Determination of Cadmium, Copper, Lead, and Zinc in Pilchard Sardines from the Bay of Boumerdés by Atomic Absorption Spectrometry

Electrochemical and Colorimetric Nanosensors for Detection of Heavy Metal Ions: A Review

Human exposure to acute and chronic levels of heavy metal ions are linked with various health issues, including reduced children's intelligence quotients, developmental challenges, cancers, hypertension, immune system compromises, cytotoxicity, oxidative cellular damage, and neurological disorders, among other health challenges. The potential environmental HMI contaminations, the biomagnification of heavy metal ions along food chains, and the associated risk factors of heavy metal ions on public health safety are a global concern of top priority. Hence, developing low-cost analytical protocols capable of rapid, selective, sensitive, and accurate detection of heavy metal ions in environmental samples and consumable products is of global public health interest. Conventional flame atomic absorption spectroscopy, graphite furnace atomic absorption spectroscopy, atomic emission spectroscopy, inductively coupled plasma-optical emission spectroscopy, inductively coupled plasma-mass spectroscopy, X-ray diffractometry, and X-ray fluorescence have been well-developed for HMIs and trace element analysis with excellent but varying degrees of sensitivity, selectivity, and accuracy. In addition to high instrumental running and maintenance costs and specialized personnel training, these instruments are not portable, limiting their practicality for on-demand, in situ, field study, or point-of-need HMI detection. Increases in the use of electrochemical and colorimetric techniques for heavy metal ion detections arise because of portable instrumentation, high sensitivity and selectivity, cost-effectiveness, small size requirements, rapidity, and visual detection of colorimetric nanosensors that facilitate on-demand, in situ, and field heavy metal ion detections. This review highlights the new approach to low-cost, rapid, selective, sensitive, and accurate detection of heavy metal ions in ecosystems (soil, water, air) and consumable products. Specifically, the review highlights low-cost, portable, and recent advances in smartphone-operated screen-printed electrodes (SPEs), plastic chip SPES, and carbon fiber paper-based nanosensors for environmental heavy metal ion detection. In addition, the review highlights recent advances in colorimetric nanosensors for heavy metal ion detection requirements. The review provides the advantages of electrochemical and optical nanosensors over the conventional methods of HMI analyses. The review further provides in-depth coverage of the detection of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) ions in the ecosystem, with emphasis on environmental and biological samples. In addition, the review discusses the advantages and challenges of the current electrochemical and colorimetric nanosensors protocol for heavy metal ion detection. It provides insight into the future directions in the use of the electrochemical and colorimetric nanosensors protocol for heavy metal ion detection.

Trace elements in Foodstuffs from the Mediterranean Basin-Occurrence, Risk Assessment, Regulations, and Prevention strategies: A review

Trace elements (TEs) are chemical compounds that naturally occur in the earth's crust and in living organisms at low concentrations. Anthropogenic activities can significantly increase the level of TEs in the environment and finally enter the food chain. Toxic TEs like cadmium, lead, arsenic, and mercury have no positive role in a biological system and can cause harmful effects on human health. Ingestion of contaminated food is a typical route of TEs intake by humans. Recent data about the occurrence of TEs in food available in the Mediterranean countries are considered in this review. Analytical methods are also discussed. Furthermore, a discussion of existing international agency regulations will be given. The risk associated with the dietary intake of TEs was estimated by considering consumer exposure and threshold values such as Benchmark dose lower confidence limit and provisional tolerable weekly intake established by the European Food Safety Authority and the Joint FAO/WHO Expert Committee on Food Additives, respectively. Finally, several remediation approaches to minimize TE contamination in foodstuffs were discussed including chemical, biological, biotechnological, and nanotechnological methods. The results of this study proved the occurrence of TEs contamination at high levels in vegetables and fish from some Mediterranean countries. Lead and cadmium are more abundant in foodstuffs than other toxic trace elements. Geographical variations in TE contamination of food crops clearly appear, with a greater risk in developing countries. There is still a need for the regular monitoring of these toxic element levels in food items to ensure consumer protection.

Capillary Flow-Driven Microfluidics Combined with a Paper Device for Fast User-Friendly Detection of Heavy Metals in Water

Human exposure to heavy metals is a concerning global problem because of its detrimental effect on our health and ecosystem. Assessing the levels of these metals is cost- and labor-intensive and nonuser friendly because current analysis approaches typically rely on heavy instrumentations like inductively coupled plasma-mass spectrometry, which is only possible in centralized labs. Hence, simple economical detection methods are in high demand in developing countries and areas with insufficient infrastructure, professional experts, and appropriate environmental treatment. Several microfluidic paper-based analytical devices have been reported as promising alternatives to conventional testing methods for on-site heavy metal detection. Paper-based microfluidics are advantageous because of their simple fabrication, biodegradability, low cost, and ability to operate without pumps. However, typical assay times for current platforms are slow, and they typically rely on pipetting a fixed volume into the assay cards. This adds complexity in actual field scenarios. Here, we report a novel, inexpensive, and straightforward capillary-driven microfluidic device combined with paper for rapid and user-friendly detection of Ni(II), Cu(II), and Fe(III) in water. A colorimetric approach was adopted to quantify these metals. The device was able to produce a homogeneous color signal within 8 s of sample insertion. The limit of detection and limit of quantification were calculated to be 2 and 6.67 ppm for nickel, 0.3 and 1 ppm for Cu, and 1.1 and 3.67 ppm for Fe, respectively. The majority (>90%) of the collected samples showed recovery in the 80-110% range with acceptable accuracy and precision (<15% RSD) for a colorimetric device. This technique can be beneficial for rapidly assessing heavy metal exposure in drinking and surface water at drastically reduced assay time and is the first example of capillary flow-driven microfluidic devices as a transport medium for heavy metal detection.

Identifying the “Dangshan” Physiological Disease of Pear Woolliness Response via Feature-Level Fusion of Near-Infrared Spectroscopy and Visual RGB Image

The “Dangshan” pear woolliness response is a physiological disease that causes large losses for fruit farmers and nutrient inadequacies.The cause of this disease is predominantly a shortage of boron and calcium in the pear and water loss from the pear. This paper used the fusion of near-infrared Spectroscopy (NIRS) and Computer Vision Technology (CVS) to detect the woolliness response disease of “Dangshan” pears. This paper employs the merging of NIRS features and image features for the detection of “Dangshan” pear woolliness response disease. Near-infrared Spectroscopy (NIRS) reflects information on organic matter containing hydrogen groups and other components in various biochemical structures in the sample under test, and Computer Vision Technology (CVS) captures image information on the disease. This study compares the results of different fusion models. Compared with other strategies, the fusion model combining spectral features and image features had better performance. These fusion models have better model effects than single-feature models, and the effects of these models may vary according to different image depth features selected for fusion modeling. Therefore, the model results of fusion modeling using different image depth features are further compared. The results show that the deeper the depth model in this study, the better the fusion modeling effect of the extracted image features and spectral features. The combination of the MLP classification model and the Xception convolutional neural classification network fused with the NIR spectral features and image features extracted, respectively, was the best combination, with accuracy (0.972), precision (0.974), recall (0.972), and F1 (0.972) of this model being the highest compared to the other models. This article illustrates that the accuracy of the “Dangshan” pear woolliness response disease may be considerably enhanced using the fusion of near-infrared spectra and image-based neural network features. It also provides a theoretical basis for the nondestructive detection of several techniques of spectra and pictures.

Prediction Models for the Content of Calcium, Boron and Potassium in the Fruit of 'Huangguan' Pears Established by Using Near-Infrared Spectroscopy

It has been proved that the imbalance of the proportion of elements of 'Huangguan' pears in the pulp and peel, especially calcium, boron and potassium, may be important factors that can seriously affect the pears' appearance quality and economic benefits. The objective of this study was to predict the content of calcium, boron and potassium in the pulp and peel of 'Huangguan' pears nondestructively and conveniently by using near-infrared spectroscopy (900-1700 nm) technology. Firstly, 12 algorithms were used to preprocess the original spectral data. Then, based on the original and preprocessed spectral data, full-band prediction models were established by using Partial Least Squares Regression and Gradient Boosting Regression Tree. Finally, the characteristic wavelengths were extracted by Genetic Algorithms to establish the characteristic wavelength prediction models. According to the prediction results, the value of the determination coefficient of the prediction sets of the best prediction models for the three elements all reached ideal levels, and the values of their Relative analysis error also showed high levels. Therefore, the micro near-infrared spectrometer based on machine learning can predict the content of calcium, boron and potassium in the pulp and peel of 'Huangguan' pears accurately and quickly. The results also provide an important scientific theoretical basis for further research on the degradation of the quality of 'Huangguan' pears caused by a lack of nutrients.

A novel smartphone-based electrochemical cell sensor for evaluating the toxicity of heavy metal ions Cd2+, Hg2+, and Pb2+ in rice

A novel smartphone-based electrochemical cell sensor was developed to evaluate the toxicity of heavy metal ions, such as cadmium (Cd²⁺), lead (Pb²⁺), and mercury (Hg²⁺) ions on Hep G2 cells. The cell sensor was fabricated with reduced graphene oxide (RGO)/molybdenum sulfide (MoS₂) composites to greatly improve the biological adaptability and amplify the electrochemical signals. Differential pulse voltammetry (DPV) was employed to measure the electrical signals induced by the toxicity of heavy metal ions. The results showed that Cd²⁺, Hg²⁺, and Pb²⁺ significantly reduced the viability of Hep G2 cells in a dose-dependent manner. The IC₅₀ values obtained by this method were 49.83, 36.94, and 733.90 μM, respectively. A synergistic effect was observed between Cd²⁺ and Pb²⁺ and between Hg²⁺ and Pb²⁺, and an antagonistic effect was observed between Cd²⁺ and Hg²⁺, and an antagonistic effect at low doses and an additive effect at high doses were found in the ternary mixtures of Cd²⁺, Hg²⁺, and Pb²⁺. These electrochemical results were confirmed via MTT assay, SEM and TEM observation, and flow cytometry. Therefore, this new electrochemical cell sensor provided a more convenient, sensitive, and flexible toxicity assessment strategy than traditional cytotoxicity assessment methods.

Highly selective simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii) in water samples using microfluidic paper-based analytical devices

A new paper-based analytical device design was fabricated by a wax printing method for simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii). Colorimetry was used to quantify these heavy metal ions using bathocuproine (Bc), dimethylglyoxime (DMG), dithizone (DTZ), and 4-(2-pyridylazo) resorcinol (PAR) as complexing agents. The affinity of complexing agents to heavy metal ions is dependent on the formation constant (Kf). To enhance the selectivity for heavy metal ion determination, the new device was designed with two pretreatment zones, where masking agents remove the interfering ions. It was found that two pretreatment zones worked better than a single pretreatment zone at removing interferences. The reaction time, sample and complexing agent volumes, and complexing agent concentrations were optimized. The analytical results were achieved with the lowest detectable concentrations of 0.32, 0.59, 5.87, 0.20, and 0.11 mg L-1 for Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii), respectively. The linear ranges were found to be 0.32-63.55 mg L-1 (Cu(ii)), 0.59-4.71 mg L-1 (Co(ii)), 5.87-352.16 mg L-1 (Ni(ii)), 0.20-12.04 mg L-1 (Hg(ii)), and 0.11-0.55 mg L-1 (Mn(ii)). The lowest detectable concentration and linearity for the five metal ions allow the application of this device for the determination of heavy metal ions in various water samples. The sensor showed high selectivity and efficiency for simultaneous determination of Cu(ii), Co(ii), Ni(ii), Hg(ii), and Mn(ii) in drinking, tap, and pond water samples on a single device and detection with the naked eye. The results illustrated that the proposed sensor showed good accuracy and precision agreement with the standard ICP-OES method.

A 3D origami paper-based analytical device combined with PVC membrane for colorimetric assay of heavy metal ions: Application to determination of Cu(II) in water samples

Microfluidic paper-based analytical devices (μPADs) as a potentially powerful analytical platform have recently gained significant attention for on-site monitoring of heavy metal ions, which are one of the most significant environmental concern because of non-degradability and high toxicity. The commonly applied μPADs suffers from some defects, such as heterogeneous deposition of reagent, resulting in poor detection limits and low sensitivity. So, in this work, a three-dimensional origami μPAD combined with PVC Membrane was developed, which can manage problems of movement of colored products or leaching out the dye and leading to color heterogeneity in the detection zones. Furthermore, a waste layer was added to μPAD for loading of more amounts of the analyte, which results in improvement of detection limit. As a proof of concept, the μPAD was used for the analysis of Cu²⁺ ion. For this purpose, pyrocatechol violet and chrome azurol S as colorimetric reagents were doped into PVC membrane and injected in the detection zone. The proposed μPAD was presented good linearity in the ranges of 5.0-1400.0 and 5.0-200.0 mg L^-1, and the limits of detections of 1.7 and 1.9 mg L^-1 in presence of chrome azurol S and pyrocatechol violet, respectively.