Rapid Quantitative Determination of Multiple Pesticide Residues in Mango Fruits by Surface-Enhanced Raman Spectroscopy

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Towards solving the reproducibility crisis in surface-enhanced Raman spectroscopy-based pesticide detection

Growing concerns about pesticide residues in agriculture are pushing the scientific community to develop innovative and efficient methods for detecting these substances at low concentrations down to the molecular level. In this context, surface-enhanced Raman spectroscopy (SERS) is a powerful analytical method that has so far already undergone some validation for its effectiveness in pesticide detection. However, despite its great potential, SERS faces significant difficulties obtaining reproducible and accurate pesticide spectra, particularly for some of the most widely used pesticides, such as malathion, chlorpyrifos, and imidacloprid. Those inconsistencies can be attributed to several factors, such as interactions between pesticides and SERS substrates and the variety of substrates and solvents used. In addition, differences in the equipment used to obtain SERS spectra and the lack of standards for control experiments further complicate the reproducibility and reliability of SERS data. This review systematically discusses the problems mentioned above, including a comprehensive analysis of the challenges in precisely evaluating SERS spectra for pesticide detection. We not only point out the existing limitations of the method, which can be traced in previous review works, but also offer practical recommendations to improve the quality and comparability of SERS spectra, thereby expanding the potential applications of the method in such an essential field as pesticide detection.

Toxicity evaluation of novel imidacloprid nanoribbons, using somatic mutation and fitness indexes in Drosophila melanogaster

Nanoribbons of imidacloprid, a systemic and chloronicotinyl insecticide, were successfully synthesized by laser-induced fragmentation/exfoliation of imidacloprid powders suspended in water, with widths ranging from 160 to 470 nm, lengths in the micron scale, and thickness of a few atoms layers. The aim of the present study was to examine the effects of acute and chronic exposure to imidacloprid (IMC) bulk and compare its effects with synthesized imidacloprid nanoribbons (IMCNR) on larval and adult viability, developmental time, olfactory capacity, longevity, productivity, and genotoxicity in Drosophila melanogaster. Larvae or adults were exposed at 0.01, 0.02, or 0.03 ppm to IMC or IMCNR. Results demonstrated that IMCNR produced a significant reduction in viability and olfactory ability. IMC did not significantly alter viability and olfactory ability. Similarly, marked differences on longevity were detected between treatment with IMC and IMCNR where the lifespan of males treated with IMC was significantly higher than control while IMCNR produced a reduction. As for productivity, developmental time, and genotoxicity, no marked differences were found between both forms of IMC.

Luminescent Probe Based on Terbium-Carbon Quantum Dots for the Quantification of Imidacloprid in Caneberries

We propose a modification of terbium-sensitized luminescence (TSL) by means of the introduction of nanoparticles to improve the sensitivity and selectivity of the analytical methods. TSL detection is usually based on the complexation between fluorescent organic compounds (the analytes) and terbium. The organic compound is then excited, and, after an energy transfer towards terbium, the latter emits the luminescence signal. Here, the modification consists of the introduction of nanoparticles (carbon quantum dots, CQDs) into the system. The carboxylic groups of CQDs react with terbium, providing an interesting time-resolved luminescence probe. We applied this system for the determination of the neonicotinoid imidacloprid (IMID). When IMID was introduced in the terbium-CQDs system, the luminescent signal (λexc/λem of 256/545 nm) was quenched, proportionally to IMID concentration in the range of 100-2500 ng·mL-1, obtaining a limit of detection of 30 ng·mL-1. A method detection limit of 0.9 mg·kg-1 was reached in caneberries, thus complying with the maximum residue level of 5 mg·kg-1 established by Codex Alimentarius. We performed recovery experiments in caneberries (blackberries, blueberries, raspberries, and mulberries), obtaining recovery yields close to 100% in all cases. These results show that the use of terbium ions-nanoparticles luminescence probes can be useful for screening purposes in quality control laboratories.

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables.

Simultaneous, Label-Free and High-throughput SERS Detection of Multiple Pesticides on Ag@Three-Dimensional Silica Photonic Microsphere Array

Rapid identification and quantitative simultaneous analysis for multiple pesticide in real samples based on surface-enhanced Raman spectroscopy (SERS) is still a challenge because of sample complexity, reproducibility, and stability of SERS substrate. With use of colloidal silver nanoparticles loaded three-dimensional (3D) silica photonic microspheres (SPMs) array as the analytical platform, a SERS-based array assay for multiple pesticides was developed in this work. The silver nanoparticles were fixed into the gaps formed by the self-assembled nanospheres of the 3D SPMs to produce "hot spots", on which the Raman enhanced effect was up to 9.86 × 10⁷ and the maximum electric field enhancement effect reached to 9.75 times, ensuring the target pesticides on the surface of the SERS-substrate integrated SPM can be detected sensitively. Using 2,4-dichlorophenoxyacetic acid (2,4-D), glyphosate, and imidacloprid as the testing pesticides, the label-free and high-throughput SERS assay for simultaneous detection of the pesticides was established, giving good linear detection ranges (0.1-204.8 μg/mL for 2,4-D, 0.3-247.9 μg/mL for glyphosate, and 0.2-204.8 μg/mL for imidacloprid) and low detection limits (3.03 ng/mL for 2,4-D, 3.14 ng/mL for glyphosate, and 8.82 ng/mL for imidacloprid). The spiked recovery rates in the real samples were measured in the range of 82-112%, which was consistent with that of the classical standard methods. The label-free 3D SERS array analytical platform provides a powerful tool for high-throughput and low-cost screening of multiple pesticide residues in real samples.