreasing sample size. The experimental results validated that a combination of NIRS and the DNRC model can facilitate rapid, convenient, and non-destructive detection of DSP toxins in Perna viridis.